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MOODY'S ANALYTICS

INCORPORATING DATA AS OF NOVEMBER 2011 INCORPORATING DATA AS OF NOVEMBER 2011 Housing Market Monitor Housing Market Monitor Housing Market Monitor

Executive SummaryExecutive Summary By Sunayana MehraBy Sunayana Mehra NOVEMBER 17, 2011NOVEMBER 17, 2011

Housing indicators were mixed in September, leaving the picture of a market treading along bottom largely untouched. Homebuilding Housing indicators were mixed in September, leaving the picture of a market treading along bottom largely untouched. Homebuilding Housing indicators were mixed in September, leaving the picture of a market treading along bottom largely untouched. Homebuilding advanced more strongly than expected, but home sales lost ground. Third quarter averages tell the same story. Sales and construction advanced more strongly than expected, but home sales lost ground. Third quarter averages tell the same story. Sales and construction advanced more strongly than expected, but home sales lost ground. Third quarter averages tell the same story. Sales and construction remain close to the average pace they have maintained since the market hit bottom in 2009. National house prices registered an remain close to the average pace they have maintained since the market hit bottom in 2009. National house prices registered an remain close to the average pace they have maintained since the market hit bottom in 2009. National house prices registered an increase compared with the second quarter on a not seasonally adjusted basis. This gain reflects in part a decline in the share of distress increase compared with the second quarter on a not seasonally adjusted basis. This gain reflects in part a decline in the share of distress increase compared with the second quarter on a not seasonally adjusted basis. This gain reflects in part a decline in the share of distress sales. sales. sales.

The expansion of the Home Affordable Refinance Program announced by the Obama administration late in October is a very positive The expansion of the Home Affordable Refinance Program announced by the Obama administration late in October is a very positive The expansion of the Home Affordable Refinance Program announced by the Obama administration late in October is a very positive step toward keeping the expansion in place. As such, HARP will not live up to the initial expectations of four million to five million step toward keeping the expansion in place. As such, HARP will not live up to the initial expectations of four million to five million step toward keeping the expansion in place. As such, HARP will not live up to the initial expectations of four million to five million refinancings, but the program will ultimately meaningfully boost the broader economy as financially stressed households will benefit refinancings, but the program will ultimately meaningfully boost the broader economy as financially stressed households will benefit refinancings, but the program will ultimately meaningfully boost the broader economy as financially stressed households will benefit from much lower mortgage payments. It will also help the housing market by forestalling some mortgage defaults. from much lower mortgage payments. It will also help the housing market by forestalling some mortgage defaults. from much lower mortgage payments. It will also help the housing market by forestalling some mortgage defaults.

Initial filings are rising the most quickly, consistent with servicers starting more foreclosure proceedings on homes in lateInitial filings are rising the most quickly, consistent with servicers starting more foreclosure proceedings on homes in lateInitial filings are rising the most quickly, consistent with servicers starting more foreclosure proceedings on homes in late‐‐‐stage stage stage delinquency. If, as expected, this trend of rising foreclosures continues, house prices will fall. More of these homes will end up as a delinquency. If, as expected, this trend of rising foreclosures continues, house prices will fall. More of these homes will end up as a delinquency. If, as expected, this trend of rising foreclosures continues, house prices will fall. More of these homes will end up as a discounted distress sale at the same time as demand remains soft for homeownership. A number of uncertainties surround the timing discounted distress sale at the same time as demand remains soft for homeownership. A number of uncertainties surround the timing discounted distress sale at the same time as demand remains soft for homeownership. A number of uncertainties surround the timing of foreclosures, however. Not only is the settlement between the state AGs and large servicers progressing in fits and starts, but of foreclosures, however. Not only is the settlement between the state AGs and large servicers progressing in fits and starts, but of foreclosures, however. Not only is the settlement between the state AGs and large servicers progressing in fits and starts, but changes in foreclosure laws/programs in several states could delay the process. changes in foreclosure laws/programs in several states could delay the process. changes in foreclosure laws/programs in several states could delay the process.

A bloated inventory of homes is weighing on house prices and homebuilding, but the excess has been stable and will be drawn down A bloated inventory of homes is weighing on house prices and homebuilding, but the excess has been stable and will be drawn down A bloated inventory of homes is weighing on house prices and homebuilding, but the excess has been stable and will be drawn down over the next year to 18 months. The exceptionally slow pace of homebuilding since 2009 that is resulting in a recordover the next year to 18 months. The exceptionally slow pace of homebuilding since 2009 that is resulting in a recordover the next year to 18 months. The exceptionally slow pace of homebuilding since 2009 that is resulting in a record‐‐‐low inventory of low inventory of low inventory of new homes, combined with strengthening household growth, will help absorb the excess stock of homes over the next year. new homes, combined with strengthening household growth, will help absorb the excess stock of homes over the next year. new homes, combined with strengthening household growth, will help absorb the excess stock of homes over the next year.

The risk of recession is retreating but remains the main downside threat to housing. Many uncertainties also remain about the timing The risk of recession is retreating but remains the main downside threat to housing. Many uncertainties also remain about the timing The risk of recession is retreating but remains the main downside threat to housing. Many uncertainties also remain about the timing of foreclosures that could easily delay the end of the price correction. A significant downside risk over the next two years centers on of foreclosures that could easily delay the end of the price correction. A significant downside risk over the next two years centers on of foreclosures that could easily delay the end of the price correction. A significant downside risk over the next two years centers on the building industrythe building industrythe building industry’’’s capacity, which has contracted considerably since the top of the housing boom. The construction outlook may s capacity, which has contracted considerably since the top of the housing boom. The construction outlook may s capacity, which has contracted considerably since the top of the housing boom. The construction outlook may be overly optimistic because homebuilders may not be able to increase production quickly. be overly optimistic because homebuilders may not be able to increase production quickly. be overly optimistic because homebuilders may not be able to increase production quickly.

This month the Housing Monitor will be updated with the mortgage market conditions for the third quarter of 2011. EarlyThis month the Housing Monitor will be updated with the mortgage market conditions for the third quarter of 2011. EarlyThis month the Housing Monitor will be updated with the mortgage market conditions for the third quarter of 2011. Early‐‐‐stage stage stage delinquency rates rose during the period while latedelinquency rates rose during the period while latedelinquency rates rose during the period while late‐‐‐stage delinquency rates fell; however, there is substantial regional variation. stage delinquency rates fell; however, there is substantial regional variation. stage delinquency rates fell; however, there is substantial regional variation. Mortgage applications rose over the last three months as mortgage interest rates fell. Overall first mortgage origination volumes Mortgage applications rose over the last three months as mortgage interest rates fell. Overall first mortgage origination volumes Mortgage applications rose over the last three months as mortgage interest rates fell. Overall first mortgage origination volumes remained elevated in recent quarters primarily because of increased refinancing despite tight underwriting standards. A discussion of remained elevated in recent quarters primarily because of increased refinancing despite tight underwriting standards. A discussion of remained elevated in recent quarters primarily because of increased refinancing despite tight underwriting standards. A discussion of the proposed HARP program is also included. the proposed HARP program is also included. the proposed HARP program is also included.

Housing Market Monitor

MOODY'S ANALYTICS / Housing Market Monitor / Copyright© 2011 / www.economy.com 1 / 50

Housing MonthlyHousing Monthly By Celia ChenBy Celia Chen NOVEMBER 17, 2011NOVEMBER 17, 2011

The housing market continues to ail as sales and construction tread along the bottom. The housing market continues to ail as sales and construction tread along the bottom. The housing market continues to ail as sales and construction tread along the bottom.

Expansion of HARP will meaningfully boost the broader economy, as financially stressed households will benefit from much lower Expansion of HARP will meaningfully boost the broader economy, as financially stressed households will benefit from much lower Expansion of HARP will meaningfully boost the broader economy, as financially stressed households will benefit from much lower mortgage payments. mortgage payments. mortgage payments.

The servicers are pushing more distressed loans through the pipeline. The servicers are pushing more distressed loans through the pipeline. The servicers are pushing more distressed loans through the pipeline.

Disposition of distressed homes will account for an increasing share of sales and will cause the remaining modest 3% decline in Disposition of distressed homes will account for an increasing share of sales and will cause the remaining modest 3% decline in Disposition of distressed homes will account for an increasing share of sales and will cause the remaining modest 3% decline in national home prices. national home prices. national home prices.

Housing indicators were mixed in September, leaving largely untouched a picture of a market treading along bottom. Homebuilding Housing indicators were mixed in September, leaving largely untouched a picture of a market treading along bottom. Homebuilding Housing indicators were mixed in September, leaving largely untouched a picture of a market treading along bottom. Homebuilding advanced more strongly than expected, but home sales lost ground. Third quarter averages tell the same story. Sales and construction advanced more strongly than expected, but home sales lost ground. Third quarter averages tell the same story. Sales and construction advanced more strongly than expected, but home sales lost ground. Third quarter averages tell the same story. Sales and construction remain close to the average pace they have maintained since the market hit bottom in 2009. The recent data do hold some positives. remain close to the average pace they have maintained since the market hit bottom in 2009. The recent data do hold some positives. remain close to the average pace they have maintained since the market hit bottom in 2009. The recent data do hold some positives. Permit issuance has been rising year over year for five months, the longest streak since spring 2010, and singlePermit issuance has been rising year over year for five months, the longest streak since spring 2010, and singlePermit issuance has been rising year over year for five months, the longest streak since spring 2010, and single‐‐‐family permitting is up for family permitting is up for family permitting is up for two consecutive months. Builders are feeling slightly less pessimistic. The National Association of Homebuilderstwo consecutive months. Builders are feeling slightly less pessimistic. The National Association of Homebuilderstwo consecutive months. Builders are feeling slightly less pessimistic. The National Association of Homebuilders’ ’ ’ housing market index housing market index housing market index remains well below the 50 mark that indicates rising optimism but posted its largest oneremains well below the 50 mark that indicates rising optimism but posted its largest oneremains well below the 50 mark that indicates rising optimism but posted its largest one‐‐‐month gain in over one year.month gain in over one year.month gain in over one year.

National house prices registered an increase compared with the second quarter on a not seasonally adjusted basis. This gain reflects in part a National house prices registered an increase compared with the second quarter on a not seasonally adjusted basis. This gain reflects in part a National house prices registered an increase compared with the second quarter on a not seasonally adjusted basis. This gain reflects in part a decline in the share of distressed sales. According to Zillow, the share of foreclosure sales dropped from nearly 20% to 18%. However, decline in the share of distressed sales. According to Zillow, the share of foreclosure sales dropped from nearly 20% to 18%. However, decline in the share of distressed sales. According to Zillow, the share of foreclosure sales dropped from nearly 20% to 18%. However, compared with a year earlier, the share is much higher. Correspondingly, house prices are still down by 2% to 5% year over year.compared with a year earlier, the share is much higher. Correspondingly, house prices are still down by 2% to 5% year over year.compared with a year earlier, the share is much higher. Correspondingly, house prices are still down by 2% to 5% year over year.

Homebuilding may be weak, but it did help to give the economy a boost in the third quarter. Real investment in fixed residential real estate Homebuilding may be weak, but it did help to give the economy a boost in the third quarter. Real investment in fixed residential real estate Homebuilding may be weak, but it did help to give the economy a boost in the third quarter. Real investment in fixed residential real estate advanced in the second and third quarters, marking the first backadvanced in the second and third quarters, marking the first backadvanced in the second and third quarters, marking the first back‐‐‐tototo‐‐‐back gain since the peak of the housing boom. The impact on broader back gain since the peak of the housing boom. The impact on broader back gain since the peak of the housing boom. The impact on broader growth is small, however, with the third quarter nominal increase accounting for less than 1% of the increase in GDP.growth is small, however, with the third quarter nominal increase accounting for less than 1% of the increase in GDP.growth is small, however, with the third quarter nominal increase accounting for less than 1% of the increase in GDP.

HARP 2

The expansion of the Home Affordable Refinance program announced by the Obama administration late in October is a very positive step The expansion of the Home Affordable Refinance program announced by the Obama administration late in October is a very positive step The expansion of the Home Affordable Refinance program announced by the Obama administration late in October is a very positive step toward keeping the expansion in place, but it is not a magic bullet. The expanded and extended program lifts the 125 LTV cap, eliminates toward keeping the expansion in place, but it is not a magic bullet. The expanded and extended program lifts the 125 LTV cap, eliminates toward keeping the expansion in place, but it is not a magic bullet. The expanded and extended program lifts the 125 LTV cap, eliminates some of Freddie and Fanniesome of Freddie and Fanniesome of Freddie and Fannie’’’s loan origination fees, and extends the program from June 2012 to the end of 2013. These measures will enable s loan origination fees, and extends the program from June 2012 to the end of 2013. These measures will enable s loan origination fees, and extends the program from June 2012 to the end of 2013. These measures will enable an additional 1.6 million homeowners to refinance, for a total of 2.85 million HARP loans. As such, HARP will not live up to the initial an additional 1.6 million homeowners to refinance, for a total of 2.85 million HARP loans. As such, HARP will not live up to the initial an additional 1.6 million homeowners to refinance, for a total of 2.85 million HARP loans. As such, HARP will not live up to the initial expectations of four million to five million refinancings, but the program will ultimately meaningfully boost the broader economy because expectations of four million to five million refinancings, but the program will ultimately meaningfully boost the broader economy because expectations of four million to five million refinancings, but the program will ultimately meaningfully boost the broader economy because financially stressed households will benefit from much lower mortgage payments. It will also help the housing market by forestalling some financially stressed households will benefit from much lower mortgage payments. It will also help the housing market by forestalling some financially stressed households will benefit from much lower mortgage payments. It will also help the housing market by forestalling some mortgage defaults. There are still a number of households in the foreclosure pipeline, however, that will not benefit from HARP and will mortgage defaults. There are still a number of households in the foreclosure pipeline, however, that will not benefit from HARP and will mortgage defaults. There are still a number of households in the foreclosure pipeline, however, that will not benefit from HARP and will weigh on the housing market and economy over the next couple of years.weigh on the housing market and economy over the next couple of years.weigh on the housing market and economy over the next couple of years.



Foreclosure update

Despite the lack of settlement over improper foreclosure processing penalties between the 50 state attorneys general and the nationDespite the lack of settlement over improper foreclosure processing penalties between the 50 state attorneys general and the nationDespite the lack of settlement over improper foreclosure processing penalties between the 50 state attorneys general and the nation’’’s s s largest mortgage servicers, the servicers are pushing more distressed loans through the pipeline. According to RealtyTrac, foreclosure filings largest mortgage servicers, the servicers are pushing more distressed loans through the pipeline. According to RealtyTrac, foreclosure filings largest mortgage servicers, the servicers are pushing more distressed loans through the pipeline. According to RealtyTrac, foreclosure filings are trending up, with monthare trending up, with monthare trending up, with month‐‐‐tototo‐‐‐month gains in August and again in October that bring filings up to their fastest pace since April. Initial filings month gains in August and again in October that bring filings up to their fastest pace since April. Initial filings month gains in August and again in October that bring filings up to their fastest pace since April. Initial filings are rising the most quickly, consistent with servicers starting more foreclosure proceedings on homes in lateare rising the most quickly, consistent with servicers starting more foreclosure proceedings on homes in lateare rising the most quickly, consistent with servicers starting more foreclosure proceedings on homes in late‐‐‐stage delinquency; stage delinquency; stage delinquency; preforeclosures nearly doubled since July, compared with a 38% annualized gain for total filings.preforeclosures nearly doubled since July, compared with a 38% annualized gain for total filings.preforeclosures nearly doubled since July, compared with a 38% annualized gain for total filings.

If, as expected, this trend of rising foreclosures continues, house prices will fall. More of these homes will end up as a discounted distressed If, as expected, this trend of rising foreclosures continues, house prices will fall. More of these homes will end up as a discounted distressed If, as expected, this trend of rising foreclosures continues, house prices will fall. More of these homes will end up as a discounted distressed home sale at the same time as demand for homeownership remains soft. A number of uncertainties surround the timing of foreclosures, home sale at the same time as demand for homeownership remains soft. A number of uncertainties surround the timing of foreclosures, home sale at the same time as demand for homeownership remains soft. A number of uncertainties surround the timing of foreclosures, however. Not only is the settlement between the state attorneys general and large servicers progressing in fits and starts, but changes in however. Not only is the settlement between the state attorneys general and large servicers progressing in fits and starts, but changes in however. Not only is the settlement between the state attorneys general and large servicers progressing in fits and starts, but changes in foreclosure laws and programs in several states could delay the process. Foreclosure timelines in the New York tristate area are among the foreclosure laws and programs in several states could delay the process. Foreclosure timelines in the New York tristate area are among the foreclosure laws and programs in several states could delay the process. Foreclosure timelines in the New York tristate area are among the nationnationnation’’’s longest already, and programs instituted over the past several years may make it difficult to accommodate the large number of s longest already, and programs instituted over the past several years may make it difficult to accommodate the large number of s longest already, and programs instituted over the past several years may make it difficult to accommodate the large number of foreclosures that servicers will likely unleash in coming months. In Nevada and Oregon, new rules are in place that effectively lengthen the foreclosures that servicers will likely unleash in coming months. In Nevada and Oregon, new rules are in place that effectively lengthen the foreclosures that servicers will likely unleash in coming months. In Nevada and Oregon, new rules are in place that effectively lengthen the foreclosure timetableforeclosure timetableforeclosure timetable———at least temporarily. Legislators in Michigan are contemplating changes to foreclosure laws that will require at least temporarily. Legislators in Michigan are contemplating changes to foreclosure laws that will require at least temporarily. Legislators in Michigan are contemplating changes to foreclosure laws that will require foreclosures to go through the court system. Bucking the trend, Floridaforeclosures to go through the court system. Bucking the trend, Floridaforeclosures to go through the court system. Bucking the trend, Florida’’’s Governor Rick Scott is pushing to take foreclosures out of the s Governor Rick Scott is pushing to take foreclosures out of the s Governor Rick Scott is pushing to take foreclosures out of the courts to expedite the process. According to RealtyTrac, Florida has the nationcourts to expedite the process. According to RealtyTrac, Florida has the nationcourts to expedite the process. According to RealtyTrac, Florida has the nation’’’s second highest foreclosure rate.s second highest foreclosure rate.s second highest foreclosure rate.

Excess inventories stable

A bloated inventory of homes continues to weigh on house prices and homebuilding, but the excess has been stable and will be drawn down A bloated inventory of homes continues to weigh on house prices and homebuilding, but the excess has been stable and will be drawn down A bloated inventory of homes continues to weigh on house prices and homebuilding, but the excess has been stable and will be drawn down over the next 12 to 18 months. Correction of this imbalance informs the projection of substantially stronger residential construction by the over the next 12 to 18 months. Correction of this imbalance informs the projection of substantially stronger residential construction by the over the next 12 to 18 months. Correction of this imbalance informs the projection of substantially stronger residential construction by the end of next year.end of next year.end of next year.

MoodyMoodyMoody’’’s Analytics defines excess inventories as the difference between homes that are currently undesirably vacant and the number of s Analytics defines excess inventories as the difference between homes that are currently undesirably vacant and the number of s Analytics defines excess inventories as the difference between homes that are currently undesirably vacant and the number of undesirably vacant homes that would prevail under normal conditions. Homes that are undesirably vacant are vacant homes that are vacant undesirably vacant homes that would prevail under normal conditions. Homes that are undesirably vacant are vacant homes that are vacant undesirably vacant homes that would prevail under normal conditions. Homes that are undesirably vacant are vacant homes that are vacant and for sale, vacant and for rent, and vacant and held off the market for other reasons. Based on calculations using the data from the Census and for sale, vacant and for rent, and vacant and held off the market for other reasons. Based on calculations using the data from the Census and for sale, vacant and for rent, and vacant and held off the market for other reasons. Based on calculations using the data from the Census BureauBureauBureau’’’s quarterly housing vacancy survey, excess inventories have been stable at an average of 1.4 million units since the third quarter of s quarterly housing vacancy survey, excess inventories have been stable at an average of 1.4 million units since the third quarter of s quarterly housing vacancy survey, excess inventories have been stable at an average of 1.4 million units since the third quarter of 2010. Although this overhang that built up during the housing boom is quite high, it has come down from the peak of 1.8 million in the 2010. Although this overhang that built up during the housing boom is quite high, it has come down from the peak of 1.8 million in the 2010. Although this overhang that built up during the housing boom is quite high, it has come down from the peak of 1.8 million in the second quarter of last year. The exceptionally slow homebuilding since 2009 that is resulting in a record low inventory of new homes, second quarter of last year. The exceptionally slow homebuilding since 2009 that is resulting in a record low inventory of new homes, second quarter of last year. The exceptionally slow homebuilding since 2009 that is resulting in a record low inventory of new homes, combined with strengthening household growth, will help absorb the excess stock of homes over the next year. Homebuilding remains slow combined with strengthening household growth, will help absorb the excess stock of homes over the next year. Homebuilding remains slow combined with strengthening household growth, will help absorb the excess stock of homes over the next year. Homebuilding remains slow at an annual average pace of 600,000 units (including manufactured housing). Concurrently, the economic recovery, although weak, has at an annual average pace of 600,000 units (including manufactured housing). Concurrently, the economic recovery, although weak, has at an annual average pace of 600,000 units (including manufactured housing). Concurrently, the economic recovery, although weak, has encouraged household growth to accelerate to an estimated pace of 1.4 million new households a year, well above the pace of new encouraged household growth to accelerate to an estimated pace of 1.4 million new households a year, well above the pace of new encouraged household growth to accelerate to an estimated pace of 1.4 million new households a year, well above the pace of new construction. This gap of 800,000 units of demand over supply will help eat through the 1.4 million excess homes by midconstruction. This gap of 800,000 units of demand over supply will help eat through the 1.4 million excess homes by midconstruction. This gap of 800,000 units of demand over supply will help eat through the 1.4 million excess homes by mid‐‐‐2013. Indeed, 2013. Indeed, 2013. Indeed, expectations that job growth will accelerate next year, which will spur even greater household growth, imply that the supply balance may be expectations that job growth will accelerate next year, which will spur even greater household growth, imply that the supply balance may be expectations that job growth will accelerate next year, which will spur even greater household growth, imply that the supply balance may be corrected even sooner. Construction will also accelerate, but not as quickly as household growth.corrected even sooner. Construction will also accelerate, but not as quickly as household growth.corrected even sooner. Construction will also accelerate, but not as quickly as household growth.



Multifamily construction will ramp up more quickly than singleMultifamily construction will ramp up more quickly than singleMultifamily construction will ramp up more quickly than single‐‐‐family, although both will rise. Many of the new households that form will family, although both will rise. Many of the new households that form will family, although both will rise. Many of the new households that form will lack the credit history or savings to purchase a home, thus driving the demand for rental units. Further, during the earlier part of the decade, lack the credit history or savings to purchase a home, thus driving the demand for rental units. Further, during the earlier part of the decade, lack the credit history or savings to purchase a home, thus driving the demand for rental units. Further, during the earlier part of the decade, construction excesses were far more endemic in the singleconstruction excesses were far more endemic in the singleconstruction excesses were far more endemic in the single‐‐‐family market than the multifamily market. Notwithstanding an increase in the family market than the multifamily market. Notwithstanding an increase in the family market than the multifamily market. Notwithstanding an increase in the third quarter, the rental vacancy rate has been trending down since it peaked in midthird quarter, the rental vacancy rate has been trending down since it peaked in midthird quarter, the rental vacancy rate has been trending down since it peaked in mid‐‐‐2009.2009.2009.

Outlook

Home sales will be flat this year compared with last year, before picking up in 2012. Disposition of distressed homes will account for an Home sales will be flat this year compared with last year, before picking up in 2012. Disposition of distressed homes will account for an Home sales will be flat this year compared with last year, before picking up in 2012. Disposition of distressed homes will account for an increasing share of sales. Homebuilding is rising this year, but very slowly. By yearincreasing share of sales. Homebuilding is rising this year, but very slowly. By yearincreasing share of sales. Homebuilding is rising this year, but very slowly. By year’’’s end, news end, news end, new‐‐‐ and existingand existingand existing‐‐‐home sales will reach a 5.4 million home sales will reach a 5.4 million home sales will reach a 5.4 million annualized pace, and starts will hit 650,000. House prices will be one of the last metrics to hit bottom. Prices are balanced with respect to annualized pace, and starts will hit 650,000. House prices will be one of the last metrics to hit bottom. Prices are balanced with respect to annualized pace, and starts will hit 650,000. House prices will be one of the last metrics to hit bottom. Prices are balanced with respect to fundamental drivers, thus distress sales will cause the remaining modest 3% decline; the national price will bottom out in the first half of fundamental drivers, thus distress sales will cause the remaining modest 3% decline; the national price will bottom out in the first half of fundamental drivers, thus distress sales will cause the remaining modest 3% decline; the national price will bottom out in the first half of 2012.2012.2012.

The risk of recession is retreating but remains the main downside threat to housing. Recession would result in a greater number of The risk of recession is retreating but remains the main downside threat to housing. Recession would result in a greater number of The risk of recession is retreating but remains the main downside threat to housing. Recession would result in a greater number of foreclosures and fewer sales and would send housing back down. Additionally, a recession would halt the emerging recovery in multifamily foreclosures and fewer sales and would send housing back down. Additionally, a recession would halt the emerging recovery in multifamily foreclosures and fewer sales and would send housing back down. Additionally, a recession would halt the emerging recovery in multifamily housing.housing.housing.

Many uncertainties also remain about the timing of foreclosures that could easily delay the end of the price correction.Many uncertainties also remain about the timing of foreclosures that could easily delay the end of the price correction.Many uncertainties also remain about the timing of foreclosures that could easily delay the end of the price correction.

A significant downside risk over the next two years centers on the building industryA significant downside risk over the next two years centers on the building industryA significant downside risk over the next two years centers on the building industry’’’s capacity, which has contracted considerably since the s capacity, which has contracted considerably since the s capacity, which has contracted considerably since the top of the housing boom. The construction outlook may be overly optimistic because homebuilders may not be able to increase production top of the housing boom. The construction outlook may be overly optimistic because homebuilders may not be able to increase production top of the housing boom. The construction outlook may be overly optimistic because homebuilders may not be able to increase production quickly.quickly.quickly.



SingleSingle‐‐Family IndicatorsFamily Indicators By Sunayana MehraBy Sunayana Mehra NOVEMBER 14, 2011NOVEMBER 14, 2011

Housing supply and price fundamentals are rebalancing, lowering the LHPI. Housing supply and price fundamentals are rebalancing, lowering the LHPI. Housing supply and price fundamentals are rebalancing, lowering the LHPI.

The house price balance is worsening, with average prices falling further below their equilibrium levels. The house price balance is worsening, with average prices falling further below their equilibrium levels. The house price balance is worsening, with average prices falling further below their equilibrium levels.

Incorporating a measure of foreclosure severity in the LHPI model raises the probability of continued price declines. Incorporating a measure of foreclosure severity in the LHPI model raises the probability of continued price declines. Incorporating a measure of foreclosure severity in the LHPI model raises the probability of continued price declines.

The LHPI suggests that house price declines will persist into the second quarter of 2012. The LHPI suggests that house price declines will persist into the second quarter of 2012. The LHPI suggests that house price declines will persist into the second quarter of 2012.

Uncertainty owing to the European sovereign debt crisis and political wrangling over the budget deficit weighed on job growth and Uncertainty owing to the European sovereign debt crisis and political wrangling over the budget deficit weighed on job growth and Uncertainty owing to the European sovereign debt crisis and political wrangling over the budget deficit weighed on job growth and consumer confidence this summer. As a result, the housing market recovery remains weak. Construction of new homes is low and demand consumer confidence this summer. As a result, the housing market recovery remains weak. Construction of new homes is low and demand consumer confidence this summer. As a result, the housing market recovery remains weak. Construction of new homes is low and demand for homes remains very soft. All major measures of house prices are down on a yearfor homes remains very soft. All major measures of house prices are down on a yearfor homes remains very soft. All major measures of house prices are down on a year‐‐‐ago basis. The possibility that the economy will reago basis. The possibility that the economy will reago basis. The possibility that the economy will re‐‐‐enter recession poses the main downside threat to housing. Recession would result in a greater number of foreclosures and fewer sales and enter recession poses the main downside threat to housing. Recession would result in a greater number of foreclosures and fewer sales and enter recession poses the main downside threat to housing. Recession would result in a greater number of foreclosures and fewer sales and would send housing back down.would send housing back down.would send housing back down.

The Moody's Analytics proprietary singleThe Moody's Analytics proprietary singleThe Moody's Analytics proprietary single‐‐‐family housing indices reflect markets that are regaining their balance relative to underlying family housing indices reflect markets that are regaining their balance relative to underlying family housing indices reflect markets that are regaining their balance relative to underlying demand and supply fundamentals but yet remain at risk of a house price decline one year from now. The deep housing correction has pushed demand and supply fundamentals but yet remain at risk of a house price decline one year from now. The deep housing correction has pushed demand and supply fundamentals but yet remain at risk of a house price decline one year from now. The deep housing correction has pushed prices far below their equilibrium relative to income and population growth in many large metro areas while the dearth of new construction prices far below their equilibrium relative to income and population growth in many large metro areas while the dearth of new construction prices far below their equilibrium relative to income and population growth in many large metro areas while the dearth of new construction is keeping incremental increases in demand for housing running ahead of new supply. Nonetheless, as the LHPI model indicates, the risk of is keeping incremental increases in demand for housing running ahead of new supply. Nonetheless, as the LHPI model indicates, the risk of is keeping incremental increases in demand for housing running ahead of new supply. Nonetheless, as the LHPI model indicates, the risk of house price declines one year from now, while easing slightly, remains well above the historical norm. Inclusion of a measure of foreclosure house price declines one year from now, while easing slightly, remains well above the historical norm. Inclusion of a measure of foreclosure house price declines one year from now, while easing slightly, remains well above the historical norm. Inclusion of a measure of foreclosure severity in the LHPI model is causing it to remain highly elevated.severity in the LHPI model is causing it to remain highly elevated.severity in the LHPI model is causing it to remain highly elevated.

Even in the face of weak household growth, the housing marketEven in the face of weak household growth, the housing marketEven in the face of weak household growth, the housing market’’’s supplys supplys supply‐‐‐demand imbalances are being redressed, a positive in a market that demand imbalances are being redressed, a positive in a market that demand imbalances are being redressed, a positive in a market that is plagued by an oversupply of housing. The extraordinarily weak pace of homebuilding has pushed our longis plagued by an oversupply of housing. The extraordinarily weak pace of homebuilding has pushed our longis plagued by an oversupply of housing. The extraordinarily weak pace of homebuilding has pushed our long‐‐‐term housing supplyterm housing supplyterm housing supply‐‐‐demand demand demand balance measure down to its lowest reading since midbalance measure down to its lowest reading since midbalance measure down to its lowest reading since mid‐‐‐1994, indicating that, despite being dragged down by uncertainty, demand is 1994, indicating that, despite being dragged down by uncertainty, demand is 1994, indicating that, despite being dragged down by uncertainty, demand is outstripping supply. The momentum toward the buildup of demand will help restore balance between the supply of homes and the demand outstripping supply. The momentum toward the buildup of demand will help restore balance between the supply of homes and the demand outstripping supply. The momentum toward the buildup of demand will help restore balance between the supply of homes and the demand for homes. Given the weak job market and large number of distressed properties that are likely to come on the market over the next six to for homes. Given the weak job market and large number of distressed properties that are likely to come on the market over the next six to for homes. Given the weak job market and large number of distressed properties that are likely to come on the market over the next six to eight months, it will be the second half of 2012 before the supplyeight months, it will be the second half of 2012 before the supplyeight months, it will be the second half of 2012 before the supply‐‐‐demand balance is fully restored. Continued gains in household formation demand balance is fully restored. Continued gains in household formation demand balance is fully restored. Continued gains in household formation will gather pace as the recovery gains traction, and homebuilding will remain modest.will gather pace as the recovery gains traction, and homebuilding will remain modest.will gather pace as the recovery gains traction, and homebuilding will remain modest.

After picking up following the two homebuyer tax credit rebate schemes, housing starts had fallen off and are now bouncing along the After picking up following the two homebuyer tax credit rebate schemes, housing starts had fallen off and are now bouncing along the After picking up following the two homebuyer tax credit rebate schemes, housing starts had fallen off and are now bouncing along the bottom. In the third quarter of 2011, builders started construction on only an annualized 424,000 singlebottom. In the third quarter of 2011, builders started construction on only an annualized 424,000 singlebottom. In the third quarter of 2011, builders started construction on only an annualized 424,000 single‐‐‐family homes, which is slightly family homes, which is slightly family homes, which is slightly higher than the all time low in the first quarter of 2009. Concurrently, demand for homes is rising, with new households forming at an higher than the all time low in the first quarter of 2009. Concurrently, demand for homes is rising, with new households forming at an higher than the all time low in the first quarter of 2009. Concurrently, demand for homes is rising, with new households forming at an expected pace of more than 1.18 million this year, compared with 1 million last year. This pace is closing in on trend growth.expected pace of more than 1.18 million this year, compared with 1 million last year. This pace is closing in on trend growth.expected pace of more than 1.18 million this year, compared with 1 million last year. This pace is closing in on trend growth.

Recent mortgage moratoriums related to faulty documentation have extended the time it takes for a foreclosed home to make it to the Recent mortgage moratoriums related to faulty documentation have extended the time it takes for a foreclosed home to make it to the Recent mortgage moratoriums related to faulty documentation have extended the time it takes for a foreclosed home to make it to the market for sale by keeping many homes in the foreclosure pipeline; this will add to the excess stock in the coming quarters. According to market for sale by keeping many homes in the foreclosure pipeline; this will add to the excess stock in the coming quarters. According to market for sale by keeping many homes in the foreclosure pipeline; this will add to the excess stock in the coming quarters. According to data from the credit bureau Equifax, about 4 million mortgage borrowers were 90 days or more delinquent or in the foreclosure process at data from the credit bureau Equifax, about 4 million mortgage borrowers were 90 days or more delinquent or in the foreclosure process at data from the credit bureau Equifax, about 4 million mortgage borrowers were 90 days or more delinquent or in the foreclosure process at the end of second quarter. Many of these distressed homeowners will add to the vacant stock when they fail to cure their delinquent loansthe end of second quarter. Many of these distressed homeowners will add to the vacant stock when they fail to cure their delinquent loansthe end of second quarter. Many of these distressed homeowners will add to the vacant stock when they fail to cure their delinquent loans

Nonetheless, the momentum toward the buildup of demand will help correct the imbalances generated by the housing boom between the Nonetheless, the momentum toward the buildup of demand will help correct the imbalances generated by the housing boom between the Nonetheless, the momentum toward the buildup of demand will help correct the imbalances generated by the housing boom between the large stock of homes (new and existing) and the number of households needing homes. Although the stock of excess housing units remains large stock of homes (new and existing) and the number of households needing homes. Although the stock of excess housing units remains large stock of homes (new and existing) and the number of households needing homes. Although the stock of excess housing units remains large at an estimated 1.3 million units, the excess demand buildup will help eliminate much of this excess over the next year to year and a large at an estimated 1.3 million units, the excess demand buildup will help eliminate much of this excess over the next year to year and a large at an estimated 1.3 million units, the excess demand buildup will help eliminate much of this excess over the next year to year and a half.half.half.



There is quite a regional variation in supply conditions, with only a few markets where the months of excess supply are exceptionally high. There is quite a regional variation in supply conditions, with only a few markets where the months of excess supply are exceptionally high. There is quite a regional variation in supply conditions, with only a few markets where the months of excess supply are exceptionally high. Only 13 of the metro area markets, or 3.3%, have an excess supply reading that is five months or greater, a tiny improvement from the first Only 13 of the metro area markets, or 3.3%, have an excess supply reading that is five months or greater, a tiny improvement from the first Only 13 of the metro area markets, or 3.3%, have an excess supply reading that is five months or greater, a tiny improvement from the first quarter, when 4% of metro areas fell into this category. New construction remains very weak, exacerbating the supply shortage. As a result, quarter, when 4% of metro areas fell into this category. New construction remains very weak, exacerbating the supply shortage. As a result, quarter, when 4% of metro areas fell into this category. New construction remains very weak, exacerbating the supply shortage. As a result, despite being weak, demand is substantially outstripping supply in about 38% of the metro areas, noticeably higher than last quarter. The despite being weak, demand is substantially outstripping supply in about 38% of the metro areas, noticeably higher than last quarter. The despite being weak, demand is substantially outstripping supply in about 38% of the metro areas, noticeably higher than last quarter. The supply balance indicator table shows the excess supply index by metro area. The regions where months of excess supply are the highest supply balance indicator table shows the excess supply index by metro area. The regions where months of excess supply are the highest supply balance indicator table shows the excess supply index by metro area. The regions where months of excess supply are the highest include metro areas in the industrial Midwest, especially in Michigan, where household growth is flat or contracting and other metro areas include metro areas in the industrial Midwest, especially in Michigan, where household growth is flat or contracting and other metro areas include metro areas in the industrial Midwest, especially in Michigan, where household growth is flat or contracting and other metro areas where the decline in household growth is outpacing the decline in new residential construction. On the other hand, demand is building up where the decline in household growth is outpacing the decline in new residential construction. On the other hand, demand is building up where the decline in household growth is outpacing the decline in new residential construction. On the other hand, demand is building up faster than supply in a number Californian and East Coast metro areas, particularly the San Francisco Bay area, Los Angeles, Ocean City NJ, faster than supply in a number Californian and East Coast metro areas, particularly the San Francisco Bay area, Los Angeles, Ocean City NJ, faster than supply in a number Californian and East Coast metro areas, particularly the San Francisco Bay area, Los Angeles, Ocean City NJ, and Peabody MA. Miami is also showing signs of strengthening demand.and Peabody MA. Miami is also showing signs of strengthening demand.and Peabody MA. Miami is also showing signs of strengthening demand.

The housing market correction has also sent house prices well below their equilibrium in a number of metro areas. Collectively, these The housing market correction has also sent house prices well below their equilibrium in a number of metro areas. Collectively, these The housing market correction has also sent house prices well below their equilibrium in a number of metro areas. Collectively, these imbalances have sent the average house price balance indicator well into undervalued territory, another force that is lowering the LHPI. The imbalances have sent the average house price balance indicator well into undervalued territory, another force that is lowering the LHPI. The imbalances have sent the average house price balance indicator well into undervalued territory, another force that is lowering the LHPI. The large house price declines to date have driven prices below what can be supported by their underlying economic and demographic drivers in large house price declines to date have driven prices below what can be supported by their underlying economic and demographic drivers in large house price declines to date have driven prices below what can be supported by their underlying economic and demographic drivers in many metro areas. As typically occurs in response to a housing bubble, the bust has overcompensated.many metro areas. As typically occurs in response to a housing bubble, the bust has overcompensated.many metro areas. As typically occurs in response to a housing bubble, the bust has overcompensated.

The large correction has caused house prices in metro areas such as San Francisco, Detroit, Seattle and Oakland to fall significantly below The large correction has caused house prices in metro areas such as San Francisco, Detroit, Seattle and Oakland to fall significantly below The large correction has caused house prices in metro areas such as San Francisco, Detroit, Seattle and Oakland to fall significantly below their equilibrium. The large house price declines to date have driven prices below what can be supported by their underlying economic and their equilibrium. The large house price declines to date have driven prices below what can be supported by their underlying economic and their equilibrium. The large house price declines to date have driven prices below what can be supported by their underlying economic and demographic drivers in many metro areas. A large inventory of foreclosures is the reason behind this overshooting. According to data from demographic drivers in many metro areas. A large inventory of foreclosures is the reason behind this overshooting. According to data from demographic drivers in many metro areas. A large inventory of foreclosures is the reason behind this overshooting. According to data from Corelogic, distressed homes sold for an approximate discount of 9% at the end of the second quarter.Corelogic, distressed homes sold for an approximate discount of 9% at the end of the second quarter.Corelogic, distressed homes sold for an approximate discount of 9% at the end of the second quarter.

In areas such as Austin TX, Asheville NC and Chattanooga TN, house prices have been more stable, but a very modest price correction, In areas such as Austin TX, Asheville NC and Chattanooga TN, house prices have been more stable, but a very modest price correction, In areas such as Austin TX, Asheville NC and Chattanooga TN, house prices have been more stable, but a very modest price correction, combined with income and population growth that weakened because of the recent recession, has left these markets slightly overpriced. combined with income and population growth that weakened because of the recent recession, has left these markets slightly overpriced. combined with income and population growth that weakened because of the recent recession, has left these markets slightly overpriced. Even so, in general, the degree of overvaluation is not as severe as that observed in the bubble metro areas during the peak of the housing Even so, in general, the degree of overvaluation is not as severe as that observed in the bubble metro areas during the peak of the housing Even so, in general, the degree of overvaluation is not as severe as that observed in the bubble metro areas during the peak of the housing boom. See the house price balance indicator table for data by metro area.boom. See the house price balance indicator table for data by metro area.boom. See the house price balance indicator table for data by metro area.



When averaged over all 384 metro area markets, the degree of overpricing has been trending down since midWhen averaged over all 384 metro area markets, the degree of overpricing has been trending down since midWhen averaged over all 384 metro area markets, the degree of overpricing has been trending down since mid‐‐‐2006, when house prices 2006, when house prices 2006, when house prices began declining. With the recent double dip, average house prices are 13% below equilibrium, compared with a historic average of 1.3% began declining. With the recent double dip, average house prices are 13% below equilibrium, compared with a historic average of 1.3% began declining. With the recent double dip, average house prices are 13% below equilibrium, compared with a historic average of 1.3% below equilibrium. The magnitude of underpricing has increased since the last quarter of 2010. As a result, the number of overpriced metro below equilibrium. The magnitude of underpricing has increased since the last quarter of 2010. As a result, the number of overpriced metro below equilibrium. The magnitude of underpricing has increased since the last quarter of 2010. As a result, the number of overpriced metro areas is lower than in the fourth quarter. Only 16,or 4%, of the metro areas in the nation are considered to be highly overpriced or areas is lower than in the fourth quarter. Only 16,or 4%, of the metro areas in the nation are considered to be highly overpriced or areas is lower than in the fourth quarter. Only 16,or 4%, of the metro areas in the nation are considered to be highly overpriced or overpriced markets.overpriced markets.overpriced markets.

To use the information provided by the excess supply indicator and overvaluation measure in a predictive capacity, the MoodyTo use the information provided by the excess supply indicator and overvaluation measure in a predictive capacity, the MoodyTo use the information provided by the excess supply indicator and overvaluation measure in a predictive capacity, the Moody’’’s Analytics s Analytics s Analytics LHPI calculates the probability of a decline in house prices one year from now based on a regression model that is driven by these indicators. LHPI calculates the probability of a decline in house prices one year from now based on a regression model that is driven by these indicators. LHPI calculates the probability of a decline in house prices one year from now based on a regression model that is driven by these indicators. In addition, the LHPI model incorporates other economic drivers relevant to house price performance such as housing affordability, In addition, the LHPI model incorporates other economic drivers relevant to house price performance such as housing affordability, In addition, the LHPI model incorporates other economic drivers relevant to house price performance such as housing affordability, employment growth in nonhousingemployment growth in nonhousingemployment growth in nonhousing‐‐‐related industries, and measures of volatility and persistence of house price declines. Further, data on related industries, and measures of volatility and persistence of house price declines. Further, data on related industries, and measures of volatility and persistence of house price declines. Further, data on REO inventory have also been included in the computation of the LHPI. Markets that are highly overpriced, that are highly oversupplied and REO inventory have also been included in the computation of the LHPI. Markets that are highly overpriced, that are highly oversupplied and REO inventory have also been included in the computation of the LHPI. Markets that are highly overpriced, that are highly oversupplied and unaffordable, or that have weak nonhousingunaffordable, or that have weak nonhousingunaffordable, or that have weak nonhousing‐‐‐related employment are at higher risk of a price decline in four quarters. In addition, all else related employment are at higher risk of a price decline in four quarters. In addition, all else related employment are at higher risk of a price decline in four quarters. In addition, all else equal, markets that have a higher number of homes in REO inventory per thousand households are also at a higher risk of price declines one equal, markets that have a higher number of homes in REO inventory per thousand households are also at a higher risk of price declines one equal, markets that have a higher number of homes in REO inventory per thousand households are also at a higher risk of price declines one year from now, simply because distressed homes can sell for a large discount, creating additional downward pressure on local house prices.year from now, simply because distressed homes can sell for a large discount, creating additional downward pressure on local house prices.year from now, simply because distressed homes can sell for a large discount, creating additional downward pressure on local house prices.

The share of the U.S. ownerThe share of the U.S. ownerThe share of the U.S. owner‐‐‐occupied housing stock at risk of a price decline remains elevated by historical standards but has receded from occupied housing stock at risk of a price decline remains elevated by historical standards but has receded from occupied housing stock at risk of a price decline remains elevated by historical standards but has receded from its highest level. About 80% of the markets were considered to be at high risk or very high risk of experiencing a price decline. The its highest level. About 80% of the markets were considered to be at high risk or very high risk of experiencing a price decline. The its highest level. About 80% of the markets were considered to be at high risk or very high risk of experiencing a price decline. The percentage of the housing stock that remains at risk of a price decline is also 80%. By share of housing stock, the average risk of a house percentage of the housing stock that remains at risk of a price decline is also 80%. By share of housing stock, the average risk of a house percentage of the housing stock that remains at risk of a price decline is also 80%. By share of housing stock, the average risk of a house price decline in the nation is above normal. The fact that the share of atprice decline in the nation is above normal. The fact that the share of atprice decline in the nation is above normal. The fact that the share of at‐‐‐risk housing stock is elevated reflects that besides a high number of risk housing stock is elevated reflects that besides a high number of risk housing stock is elevated reflects that besides a high number of markets with an abovemarkets with an abovemarkets with an above‐‐‐average risk of price decline, there are a fairly large number of homes in each market that could see prices decline. average risk of price decline, there are a fairly large number of homes in each market that could see prices decline. average risk of price decline, there are a fairly large number of homes in each market that could see prices decline. One positive is that although the aggregate LHPI measures are very high, they are noticeably lower than the peak in the third quarter of last One positive is that although the aggregate LHPI measures are very high, they are noticeably lower than the peak in the third quarter of last One positive is that although the aggregate LHPI measures are very high, they are noticeably lower than the peak in the third quarter of last year.year.year.



The map shows the metro areas that the LHPI flags as being at risk of a house price decline based on data through the second quarter of The map shows the metro areas that the LHPI flags as being at risk of a house price decline based on data through the second quarter of The map shows the metro areas that the LHPI flags as being at risk of a house price decline based on data through the second quarter of 2011. A large number of markets are still characterized as at risk, and most of these can be classified as markets that were at the core of the 2011. A large number of markets are still characterized as at risk, and most of these can be classified as markets that were at the core of the 2011. A large number of markets are still characterized as at risk, and most of these can be classified as markets that were at the core of the housing boom and bust. Markets with a high and rising share of foreclosure inventory make up a disproportionately high share of athousing boom and bust. Markets with a high and rising share of foreclosure inventory make up a disproportionately high share of athousing boom and bust. Markets with a high and rising share of foreclosure inventory make up a disproportionately high share of at‐‐‐risk risk risk markets particularly in California, Florida, Nevada and Arizona. Rising housing affordability and little new construction are helping these markets particularly in California, Florida, Nevada and Arizona. Rising housing affordability and little new construction are helping these markets particularly in California, Florida, Nevada and Arizona. Rising housing affordability and little new construction are helping these states reduce their risk, but a huge foreclosure inventory overhang is driving the LHPI in the opposite direction. Some other areas that states reduce their risk, but a huge foreclosure inventory overhang is driving the LHPI in the opposite direction. Some other areas that states reduce their risk, but a huge foreclosure inventory overhang is driving the LHPI in the opposite direction. Some other areas that remain at high risk are those where price declines have thus been moderate relative to their runup during the boom (such as the East Coast). remain at high risk are those where price declines have thus been moderate relative to their runup during the boom (such as the East Coast). remain at high risk are those where price declines have thus been moderate relative to their runup during the boom (such as the East Coast). The LHPI table shows the values for the fourth quarter as well as the values for the inputs to the LHPI. The housing market risk ranking table The LHPI table shows the values for the fourth quarter as well as the values for the inputs to the LHPI. The housing market risk ranking table The LHPI table shows the values for the fourth quarter as well as the values for the inputs to the LHPI. The housing market risk ranking table displays the Housing Monitor results by metro area.displays the Housing Monitor results by metro area.displays the Housing Monitor results by metro area.

Six of the 10 metro areas at very high risk of a price decline lie in the Mountain region or the West, where foreclosure inventories are among Six of the 10 metro areas at very high risk of a price decline lie in the Mountain region or the West, where foreclosure inventories are among Six of the 10 metro areas at very high risk of a price decline lie in the Mountain region or the West, where foreclosure inventories are among the highest in the country. The South and Central Plains contain seven of the 10 metro areas at lowest risk of a price decline. The economies the highest in the country. The South and Central Plains contain seven of the 10 metro areas at lowest risk of a price decline. The economies the highest in the country. The South and Central Plains contain seven of the 10 metro areas at lowest risk of a price decline. The economies in the Central Plains typically experienced a mild recession and benefit from a rebound in agricultural and commodityin the Central Plains typically experienced a mild recession and benefit from a rebound in agricultural and commodityin the Central Plains typically experienced a mild recession and benefit from a rebound in agricultural and commodity‐‐‐related industries as related industries as related industries as well as machinery manufacturing. Overall, this has contributed to quicker improvement in fundamental drivers of house prices than in other well as machinery manufacturing. Overall, this has contributed to quicker improvement in fundamental drivers of house prices than in other well as machinery manufacturing. Overall, this has contributed to quicker improvement in fundamental drivers of house prices than in other regions of the country.regions of the country.regions of the country.

Distress sales govern the nearDistress sales govern the nearDistress sales govern the near‐‐‐term outlook for house prices; a rising share of distress sales will result in a decline in house prices. In the term outlook for house prices; a rising share of distress sales will result in a decline in house prices. In the term outlook for house prices; a rising share of distress sales will result in a decline in house prices. In the second quarter, the NAR reported a decline in the share of distress sales from 39% to 33%. This share will rise once the stalled foreclosure second quarter, the NAR reported a decline in the share of distress sales from 39% to 33%. This share will rise once the stalled foreclosure second quarter, the NAR reported a decline in the share of distress sales from 39% to 33%. This share will rise once the stalled foreclosure processing machine starts up again, driving house prices back down. Expectations that house prices will fall in coming quarters rely heavily on processing machine starts up again, driving house prices back down. Expectations that house prices will fall in coming quarters rely heavily on processing machine starts up again, driving house prices back down. Expectations that house prices will fall in coming quarters rely heavily on the assumption that the foreclosure process will accelerate soon.the assumption that the foreclosure process will accelerate soon.the assumption that the foreclosure process will accelerate soon.

Foreclosure filings are starting to pick up as loan servicers wrap up the extensive loan reviews that were required to address roboForeclosure filings are starting to pick up as loan servicers wrap up the extensive loan reviews that were required to address roboForeclosure filings are starting to pick up as loan servicers wrap up the extensive loan reviews that were required to address robo‐‐‐signing signing signing issues that surfaced late last year. Despite some evidence of resolution, uncertainties still surround the industryissues that surfaced late last year. Despite some evidence of resolution, uncertainties still surround the industryissues that surfaced late last year. Despite some evidence of resolution, uncertainties still surround the industry’’’s practices and could result in s practices and could result in s practices and could result in further delays in foreclosures, which would support house prices in the interim but only lengthen the time it takes for the housing market to further delays in foreclosures, which would support house prices in the interim but only lengthen the time it takes for the housing market to further delays in foreclosures, which would support house prices in the interim but only lengthen the time it takes for the housing market to clear and prices to return to equilibrium.clear and prices to return to equilibrium.clear and prices to return to equilibrium.



Mortgage MarketMortgage Market By Cristian deRitisBy Cristian deRitis NOVEMBER 16, 2011NOVEMBER 16, 2011

EarlyEarlyEarly‐‐‐stage delinquency rates rose during the period while latestage delinquency rates rose during the period while latestage delinquency rates rose during the period while late‐‐‐stage delinquency rates fell; however, there is substantial regional stage delinquency rates fell; however, there is substantial regional stage delinquency rates fell; however, there is substantial regional variation variation variation

Mortgage applications rose over the last three months as mortgage interest rates fell. Mortgage applications rose over the last three months as mortgage interest rates fell. Mortgage applications rose over the last three months as mortgage interest rates fell.

Overall first mortgage origination volumes remained elevated in recent quarters primarily because of increased refinancing despite Overall first mortgage origination volumes remained elevated in recent quarters primarily because of increased refinancing despite Overall first mortgage origination volumes remained elevated in recent quarters primarily because of increased refinancing despite tight underwriting standards. tight underwriting standards. tight underwriting standards.

The expanded HARP program could help provide some stability to the housing market by lowering mortgage payments and The expanded HARP program could help provide some stability to the housing market by lowering mortgage payments and The expanded HARP program could help provide some stability to the housing market by lowering mortgage payments and preventing some foreclosures preventing some foreclosures preventing some foreclosures

Credit conditions in the U.S. residential mortgage market were mixed over the past three months as prices firmed in some local housing Credit conditions in the U.S. residential mortgage market were mixed over the past three months as prices firmed in some local housing Credit conditions in the U.S. residential mortgage market were mixed over the past three months as prices firmed in some local housing markets while persistently weak labor markets weighed on performance. In a reversal of recent trends, earlymarkets while persistently weak labor markets weighed on performance. In a reversal of recent trends, earlymarkets while persistently weak labor markets weighed on performance. In a reversal of recent trends, early‐‐‐stage delinquency rates rose stage delinquency rates rose stage delinquency rates rose during the period while lateduring the period while lateduring the period while late‐‐‐stage delinquency rates fell as reported by the credit bureau Equifax. The overall dollar delinquency rate on stage delinquency rates fell as reported by the credit bureau Equifax. The overall dollar delinquency rate on stage delinquency rates fell as reported by the credit bureau Equifax. The overall dollar delinquency rate on mortgage debt outstanding rose to 6.65%, an increase of 6 basis points over the last three months. Default rates (including bankruptcies) fell mortgage debt outstanding rose to 6.65%, an increase of 6 basis points over the last three months. Default rates (including bankruptcies) fell mortgage debt outstanding rose to 6.65%, an increase of 6 basis points over the last three months. Default rates (including bankruptcies) fell by 6 basis points even as loan servicers stepped up their efforts to pull distressed borrowers through the foreclosure process. Although by 6 basis points even as loan servicers stepped up their efforts to pull distressed borrowers through the foreclosure process. Although by 6 basis points even as loan servicers stepped up their efforts to pull distressed borrowers through the foreclosure process. Although investor interest in purchasing real estateinvestor interest in purchasing real estateinvestor interest in purchasing real estate‐‐‐owned properties has grown in some parts of the country, flows into REO inventory continued at owned properties has grown in some parts of the country, flows into REO inventory continued at owned properties has grown in some parts of the country, flows into REO inventory continued at a robust pace. Loan originations for the purchase of new or existing homes remains depressed, resulting in lower outstanding balances a robust pace. Loan originations for the purchase of new or existing homes remains depressed, resulting in lower outstanding balances a robust pace. Loan originations for the purchase of new or existing homes remains depressed, resulting in lower outstanding balances relative to a year ago. As an indication of the unrelenting contraction of the mortgage market, the amount of mortgage debt outstanding relative to a year ago. As an indication of the unrelenting contraction of the mortgage market, the amount of mortgage debt outstanding relative to a year ago. As an indication of the unrelenting contraction of the mortgage market, the amount of mortgage debt outstanding has retreated back to November 2006 levels. Proposed changes to the governmenthas retreated back to November 2006 levels. Proposed changes to the governmenthas retreated back to November 2006 levels. Proposed changes to the government’’’s Home Affordable Refinancing Program at the of s Home Affordable Refinancing Program at the of s Home Affordable Refinancing Program at the of October will lead to some increased refinancing in the near term but is likely to have a minimal impact on performance.October will lead to some increased refinancing in the near term but is likely to have a minimal impact on performance.October will lead to some increased refinancing in the near term but is likely to have a minimal impact on performance.



While the overall delinquency rate on first mortgage loans has increased, there is substantial regional variation due to differences in house While the overall delinquency rate on first mortgage loans has increased, there is substantial regional variation due to differences in house While the overall delinquency rate on first mortgage loans has increased, there is substantial regional variation due to differences in house price declines and unemployment rates across census areas. Delinquency rates for loans that were 120 days or more past due declined over price declines and unemployment rates across census areas. Delinquency rates for loans that were 120 days or more past due declined over price declines and unemployment rates across census areas. Delinquency rates for loans that were 120 days or more past due declined over the last three months, as they did throughout 2010 and the first half of 2011. Loan defaults (including bankruptcies) fell in September as the last three months, as they did throughout 2010 and the first half of 2011. Loan defaults (including bankruptcies) fell in September as the last three months, as they did throughout 2010 and the first half of 2011. Loan defaults (including bankruptcies) fell in September as reported by Equifax, though volatility in the series suggests that the broader trend of elevated defaults is persisting. In September, 1 million reported by Equifax, though volatility in the series suggests that the broader trend of elevated defaults is persisting. In September, 1 million reported by Equifax, though volatility in the series suggests that the broader trend of elevated defaults is persisting. In September, 1 million first mortgage loans failed at an annualized rate. Putting this figure into context, 1.4 million first mortgages defaulted for all of 2010, up from first mortgage loans failed at an annualized rate. Putting this figure into context, 1.4 million first mortgages defaulted for all of 2010, up from first mortgage loans failed at an annualized rate. Putting this figure into context, 1.4 million first mortgages defaulted for all of 2010, up from 1.2 million for 2009, 937,000 in 2008, a little more than half a million in 2007, and 307,000 in 2006.1.2 million for 2009, 937,000 in 2008, a little more than half a million in 2007, and 307,000 in 2006.1.2 million for 2009, 937,000 in 2008, a little more than half a million in 2007, and 307,000 in 2006.

The national first mortgage default rate (including bankruptcies) is elevated at 0.21% of dollar balances, with the highest default rates in The national first mortgage default rate (including bankruptcies) is elevated at 0.21% of dollar balances, with the highest default rates in The national first mortgage default rate (including bankruptcies) is elevated at 0.21% of dollar balances, with the highest default rates in states that experienced the most new construction and price appreciation during the housing boom. Nevada led the nation with a monthly states that experienced the most new construction and price appreciation during the housing boom. Nevada led the nation with a monthly states that experienced the most new construction and price appreciation during the housing boom. Nevada led the nation with a monthly default rate of 0.7% of outstanding balancesdefault rate of 0.7% of outstanding balancesdefault rate of 0.7% of outstanding balances———a decrease of 26 basis points since June. Arizona followed with a default rate of 0.49%, a 26a decrease of 26 basis points since June. Arizona followed with a default rate of 0.49%, a 26a decrease of 26 basis points since June. Arizona followed with a default rate of 0.49%, a 26‐‐‐basis point decrease from June. Florida and California had similar default rates of 0.33% and 0.37%, respectively, a drop of 10 basis points basis point decrease from June. Florida and California had similar default rates of 0.33% and 0.37%, respectively, a drop of 10 basis points basis point decrease from June. Florida and California had similar default rates of 0.33% and 0.37%, respectively, a drop of 10 basis points since June for both states. Default rates remained elevated in Idaho, Oregon and Utah, where the housing market is stagnant. Georgia since June for both states. Default rates remained elevated in Idaho, Oregon and Utah, where the housing market is stagnant. Georgia since June for both states. Default rates remained elevated in Idaho, Oregon and Utah, where the housing market is stagnant. Georgia continued to struggle, with a default rates of 0.24%. Vermont and the District of Columbia had the lowest default rates in the nation at just continued to struggle, with a default rates of 0.24%. Vermont and the District of Columbia had the lowest default rates in the nation at just continued to struggle, with a default rates of 0.24%. Vermont and the District of Columbia had the lowest default rates in the nation at just 0.04% and 0.05% of outstanding balances.0.04% and 0.05% of outstanding balances.0.04% and 0.05% of outstanding balances.



Mortgage applications rose 29% over the last three months as mortgage interest rates fell, according to the Mortgage Bankers Association. Mortgage applications rose 29% over the last three months as mortgage interest rates fell, according to the Mortgage Bankers Association. Mortgage applications rose 29% over the last three months as mortgage interest rates fell, according to the Mortgage Bankers Association. Although the Freddie Mac 30Although the Freddie Mac 30Although the Freddie Mac 30‐‐‐year primary mortgage market survey rate reached a new historic low of 4.1%, many of the borrowers who year primary mortgage market survey rate reached a new historic low of 4.1%, many of the borrowers who year primary mortgage market survey rate reached a new historic low of 4.1%, many of the borrowers who could benefit financially from refinancing have either already done so recently or are unable to do so because of a deterioration in their could benefit financially from refinancing have either already done so recently or are unable to do so because of a deterioration in their could benefit financially from refinancing have either already done so recently or are unable to do so because of a deterioration in their incomes or credit scores. The administration proposed some changes to the governmentincomes or credit scores. The administration proposed some changes to the governmentincomes or credit scores. The administration proposed some changes to the government’’’s Home Affordable Refinancing Program in late s Home Affordable Refinancing Program in late s Home Affordable Refinancing Program in late October, including the removal of an eligibility cap on loanOctober, including the removal of an eligibility cap on loanOctober, including the removal of an eligibility cap on loan‐‐‐tototo‐‐‐value ratios. This will lead to some increased refinancing over the next few value ratios. This will lead to some increased refinancing over the next few value ratios. This will lead to some increased refinancing over the next few quarters from borrowers who were previously excluded from the program.quarters from borrowers who were previously excluded from the program.quarters from borrowers who were previously excluded from the program.

Privately funded mortgage financing is available only for the highestPrivately funded mortgage financing is available only for the highestPrivately funded mortgage financing is available only for the highest‐‐‐credit, highcredit, highcredit, high‐‐‐income borrowers with loan balances that exceed the income borrowers with loan balances that exceed the income borrowers with loan balances that exceed the conforming loan limit. Lending standards are likely to loosen over the next year or two as private lenders look to expand their market share, conforming loan limit. Lending standards are likely to loosen over the next year or two as private lenders look to expand their market share, conforming loan limit. Lending standards are likely to loosen over the next year or two as private lenders look to expand their market share, but the process will be slow and will depend largely on the future structure of the housing finance system to be determined by Congress. A but the process will be slow and will depend largely on the future structure of the housing finance system to be determined by Congress. A but the process will be slow and will depend largely on the future structure of the housing finance system to be determined by Congress. A lowering of the conforming loan limit at the end of September briefly tested the appetite across private lenders to provide mortgage lowering of the conforming loan limit at the end of September briefly tested the appetite across private lenders to provide mortgage lowering of the conforming loan limit at the end of September briefly tested the appetite across private lenders to provide mortgage financing. The experiment may be shortfinancing. The experiment may be shortfinancing. The experiment may be short‐‐‐lived, however, as the Senate voted to extend the higher conforming limit through the end of 2013 lived, however, as the Senate voted to extend the higher conforming limit through the end of 2013 lived, however, as the Senate voted to extend the higher conforming limit through the end of 2013 and the House may follow.and the House may follow.and the House may follow.

As a result of the rate activity, refinancing accounted for 78% of all mortgage applications during the last week of October. The number of As a result of the rate activity, refinancing accounted for 78% of all mortgage applications during the last week of October. The number of As a result of the rate activity, refinancing accounted for 78% of all mortgage applications during the last week of October. The number of loan applications rose 30% from three months ago and was just slightly below the peak reached in September, according to the Mortgage loan applications rose 30% from three months ago and was just slightly below the peak reached in September, according to the Mortgage loan applications rose 30% from three months ago and was just slightly below the peak reached in September, according to the Mortgage Bankers Association. Theoretically, a substantial number of borrowers could benefit financially from refinancing as they are carrying Bankers Association. Theoretically, a substantial number of borrowers could benefit financially from refinancing as they are carrying Bankers Association. Theoretically, a substantial number of borrowers could benefit financially from refinancing as they are carrying mortgage rates in excess of 5%. However, many are unable to do so as falling house prices have pushed their loanmortgage rates in excess of 5%. However, many are unable to do so as falling house prices have pushed their loanmortgage rates in excess of 5%. However, many are unable to do so as falling house prices have pushed their loan‐‐‐tototo‐‐‐value ratios up or as value ratios up or as value ratios up or as they have experienced a deterioration in their credit stemming from delinquencies on other credit accounts. Given expectations for further they have experienced a deterioration in their credit stemming from delinquencies on other credit accounts. Given expectations for further they have experienced a deterioration in their credit stemming from delinquencies on other credit accounts. Given expectations for further increases in mortgage rates over the next couple of years, refinancing will decline and purchases will occupy a larger share of loan origination increases in mortgage rates over the next couple of years, refinancing will decline and purchases will occupy a larger share of loan origination increases in mortgage rates over the next couple of years, refinancing will decline and purchases will occupy a larger share of loan origination volumes.volumes.volumes.

Growth in loan originations due to refinancing. Overall first mortgage origination volumes remained elevated in recent quarters Overall first mortgage origination volumes remained elevated in recent quarters Overall first mortgage origination volumes remained elevated in recent quarters



primarily because of increased refinancing despite tight underwriting standards. Borrowers with low credit scores continue to struggle to primarily because of increased refinancing despite tight underwriting standards. Borrowers with low credit scores continue to struggle to primarily because of increased refinancing despite tight underwriting standards. Borrowers with low credit scores continue to struggle to obtain mortgage credit, though borrowers with midobtain mortgage credit, though borrowers with midobtain mortgage credit, though borrowers with mid‐‐‐range scores are gradually gaining greater access (provided they are employed, can range scores are gradually gaining greater access (provided they are employed, can range scores are gradually gaining greater access (provided they are employed, can demonstrate a steady income, and can produce a down payment). Approximately 8% of new loan originations in the first quarter went to demonstrate a steady income, and can produce a down payment). Approximately 8% of new loan originations in the first quarter went to demonstrate a steady income, and can produce a down payment). Approximately 8% of new loan originations in the first quarter went to borrowers with credit scores below 620 as credit availability remains highly restricted by the FHA and the GSEs, which dominate the lending borrowers with credit scores below 620 as credit availability remains highly restricted by the FHA and the GSEs, which dominate the lending borrowers with credit scores below 620 as credit availability remains highly restricted by the FHA and the GSEs, which dominate the lending market.market.market.

Despite a persistently weak labor market and further declines in house prices, loans originated in the past three years are benefiting from the Despite a persistently weak labor market and further declines in house prices, loans originated in the past three years are benefiting from the Despite a persistently weak labor market and further declines in house prices, loans originated in the past three years are benefiting from the extremely tight underwriting that restricted credit to only the most qualified borrowers. Borrowers with newer loans are also carrying much extremely tight underwriting that restricted credit to only the most qualified borrowers. Borrowers with newer loans are also carrying much extremely tight underwriting that restricted credit to only the most qualified borrowers. Borrowers with newer loans are also carrying much lower interest rates than their predecessors, making monthly payments lower and easier to manage. Although affordability does not lower interest rates than their predecessors, making monthly payments lower and easier to manage. Although affordability does not lower interest rates than their predecessors, making monthly payments lower and easier to manage. Although affordability does not measure credit availability, the National Association of Realtors' affordability index keeps hitting new record highs because of the measure credit availability, the National Association of Realtors' affordability index keeps hitting new record highs because of the measure credit availability, the National Association of Realtors' affordability index keeps hitting new record highs because of the combination of falling house prices and low interest rates. Willing homebuyers with excellent credit, stable employment prospects, and the combination of falling house prices and low interest rates. Willing homebuyers with excellent credit, stable employment prospects, and the combination of falling house prices and low interest rates. Willing homebuyers with excellent credit, stable employment prospects, and the resources to make sizable down payments have ample opportunities to purchase affordable homes. Despite the relative bargains available, resources to make sizable down payments have ample opportunities to purchase affordable homes. Despite the relative bargains available, resources to make sizable down payments have ample opportunities to purchase affordable homes. Despite the relative bargains available, many potential buyers will wait on the sidelines until house prices stabilize fully and consumer confidence is restored.many potential buyers will wait on the sidelines until house prices stabilize fully and consumer confidence is restored.many potential buyers will wait on the sidelines until house prices stabilize fully and consumer confidence is restored.



Home equity loan losses drag on lender portfolios. Outstanding balances on HELOCs contracted at a 6.6% yearOutstanding balances on HELOCs contracted at a 6.6% yearOutstanding balances on HELOCs contracted at a 6.6% year‐‐‐overoverover‐‐‐year rate in year rate in year rate in September as borrowers deleveraged. The number of HELOC loans outstanding fell as lenders are exiting the home equity lending business September as borrowers deleveraged. The number of HELOC loans outstanding fell as lenders are exiting the home equity lending business September as borrowers deleveraged. The number of HELOC loans outstanding fell as lenders are exiting the home equity lending business and restricting new credit. Closedand restricting new credit. Closedand restricting new credit. Closed‐‐‐end home equity loans are 13.2% below their yearend home equity loans are 13.2% below their yearend home equity loans are 13.2% below their year‐‐‐ago levels, with extremely limited new loan ago levels, with extremely limited new loan ago levels, with extremely limited new loan production. Moodyproduction. Moodyproduction. Moody’’’s Analytics projects only modest growth in HELOC volume a few years out once the housing market stabilizes. As a s Analytics projects only modest growth in HELOC volume a few years out once the housing market stabilizes. As a s Analytics projects only modest growth in HELOC volume a few years out once the housing market stabilizes. As a result, consumers will increasingly turn to bankcards and other sources of credit to finance their spending.result, consumers will increasingly turn to bankcards and other sources of credit to finance their spending.result, consumers will increasingly turn to bankcards and other sources of credit to finance their spending.

The performance and outlook of second mortgages remains weak. Delinquency and default rates for home equity loans and lines of credit The performance and outlook of second mortgages remains weak. Delinquency and default rates for home equity loans and lines of credit The performance and outlook of second mortgages remains weak. Delinquency and default rates for home equity loans and lines of credit are high relative to first mortgages and historic trends. Many lenders are delaying writeare high relative to first mortgages and historic trends. Many lenders are delaying writeare high relative to first mortgages and historic trends. Many lenders are delaying write‐‐‐downs on second loans for as long as possible as downs on second loans for as long as possible as downs on second loans for as long as possible as they seek to preserve capital and, in some instances, hope for a turnaround in house prices. Delays in the foreclosure of first mortgages have they seek to preserve capital and, in some instances, hope for a turnaround in house prices. Delays in the foreclosure of first mortgages have they seek to preserve capital and, in some instances, hope for a turnaround in house prices. Delays in the foreclosure of first mortgages have also permitted some borrowers to keep their home equity lines open by paying the smaller amounts due on their home equity lines while also permitted some borrowers to keep their home equity lines open by paying the smaller amounts due on their home equity lines while also permitted some borrowers to keep their home equity lines open by paying the smaller amounts due on their home equity lines while forgoing the larger payment on their first mortgages. As more first mortgage are pushed through the foreclosure process, these trends will forgoing the larger payment on their first mortgages. As more first mortgage are pushed through the foreclosure process, these trends will forgoing the larger payment on their first mortgages. As more first mortgage are pushed through the foreclosure process, these trends will reverse, with more lenders forced to recognize the outstanding losses on their second lien portfolios.reverse, with more lenders forced to recognize the outstanding losses on their second lien portfolios.reverse, with more lenders forced to recognize the outstanding losses on their second lien portfolios.



Congress likely to extend higher conforming loan limits for the FHA. Higher conforming loan limits for loans guaranteed by Higher conforming loan limits for loans guaranteed by Higher conforming loan limits for loans guaranteed by Fannie Mae, Freddie Mac and the FHA expired at the end of September. Although the return to lower limits was viewed by some analysts as Fannie Mae, Freddie Mac and the FHA expired at the end of September. Although the return to lower limits was viewed by some analysts as Fannie Mae, Freddie Mac and the FHA expired at the end of September. Although the return to lower limits was viewed by some analysts as a litmus test for the ability of private mortgage lenders to provide financing, market participants, including the National Association of a litmus test for the ability of private mortgage lenders to provide financing, market participants, including the National Association of a litmus test for the ability of private mortgage lenders to provide financing, market participants, including the National Association of Realtors and the Mortgage Bankers Association, expressed fears that the economy in general and the housing market in particular were too Realtors and the Mortgage Bankers Association, expressed fears that the economy in general and the housing market in particular were too Realtors and the Mortgage Bankers Association, expressed fears that the economy in general and the housing market in particular were too fragile to handle the change.fragile to handle the change.fragile to handle the change.

The conforming loan limit that defines the maximum size of loans that are eligible for sale to the governmentThe conforming loan limit that defines the maximum size of loans that are eligible for sale to the governmentThe conforming loan limit that defines the maximum size of loans that are eligible for sale to the government‐‐‐sponsored enterprises Fannie sponsored enterprises Fannie sponsored enterprises Fannie Mae and Freddie Mac was raised to $729,750 with the 2008 economic stimulus package. This permitted a larger number of borrowers to Mae and Freddie Mac was raised to $729,750 with the 2008 economic stimulus package. This permitted a larger number of borrowers to Mae and Freddie Mac was raised to $729,750 with the 2008 economic stimulus package. This permitted a larger number of borrowers to either purchase or refinance their mortgages at the lower rates commanded by GSE loans. With the expiration of the temporary increase at either purchase or refinance their mortgages at the lower rates commanded by GSE loans. With the expiration of the temporary increase at either purchase or refinance their mortgages at the lower rates commanded by GSE loans. With the expiration of the temporary increase at the end of September, the limit returned to its previous level of $417,000 in most parts of the country. For designated the end of September, the limit returned to its previous level of $417,000 in most parts of the country. For designated the end of September, the limit returned to its previous level of $417,000 in most parts of the country. For designated “““high costhigh costhigh cost” ” ” areas, the areas, the areas, the limit is defined as the lesser of 115% of the local median value of homes or $625,500, thereby limiting the impact of the change.limit is defined as the lesser of 115% of the local median value of homes or $625,500, thereby limiting the impact of the change.limit is defined as the lesser of 115% of the local median value of homes or $625,500, thereby limiting the impact of the change.

Bills in both the House and Senate have been introduced calling for an extension of the higher loan limits at the GSEs as well as the FHA. Bills in both the House and Senate have been introduced calling for an extension of the higher loan limits at the GSEs as well as the FHA. Bills in both the House and Senate have been introduced calling for an extension of the higher loan limits at the GSEs as well as the FHA. Although the Senate approved measures that would restore high balance loan limits for Fannie Mae and Freddie Mac to $729,750, this Although the Senate approved measures that would restore high balance loan limits for Fannie Mae and Freddie Mac to $729,750, this Although the Senate approved measures that would restore high balance loan limits for Fannie Mae and Freddie Mac to $729,750, this measure was rejected by the House, and it is expected that the conforming limit for the GSEs will remain at $625,500.measure was rejected by the House, and it is expected that the conforming limit for the GSEs will remain at $625,500.measure was rejected by the House, and it is expected that the conforming limit for the GSEs will remain at $625,500.

In midIn midIn mid‐‐‐November, a bipartisan congressional committee sought to achieve a compromise by agreeing on a measure that would restore November, a bipartisan congressional committee sought to achieve a compromise by agreeing on a measure that would restore November, a bipartisan congressional committee sought to achieve a compromise by agreeing on a measure that would restore loan limits to $729,750 through 2013 in certain loan limits to $729,750 through 2013 in certain loan limits to $729,750 through 2013 in certain “““high costhigh costhigh cost” ” ” areas for the FHA exclusively. While the measure is not yet law, some areas for the FHA exclusively. While the measure is not yet law, some areas for the FHA exclusively. While the measure is not yet law, some momentum is building to approve it.momentum is building to approve it.momentum is building to approve it.

While lowering the conforming limit may be in the governmentWhile lowering the conforming limit may be in the governmentWhile lowering the conforming limit may be in the government’’’s best interest in the long run, it could have significant implications for home s best interest in the long run, it could have significant implications for home s best interest in the long run, it could have significant implications for home sales and prices in the short run as available credit for potential homebuyers is reduced. So far, expected increases in jumbo rates have been sales and prices in the short run as available credit for potential homebuyers is reduced. So far, expected increases in jumbo rates have been sales and prices in the short run as available credit for potential homebuyers is reduced. So far, expected increases in jumbo rates have been offset to some extent by the generally low interest rate environment. Should interest rates on Treasury securities start to rise, however, offset to some extent by the generally low interest rate environment. Should interest rates on Treasury securities start to rise, however, offset to some extent by the generally low interest rate environment. Should interest rates on Treasury securities start to rise, however, jumbo borrowers could see rates increase quickly.jumbo borrowers could see rates increase quickly.jumbo borrowers could see rates increase quickly.

Counteracting some of this impact would be a resurgence in private residential mortgageCounteracting some of this impact would be a resurgence in private residential mortgageCounteracting some of this impact would be a resurgence in private residential mortgage‐‐‐backed securities. While a few RMBS have been backed securities. While a few RMBS have been backed securities. While a few RMBS have been issued in the past year, the market has yet to recover to the degree necessary to have a meaningful impact. Without an indication that the issued in the past year, the market has yet to recover to the degree necessary to have a meaningful impact. Without an indication that the issued in the past year, the market has yet to recover to the degree necessary to have a meaningful impact. Without an indication that the private market is prepared to provide more mortgage financing, policymakers may be reluctant to reduce the governmentprivate market is prepared to provide more mortgage financing, policymakers may be reluctant to reduce the governmentprivate market is prepared to provide more mortgage financing, policymakers may be reluctant to reduce the government’’’s participation in s participation in s participation in the mortgage market. At present, the government is providing financing on approximately 95% of all new mortgage originations.the mortgage market. At present, the government is providing financing on approximately 95% of all new mortgage originations.the mortgage market. At present, the government is providing financing on approximately 95% of all new mortgage originations.

While it is likely that the FHAWhile it is likely that the FHAWhile it is likely that the FHA’’’s higher conforming loan limit will be restored in the short term, there is a possibility that it may be lowered s higher conforming loan limit will be restored in the short term, there is a possibility that it may be lowered s higher conforming loan limit will be restored in the short term, there is a possibility that it may be lowered prior to the end of 2013. Among the possible budget cuts being considered to reduce the federal deficit is a proposal to lower the prior to the end of 2013. Among the possible budget cuts being considered to reduce the federal deficit is a proposal to lower the prior to the end of 2013. Among the possible budget cuts being considered to reduce the federal deficit is a proposal to lower the conforming loan limit to $417,000 at a projected cost saving of $4 billion over 10 years.conforming loan limit to $417,000 at a projected cost saving of $4 billion over 10 years.conforming loan limit to $417,000 at a projected cost saving of $4 billion over 10 years.

Administration restrings HARP. In late October, the Obama administration proposed expanding borrower eligibility for the Home In late October, the Obama administration proposed expanding borrower eligibility for the Home In late October, the Obama administration proposed expanding borrower eligibility for the Home Affordable Refinance Program. HARP was introduced in 2009 to help underwater homeowners restructure their loans if they are backed by Affordable Refinance Program. HARP was introduced in 2009 to help underwater homeowners restructure their loans if they are backed by Affordable Refinance Program. HARP was introduced in 2009 to help underwater homeowners restructure their loans if they are backed by Fannie Mae and Freddie Mac.Fannie Mae and Freddie Mac.Fannie Mae and Freddie Mac.

Under reasonable assumptions about future mortgage rates and how the program will be implemented, the restrung HARP is expected to Under reasonable assumptions about future mortgage rates and how the program will be implemented, the restrung HARP is expected to Under reasonable assumptions about future mortgage rates and how the program will be implemented, the restrung HARP is expected to



refinance up to 1.6 million additional homes, bringing total refinancings under the program to 2.85 million.refinance up to 1.6 million additional homes, bringing total refinancings under the program to 2.85 million.refinance up to 1.6 million additional homes, bringing total refinancings under the program to 2.85 million.

The Obama administration initially thought the program would allow between four million and five million homeowners to take advantage The Obama administration initially thought the program would allow between four million and five million homeowners to take advantage The Obama administration initially thought the program would allow between four million and five million homeowners to take advantage of lower mortgage rates. To date, however, there have been fewer than 900,000 HARP refinancings, fewer than 100,000 of them involving of lower mortgage rates. To date, however, there have been fewer than 900,000 HARP refinancings, fewer than 100,000 of them involving of lower mortgage rates. To date, however, there have been fewer than 900,000 HARP refinancings, fewer than 100,000 of them involving underwater homeownersunderwater homeownersunderwater homeowners———those who owe more than their homesthose who owe more than their homesthose who owe more than their homes’ ’ ’ market value.market value.market value.

HARP has fallen well short of expectations for a range of reasons that the programHARP has fallen well short of expectations for a range of reasons that the programHARP has fallen well short of expectations for a range of reasons that the program’’’s changes address. These include increasing the number s changes address. These include increasing the number s changes address. These include increasing the number of homeowners eligible to participate; boosting the savings for homeowners who refinance, creating a larger incentive to participate; and of homeowners eligible to participate; boosting the savings for homeowners who refinance, creating a larger incentive to participate; and of homeowners eligible to participate; boosting the savings for homeowners who refinance, creating a larger incentive to participate; and substantially increasing incentives for mortgage servicers who enable more refinancing.substantially increasing incentives for mortgage servicers who enable more refinancing.substantially increasing incentives for mortgage servicers who enable more refinancing.

Although it is not a panacea for the housing marketAlthough it is not a panacea for the housing marketAlthough it is not a panacea for the housing market’’’s woes, the expanded HARP could help provide some stability to the housing market by s woes, the expanded HARP could help provide some stability to the housing market by s woes, the expanded HARP could help provide some stability to the housing market by lowering mortgage payments and preventing some foreclosures.lowering mortgage payments and preventing some foreclosures.lowering mortgage payments and preventing some foreclosures.

State attorneys general contemplate deal. Federal officials and other state attorneys general are negotiating a settlement over Federal officials and other state attorneys general are negotiating a settlement over Federal officials and other state attorneys general are negotiating a settlement over foreclosure abuses with major U.S. banks. A deal could provide some assistance to existing homeowners, though it may result in more foreclosure abuses with major U.S. banks. A deal could provide some assistance to existing homeowners, though it may result in more foreclosure abuses with major U.S. banks. A deal could provide some assistance to existing homeowners, though it may result in more limited credit in the future if lenders are required to conserve capital to pay fines and implement new systems and processes.limited credit in the future if lenders are required to conserve capital to pay fines and implement new systems and processes.limited credit in the future if lenders are required to conserve capital to pay fines and implement new systems and processes.

The agreement is geared toward settling statesThe agreement is geared toward settling statesThe agreement is geared toward settling states’ ’ ’ claims of poor mortgage and foreclosure practices, including the form of document fraud claims of poor mortgage and foreclosure practices, including the form of document fraud claims of poor mortgage and foreclosure practices, including the form of document fraud known as roboknown as roboknown as robo‐‐‐signing in which lenders approved documents used to file foreclosure proceedings without actually reading them.signing in which lenders approved documents used to file foreclosure proceedings without actually reading them.signing in which lenders approved documents used to file foreclosure proceedings without actually reading them.

A proposed settlement reportedly would prevent the states from pursuing claims against banks relating to fraud or abuse in the origination A proposed settlement reportedly would prevent the states from pursuing claims against banks relating to fraud or abuse in the origination A proposed settlement reportedly would prevent the states from pursuing claims against banks relating to fraud or abuse in the origination of loans during the housing boom. It would also prevent states from pursuing claims for foreclosure abuses, including the mishandling of loan of loans during the housing boom. It would also prevent states from pursuing claims for foreclosure abuses, including the mishandling of loan of loans during the housing boom. It would also prevent states from pursuing claims for foreclosure abuses, including the mishandling of loan modification application. Whether the proposal would preclude the states from pursuing the banks for issues related to the repackaging and modification application. Whether the proposal would preclude the states from pursuing the banks for issues related to the repackaging and modification application. Whether the proposal would preclude the states from pursuing the banks for issues related to the repackaging and marketing of loans as mortgagemarketing of loans as mortgagemarketing of loans as mortgage‐‐‐backed securities is unclear.backed securities is unclear.backed securities is unclear.

In return, large lenders would provide upward of $20 billion in foreclosure relief primarily in the form of writing down outstanding balances In return, large lenders would provide upward of $20 billion in foreclosure relief primarily in the form of writing down outstanding balances In return, large lenders would provide upward of $20 billion in foreclosure relief primarily in the form of writing down outstanding balances on tens of millions of mortgages.on tens of millions of mortgages.on tens of millions of mortgages.

Although the proposal appeared to gain some traction earlier in the year, a number of state attorneys general have publicly come out Although the proposal appeared to gain some traction earlier in the year, a number of state attorneys general have publicly come out Although the proposal appeared to gain some traction earlier in the year, a number of state attorneys general have publicly come out against it. Further delays in an agreement could dilute the impact that foreclosure relief could have on borrowers and the broader housing against it. Further delays in an agreement could dilute the impact that foreclosure relief could have on borrowers and the broader housing against it. Further delays in an agreement could dilute the impact that foreclosure relief could have on borrowers and the broader housing market.market.market.



Regional HighlightsRegional Highlights By Alexander MironBy Alexander Miron NOVEMBER 15, 2011NOVEMBER 15, 2011

ExistingExistingExisting‐‐‐house prices fell in most metro areas during the second quarter, but the number of metro areas in highhouse prices fell in most metro areas during the second quarter, but the number of metro areas in highhouse prices fell in most metro areas during the second quarter, but the number of metro areas in high‐‐‐ and elevated and elevated and elevated‐‐‐risk risk risk categories decreased slightly. categories decreased slightly. categories decreased slightly.

Metro areas most at risk of a house price decline are united by the effects of persistence in house price declines and stubbornly high Metro areas most at risk of a house price decline are united by the effects of persistence in house price declines and stubbornly high Metro areas most at risk of a house price decline are united by the effects of persistence in house price declines and stubbornly high foreclosure inventories. foreclosure inventories. foreclosure inventories.

Metro areas least likely to experience a house price decline are generally undersupplied or underpriced and are less burdened by Metro areas least likely to experience a house price decline are generally undersupplied or underpriced and are less burdened by Metro areas least likely to experience a house price decline are generally undersupplied or underpriced and are less burdened by foreclosures than the national average. foreclosures than the national average. foreclosures than the national average.

Based on valuation and supply balance metrics for the second quarter, MoodyBased on valuation and supply balance metrics for the second quarter, MoodyBased on valuation and supply balance metrics for the second quarter, Moody’’’s Analytics classifies 82 metro areas as having a very high risk s Analytics classifies 82 metro areas as having a very high risk s Analytics classifies 82 metro areas as having a very high risk of house price declines in the next year. Encouragingly, the number of metro areas in the very high risk category decreased from the first of house price declines in the next year. Encouragingly, the number of metro areas in the very high risk category decreased from the first of house price declines in the next year. Encouragingly, the number of metro areas in the very high risk category decreased from the first quarter even though house prices in most regions fell during the second quarter, a factor that raises the odds prices will drop in the near quarter even though house prices in most regions fell during the second quarter, a factor that raises the odds prices will drop in the near quarter even though house prices in most regions fell during the second quarter, a factor that raises the odds prices will drop in the near future. The shrinking highfuture. The shrinking highfuture. The shrinking high‐‐‐risk category is largely a reflection of the widespread and even more substantial improvement in housing supply risk category is largely a reflection of the widespread and even more substantial improvement in housing supply risk category is largely a reflection of the widespread and even more substantial improvement in housing supply balances, more favorable valuations, and smaller REO inventories. In fact, just 11 metro areas in the second quarter showed a housing supply balances, more favorable valuations, and smaller REO inventories. In fact, just 11 metro areas in the second quarter showed a housing supply balances, more favorable valuations, and smaller REO inventories. In fact, just 11 metro areas in the second quarter showed a housing supply balance in excess of five months, which loosely separates a balanced market from an oversupplied market.balance in excess of five months, which loosely separates a balanced market from an oversupplied market.balance in excess of five months, which loosely separates a balanced market from an oversupplied market.

Other factors important to future house prices have been slower to improve over the last several quarters. The metro areas that compose Other factors important to future house prices have been slower to improve over the last several quarters. The metro areas that compose Other factors important to future house prices have been slower to improve over the last several quarters. The metro areas that compose the high risk and very high risk categories are united by persistence in house price declines, stubbornly high REO inventories, and weak labor the high risk and very high risk categories are united by persistence in house price declines, stubbornly high REO inventories, and weak labor the high risk and very high risk categories are united by persistence in house price declines, stubbornly high REO inventories, and weak labor markets where nonhousing employment fell over the year in the second quarter. Market structure also plays a role in determining which markets where nonhousing employment fell over the year in the second quarter. Market structure also plays a role in determining which markets where nonhousing employment fell over the year in the second quarter. Market structure also plays a role in determining which metro areas are likely to experience a house price recovery over the coming year. Broadly speaking, metro areas with ties to growing tech, metro areas are likely to experience a house price recovery over the coming year. Broadly speaking, metro areas with ties to growing tech, metro areas are likely to experience a house price recovery over the coming year. Broadly speaking, metro areas with ties to growing tech, manufacturing or aerospace industries are positioned to recover more quickly than those that suffer from shrinking employment or manufacturing or aerospace industries are positioned to recover more quickly than those that suffer from shrinking employment or manufacturing or aerospace industries are positioned to recover more quickly than those that suffer from shrinking employment or population bases or those that have strong ties to the federal government.population bases or those that have strong ties to the federal government.population bases or those that have strong ties to the federal government.

Provo’’’s bloated foreclosure pipeline is a key reason why the LHPI anticipates house prices will decline through at least mids bloated foreclosure pipeline is a key reason why the LHPI anticipates house prices will decline through at least mids bloated foreclosure pipeline is a key reason why the LHPI anticipates house prices will decline through at least mid‐‐‐2012, placing the 2012, placing the 2012, placing the odds of a drop at 4odds of a drop at 4odds of a drop at 4‐‐‐tototo‐‐‐1. Foreclosures, which have been a much greater weight on Provo1. Foreclosures, which have been a much greater weight on Provo1. Foreclosures, which have been a much greater weight on Provo’’’s housing market than state and national averages, s housing market than state and national averages, s housing market than state and national averages, are the last major hurdle for local price stability. The persistence of house price declines in Provoare the last major hurdle for local price stability. The persistence of house price declines in Provoare the last major hurdle for local price stability. The persistence of house price declines in Provo———since 2007, house prices have fallen in since 2007, house prices have fallen in since 2007, house prices have fallen in every quarter except for oneevery quarter except for oneevery quarter except for one———is the leading factor behind the metro areais the leading factor behind the metro areais the leading factor behind the metro area’’’s highs highs high‐‐‐risk ranking. House prices fell faster in early 2011 than they risk ranking. House prices fell faster in early 2011 than they risk ranking. House prices fell faster in early 2011 than they did in 2010 because lenders began disposing of their burgeoning supply of repossessed homes at a faster rate. However, the share of did in 2010 because lenders began disposing of their burgeoning supply of repossessed homes at a faster rate. However, the share of did in 2010 because lenders began disposing of their burgeoning supply of repossessed homes at a faster rate. However, the share of households with homes in REO, many of which will ultimately be disposed of through a distress sale, is twice the national average, which households with homes in REO, many of which will ultimately be disposed of through a distress sale, is twice the national average, which households with homes in REO, many of which will ultimately be disposed of through a distress sale, is twice the national average, which greatly increases the odds that prices will continue falling over the next few quarters.greatly increases the odds that prices will continue falling over the next few quarters.greatly increases the odds that prices will continue falling over the next few quarters.

MoodyMoodyMoody’’’s Analytics expects existing singles Analytics expects existing singles Analytics expects existing single‐‐‐family house prices will stabilize by the middle of 2012. Although the share of homes in REO is family house prices will stabilize by the middle of 2012. Although the share of homes in REO is family house prices will stabilize by the middle of 2012. Although the share of homes in REO is above the U.S. average, local mortgage delinquency rates have fallen significantly, so there will gradually be fewer new foreclosures on the above the U.S. average, local mortgage delinquency rates have fallen significantly, so there will gradually be fewer new foreclosures on the above the U.S. average, local mortgage delinquency rates have fallen significantly, so there will gradually be fewer new foreclosures on the market.market.market.

Even after years of falling prices, a few markets are still rated as generally unaffordable. As one of these, Even after years of falling prices, a few markets are still rated as generally unaffordable. As one of these, Even after years of falling prices, a few markets are still rated as generally unaffordable. As one of these, Miami still faces a very high risk of still faces a very high risk of still faces a very high risk of

Metro AreaMetro AreaMetro Area Leading House Price IndicatorLeading House Price IndicatorLeading House Price Indicator % House Price Balance% House Price Balance% House Price Balance Mo of Excess SupplyMo of Excess SupplyMo of Excess Supply Provo UTProvo UTProvo UT 80.280.280.2 BalancedBalancedBalanced ‐‐‐3.93.93.9 Miami FLMiami FLMiami FL 77.677.677.6 BalancedBalancedBalanced ‐‐‐10.010.010.0 Virginia Beach VAVirginia Beach VAVirginia Beach VA 76.476.476.4 BalancedBalancedBalanced ‐‐‐4.94.94.9 Tucson AZTucson AZTucson AZ 64.964.964.9 Highly UndervaluedHighly UndervaluedHighly Undervalued ‐‐‐5.75.75.7 Seattle WASeattle WASeattle WA 61.161.161.1 Highly UndervaluedHighly UndervaluedHighly Undervalued ‐‐‐6.46.46.4 Washington DCWashington DCWashington DC 16.716.716.7 BalancedBalancedBalanced ‐‐‐7.47.47.4 Cleveland OHCleveland OHCleveland OH 12.512.512.5 Highly UndervaluedHighly UndervaluedHighly Undervalued ‐‐‐5.25.25.2 San Francisco CASan Francisco CASan Francisco CA 10.710.710.7 Highly UndervaluedHighly UndervaluedHighly Undervalued ‐‐‐10.410.410.4 Memphis TNMemphis TNMemphis TN 9.59.59.5 Highly UndervaluedHighly UndervaluedHighly Undervalued ‐‐‐5.45.45.4 Baltimore MDBaltimore MDBaltimore MD 8.28.28.2 Highly UndervaluedHighly UndervaluedHighly Undervalued ‐‐‐6.46.46.4



experiencing a price decline before midexperiencing a price decline before midexperiencing a price decline before mid‐‐‐2012. As measured by the Moody2012. As measured by the Moody2012. As measured by the Moody’’’s Analytics housing affordability index, singles Analytics housing affordability index, singles Analytics housing affordability index, single‐‐‐family homes are family homes are family homes are less affordable in relation to local household income than the U.S. average and are among the least affordable in all of Florida, second only less affordable in relation to local household income than the U.S. average and are among the least affordable in all of Florida, second only less affordable in relation to local household income than the U.S. average and are among the least affordable in all of Florida, second only to Naples. In addition, despite the recent improvement in nonhousing employment growth, Miamito Naples. In addition, despite the recent improvement in nonhousing employment growth, Miamito Naples. In addition, despite the recent improvement in nonhousing employment growth, Miami’’’s mortgage default rate and foreclosure s mortgage default rate and foreclosure s mortgage default rate and foreclosure backlog raise substantial downside risk for prices. Consistent with the very high risk ranking results from the LHPI, Moodybacklog raise substantial downside risk for prices. Consistent with the very high risk ranking results from the LHPI, Moodybacklog raise substantial downside risk for prices. Consistent with the very high risk ranking results from the LHPI, Moody’’’s Analytics expects s Analytics expects s Analytics expects local house prices will fall by about 13% through early 2013.local house prices will fall by about 13% through early 2013.local house prices will fall by about 13% through early 2013.

MiamiMiamiMiami’’’s struggles with foreclosures are unfortunate because other fundamental house price drivers are in good shapes struggles with foreclosures are unfortunate because other fundamental house price drivers are in good shapes struggles with foreclosures are unfortunate because other fundamental house price drivers are in good shape———the supply balance the supply balance the supply balance indicator paints a picture of a market that has significant pentindicator paints a picture of a market that has significant pentindicator paints a picture of a market that has significant pent‐‐‐up demand, although this has yet to translate into increased home sales. In up demand, although this has yet to translate into increased home sales. In up demand, although this has yet to translate into increased home sales. In addition, house prices remain undervalued in relation to the value that is consistent with underlying demographic and economic drivers, in addition, house prices remain undervalued in relation to the value that is consistent with underlying demographic and economic drivers, in addition, house prices remain undervalued in relation to the value that is consistent with underlying demographic and economic drivers, in particular, population and per capita income growth as well as vacationparticular, population and per capita income growth as well as vacationparticular, population and per capita income growth as well as vacation‐‐‐home demand. The housing supply balance is well below zerohome demand. The housing supply balance is well below zerohome demand. The housing supply balance is well below zero———implying significant pentimplying significant pentimplying significant pent‐‐‐up demandup demandup demand———while the price balance metric suggests house prices are about 12% below the level consistent with while the price balance metric suggests house prices are about 12% below the level consistent with while the price balance metric suggests house prices are about 12% below the level consistent with recent growth in household income. Down the road, after breaking through its foreclosure backlog, Miami could be a good candidate for a recent growth in household income. Down the road, after breaking through its foreclosure backlog, Miami could be a good candidate for a recent growth in household income. Down the road, after breaking through its foreclosure backlog, Miami could be a good candidate for a metro area where prices rise quickly back to their fundamental values.metro area where prices rise quickly back to their fundamental values.metro area where prices rise quickly back to their fundamental values.

Overvalued singleOvervalued singleOvervalued single‐‐‐family house prices have been an ongoing theme in the family house prices have been an ongoing theme in the family house prices have been an ongoing theme in the Virginia Beach housing market, but the second quarter of 2011 housing market, but the second quarter of 2011 housing market, but the second quarter of 2011 brought some improvement. For the first time since the house price correction began, the Moodybrought some improvement. For the first time since the house price correction began, the Moodybrought some improvement. For the first time since the house price correction began, the Moody’’’s Analytics price balance measure shows s Analytics price balance measure shows s Analytics price balance measure shows singlesinglesingle‐‐‐family homes are in line with value fundamentals. However, at least over the short term, a high number of foreclosures will cause family homes are in line with value fundamentals. However, at least over the short term, a high number of foreclosures will cause family homes are in line with value fundamentals. However, at least over the short term, a high number of foreclosures will cause local house prices to local house prices to local house prices to ‘‘‘overcorrect,overcorrect,overcorrect,’ ’ ’ dipping below this equilibrium value. Moodydipping below this equilibrium value. Moodydipping below this equilibrium value. Moody’’’s Analytics anticipates existings Analytics anticipates existings Analytics anticipates existing‐‐‐house prices in the metro house prices in the metro house prices in the metro area will fall by about 3.6% through the end of 2011 before reaching a trough. Downside risks cloud the outlook for foreclosures and house area will fall by about 3.6% through the end of 2011 before reaching a trough. Downside risks cloud the outlook for foreclosures and house area will fall by about 3.6% through the end of 2011 before reaching a trough. Downside risks cloud the outlook for foreclosures and house prices. Virginia Beach appears to be working through its foreclosure backlog at a much slower rate than many regions of the country. This prices. Virginia Beach appears to be working through its foreclosure backlog at a much slower rate than many regions of the country. This prices. Virginia Beach appears to be working through its foreclosure backlog at a much slower rate than many regions of the country. This raises the odds that house prices will take longer to reach their trough than the baseline forecast assumes.raises the odds that house prices will take longer to reach their trough than the baseline forecast assumes.raises the odds that house prices will take longer to reach their trough than the baseline forecast assumes.

The likelihood is high that house prices in The likelihood is high that house prices in The likelihood is high that house prices in Tucson will fall over the coming year. The persistence of house price declines is a major weight on will fall over the coming year. The persistence of house price declines is a major weight on will fall over the coming year. The persistence of house price declines is a major weight on TucsonTucsonTucson’’’s housing market. Falling prices alter the behavior of buyers, sellers and lenders, deterring home sales, which in turn fuels more price s housing market. Falling prices alter the behavior of buyers, sellers and lenders, deterring home sales, which in turn fuels more price s housing market. Falling prices alter the behavior of buyers, sellers and lenders, deterring home sales, which in turn fuels more price declines. In Tucson, this cycle has become selfdeclines. In Tucson, this cycle has become selfdeclines. In Tucson, this cycle has become self‐‐‐reinforcing; a large share of households are under water on their mortgages, owing more than reinforcing; a large share of households are under water on their mortgages, owing more than reinforcing; a large share of households are under water on their mortgages, owing more than the value of the underlying home, which greatly raises the odds prices will fall over the next several quarters. Renewed job growth could the value of the underlying home, which greatly raises the odds prices will fall over the next several quarters. Renewed job growth could the value of the underlying home, which greatly raises the odds prices will fall over the next several quarters. Renewed job growth could break this cycle, but Tucsonbreak this cycle, but Tucsonbreak this cycle, but Tucson’’’s relatively recent labor market recovery appears to have hit a soft patch. Unfortunately, the Moodys relatively recent labor market recovery appears to have hit a soft patch. Unfortunately, the Moodys relatively recent labor market recovery appears to have hit a soft patch. Unfortunately, the Moody’’’s Analytics s Analytics s Analytics baseline outlook agrees with the results of the LHPI, calling for a drop of nearly 5% before the labor market begins creating jobs at a steady baseline outlook agrees with the results of the LHPI, calling for a drop of nearly 5% before the labor market begins creating jobs at a steady baseline outlook agrees with the results of the LHPI, calling for a drop of nearly 5% before the labor market begins creating jobs at a steady rate and the price correction runs its course.rate and the price correction runs its course.rate and the price correction runs its course.

Seattle’’’s housing market falls into the highs housing market falls into the highs housing market falls into the high‐‐‐risk category largely because of somewhat lower than average singlerisk category largely because of somewhat lower than average singlerisk category largely because of somewhat lower than average single‐‐‐family housing family housing family housing affordability and elevated REO inventory, a trait shared by many metro areas in the Pacific and Mountain West divisions. Seattleaffordability and elevated REO inventory, a trait shared by many metro areas in the Pacific and Mountain West divisions. Seattleaffordability and elevated REO inventory, a trait shared by many metro areas in the Pacific and Mountain West divisions. Seattle’’’s strong s strong s strong labor market reboundlabor market reboundlabor market rebound———nonhousing employment rose by more than 2% from a year ago in the second quarter compared with a rise of less nonhousing employment rose by more than 2% from a year ago in the second quarter compared with a rise of less nonhousing employment rose by more than 2% from a year ago in the second quarter compared with a rise of less than 1% at the national levelthan 1% at the national levelthan 1% at the national level———is key to its improving risk profile. The areais key to its improving risk profile. The areais key to its improving risk profile. The area’’’s aerospace and software publishing industries are responsible for s aerospace and software publishing industries are responsible for s aerospace and software publishing industries are responsible for leading the recovery, and strong aircraft orders and tech spending suggest the job market will remain on firm ground.leading the recovery, and strong aircraft orders and tech spending suggest the job market will remain on firm ground.leading the recovery, and strong aircraft orders and tech spending suggest the job market will remain on firm ground.

Through the end of 2011, SeattleThrough the end of 2011, SeattleThrough the end of 2011, Seattle’’’s high share of households with homes in foreclosure will cause existings high share of households with homes in foreclosure will cause existings high share of households with homes in foreclosure will cause existing‐‐‐house prices to fall by an additional house prices to fall by an additional house prices to fall by an additional 2.8%. However, longer2.8%. However, longer2.8%. However, longer‐‐‐term demographics remain supportive of house price appreciation. Seattle, like many metro areas in the Northwest term demographics remain supportive of house price appreciation. Seattle, like many metro areas in the Northwest term demographics remain supportive of house price appreciation. Seattle, like many metro areas in the Northwest where supply and demand are now in balance, is very likely to be highly undersupplied by the middle of 2012. Once the negative feedback where supply and demand are now in balance, is very likely to be highly undersupplied by the middle of 2012. Once the negative feedback where supply and demand are now in balance, is very likely to be highly undersupplied by the middle of 2012. Once the negative feedback loop that arises from Seattleloop that arises from Seattleloop that arises from Seattle’’’s high foreclosure rate breaks, its aboves high foreclosure rate breaks, its aboves high foreclosure rate breaks, its above‐‐‐average share of younger households will translate into strong average share of younger households will translate into strong average share of younger households will translate into strong demand for singledemand for singledemand for single‐‐‐family housing.family housing.family housing.

Washington DC’’’s housing bust unfolded in line with most of the rest of the country, but its recovery will lead that of the nation. Existings housing bust unfolded in line with most of the rest of the country, but its recovery will lead that of the nation. Existings housing bust unfolded in line with most of the rest of the country, but its recovery will lead that of the nation. Existing‐‐‐house prices are already showing signs of strength: The Casehouse prices are already showing signs of strength: The Casehouse prices are already showing signs of strength: The Case‐‐‐Shiller singleShiller singleShiller single‐‐‐family aggregate index rose in the second quarter and is up by family aggregate index rose in the second quarter and is up by family aggregate index rose in the second quarter and is up by about 1% over the year. From a fundamental perspective, the conditions are in place that will allow the District of Columbiaabout 1% over the year. From a fundamental perspective, the conditions are in place that will allow the District of Columbiaabout 1% over the year. From a fundamental perspective, the conditions are in place that will allow the District of Columbia’’’s housing s housing s housing market to continue improving. Namely, housing supply balance and price valuation metrics favor stability in existingmarket to continue improving. Namely, housing supply balance and price valuation metrics favor stability in existingmarket to continue improving. Namely, housing supply balance and price valuation metrics favor stability in existing‐‐‐house prices. Net inhouse prices. Net inhouse prices. Net in‐‐‐migration throughout the recession and the District of Columbiamigration throughout the recession and the District of Columbiamigration throughout the recession and the District of Columbia’’’s stronger labor market helped the metro area get a head start on the U.S.; s stronger labor market helped the metro area get a head start on the U.S.; s stronger labor market helped the metro area get a head start on the U.S.; according to the supply balance indicator, the metro area boasts sizable pentaccording to the supply balance indicator, the metro area boasts sizable pentaccording to the supply balance indicator, the metro area boasts sizable pent‐‐‐up demand.up demand.up demand.

The LHPI assigns the District of Columbia housing market slightly less than a 1The LHPI assigns the District of Columbia housing market slightly less than a 1The LHPI assigns the District of Columbia housing market slightly less than a 1‐‐‐ininin‐‐‐5 chance of seeing prices drop during 2012, which lends 5 chance of seeing prices drop during 2012, which lends 5 chance of seeing prices drop during 2012, which lends upside risk to the Moodyupside risk to the Moodyupside risk to the Moody’’’s Analytics baseline forecast for a modest decline of 3%. The major factors behind the forecast for a decline are s Analytics baseline forecast for a modest decline of 3%. The major factors behind the forecast for a decline are s Analytics baseline forecast for a modest decline of 3%. The major factors behind the forecast for a decline are worries stemming from federal government cutbacks, which are likely to hurt local area incomes, restraining homebuying and house prices.worries stemming from federal government cutbacks, which are likely to hurt local area incomes, restraining homebuying and house prices.worries stemming from federal government cutbacks, which are likely to hurt local area incomes, restraining homebuying and house prices.

The risk of a house price decline is very low in The risk of a house price decline is very low in The risk of a house price decline is very low in Cleveland, which never experienced much in the way of a housing bubble during the middle of , which never experienced much in the way of a housing bubble during the middle of , which never experienced much in the way of a housing bubble during the middle of last decade, making the metro area unlike much of the rest of the country. Excess supply did not have much chance to develop, but instead last decade, making the metro area unlike much of the rest of the country. Excess supply did not have much chance to develop, but instead last decade, making the metro area unlike much of the rest of the country. Excess supply did not have much chance to develop, but instead



of a supply imbalance, Cleveland suffers from a lack of demand, which has kept downward pressure on existingof a supply imbalance, Cleveland suffers from a lack of demand, which has kept downward pressure on existingof a supply imbalance, Cleveland suffers from a lack of demand, which has kept downward pressure on existing‐‐‐house prices throughout house prices throughout house prices throughout 2011. Although the loss of households slowed somewhat during the recession, Moody2011. Although the loss of households slowed somewhat during the recession, Moody2011. Although the loss of households slowed somewhat during the recession, Moody’’’s Analytics estimates the overall number of s Analytics estimates the overall number of s Analytics estimates the overall number of households resumed falling in 2010. Because the supply balance indicator upon which the LHPI is based measures the change in housing households resumed falling in 2010. Because the supply balance indicator upon which the LHPI is based measures the change in housing households resumed falling in 2010. Because the supply balance indicator upon which the LHPI is based measures the change in housing supply relative to demand but does not consider the overall level of either, the indicator may understate the likelihood of house price supply relative to demand but does not consider the overall level of either, the indicator may understate the likelihood of house price supply relative to demand but does not consider the overall level of either, the indicator may understate the likelihood of house price declines over the short term. In fact, Moodydeclines over the short term. In fact, Moodydeclines over the short term. In fact, Moody’’’s Analytics believes house prices in Cleveland will fall another 3.6% before bottoming in mids Analytics believes house prices in Cleveland will fall another 3.6% before bottoming in mids Analytics believes house prices in Cleveland will fall another 3.6% before bottoming in mid‐‐‐2012.2012.2012.

So long as the local population base is shrinking, it is hard to be upbeat about ClevelandSo long as the local population base is shrinking, it is hard to be upbeat about ClevelandSo long as the local population base is shrinking, it is hard to be upbeat about Cleveland’’’s prospects. With younger households increasingly s prospects. With younger households increasingly s prospects. With younger households increasingly searching for work in other regions, the demographic makeup is quickly shifting toward the older cohorts, few of whom are likely to demand searching for work in other regions, the demographic makeup is quickly shifting toward the older cohorts, few of whom are likely to demand searching for work in other regions, the demographic makeup is quickly shifting toward the older cohorts, few of whom are likely to demand singlesinglesingle‐‐‐family housing. This could mean the regionfamily housing. This could mean the regionfamily housing. This could mean the region’’’s houses will remain undervalued in relation to local incomes over the next few years while s houses will remain undervalued in relation to local incomes over the next few years while s houses will remain undervalued in relation to local incomes over the next few years while a very slow pace of house price appreciation emerges.a very slow pace of house price appreciation emerges.a very slow pace of house price appreciation emerges.

After years of struggling with oppressively high mortgage delinquency rates and foreclosures, the After years of struggling with oppressively high mortgage delinquency rates and foreclosures, the After years of struggling with oppressively high mortgage delinquency rates and foreclosures, the Memphis housing market appears to housing market appears to housing market appears to have absorbed its excesses and is in relatively good health. The LHPI places Memphis in the lowest risk category because of its favorable have absorbed its excesses and is in relatively good health. The LHPI places Memphis in the lowest risk category because of its favorable have absorbed its excesses and is in relatively good health. The LHPI places Memphis in the lowest risk category because of its favorable supply balance and highly undervalued house prices, which were push far below their fundamental value because of widespread bank sales of supply balance and highly undervalued house prices, which were push far below their fundamental value because of widespread bank sales of supply balance and highly undervalued house prices, which were push far below their fundamental value because of widespread bank sales of REO properties. MemphisREO properties. MemphisREO properties. Memphis’ ’ ’ REO inventory is half as large as the U.S. average, on a per household basis, despite being nearly twice as large as REO inventory is half as large as the U.S. average, on a per household basis, despite being nearly twice as large as REO inventory is half as large as the U.S. average, on a per household basis, despite being nearly twice as large as average during 2008.average during 2008.average during 2008.

Consistent with the results of the LHPI, MoodyConsistent with the results of the LHPI, MoodyConsistent with the results of the LHPI, Moody’’’s Analytics believes existings Analytics believes existings Analytics believes existing‐‐‐house prices in Memphis have reached their trough. Prices will house prices in Memphis have reached their trough. Prices will house prices in Memphis have reached their trough. Prices will remain flat during the second half of 2011 before experiencing a modest fillip in 2012, when fewer foreclosures, low mortgage rates, and a remain flat during the second half of 2011 before experiencing a modest fillip in 2012, when fewer foreclosures, low mortgage rates, and a remain flat during the second half of 2011 before experiencing a modest fillip in 2012, when fewer foreclosures, low mortgage rates, and a healthier job market will contribute to a pop in prices.healthier job market will contribute to a pop in prices.healthier job market will contribute to a pop in prices.

In terms of existingIn terms of existingIn terms of existing‐‐‐house prices, house prices, house prices, Baltimore is very near its bottom. The LHPI categorizes Baltimore in the very low risk category largely is very near its bottom. The LHPI categorizes Baltimore in the very low risk category largely is very near its bottom. The LHPI categorizes Baltimore in the very low risk category largely because measures of its housing supply balance and valuation show strong support for house price growth. In addition, although distress sales because measures of its housing supply balance and valuation show strong support for house price growth. In addition, although distress sales because measures of its housing supply balance and valuation show strong support for house price growth. In addition, although distress sales are still a weight on overall house prices, Baltimoreare still a weight on overall house prices, Baltimoreare still a weight on overall house prices, Baltimore’’’s much lower REO inventory overhang means there is less risk of an extended drag from s much lower REO inventory overhang means there is less risk of an extended drag from s much lower REO inventory overhang means there is less risk of an extended drag from clearing the lowclearing the lowclearing the low‐‐‐priced foreclosure inventory.priced foreclosure inventory.priced foreclosure inventory.

Despite its favorable fundamentals, house prices in Baltimore have fallen at a steady rate over the past year because of the disappointing Despite its favorable fundamentals, house prices in Baltimore have fallen at a steady rate over the past year because of the disappointing Despite its favorable fundamentals, house prices in Baltimore have fallen at a steady rate over the past year because of the disappointing performance of local employment and income growth. The nearperformance of local employment and income growth. The nearperformance of local employment and income growth. The near‐‐‐term outlook anticipates the economy will tread water over the next term outlook anticipates the economy will tread water over the next term outlook anticipates the economy will tread water over the next couple of months because of diminished federal spending, upon which local federal civilian and military personnel rely heavily. Moodycouple of months because of diminished federal spending, upon which local federal civilian and military personnel rely heavily. Moodycouple of months because of diminished federal spending, upon which local federal civilian and military personnel rely heavily. Moody’’’s s s Analytics therefore expects existingAnalytics therefore expects existingAnalytics therefore expects existing‐‐‐house prices will fall by about 2% through the end of 2011 before the labor market firms enough to house prices will fall by about 2% through the end of 2011 before the labor market firms enough to house prices will fall by about 2% through the end of 2011 before the labor market firms enough to support a stable rebound in price appreciation.support a stable rebound in price appreciation.support a stable rebound in price appreciation.

San Francisco stands out among western metro areas as one of the least vulnerable to house price declines over the coming year because stands out among western metro areas as one of the least vulnerable to house price declines over the coming year because stands out among western metro areas as one of the least vulnerable to house price declines over the coming year because of its strong fundamentals, which will limit any additional decline in existingof its strong fundamentals, which will limit any additional decline in existingof its strong fundamentals, which will limit any additional decline in existing‐‐‐house prices. Specifically, the accumulation of considerable penthouse prices. Specifically, the accumulation of considerable penthouse prices. Specifically, the accumulation of considerable pent‐‐‐up demand as well as generally high household incomes that make singleup demand as well as generally high household incomes that make singleup demand as well as generally high household incomes that make single‐‐‐family housing appear undervalued set San Francisco apart from family housing appear undervalued set San Francisco apart from family housing appear undervalued set San Francisco apart from many of the hardmany of the hardmany of the hard‐‐‐hit housing markets in the West. Meanwhile, foreclosures, which are a big problem throughout much of the region, pose hit housing markets in the West. Meanwhile, foreclosures, which are a big problem throughout much of the region, pose hit housing markets in the West. Meanwhile, foreclosures, which are a big problem throughout much of the region, pose little danger to local house prices. Even an uptick in new foreclosure filings would not prevent house prices from bottoming by the end of little danger to local house prices. Even an uptick in new foreclosure filings would not prevent house prices from bottoming by the end of little danger to local house prices. Even an uptick in new foreclosure filings would not prevent house prices from bottoming by the end of 2011, ahead of California and the rest of the U.S.2011, ahead of California and the rest of the U.S.2011, ahead of California and the rest of the U.S.

MoodyMoodyMoody’’’s Analytics projects house prices in San Francisco will decline modestly over the short term, experiencing a decline of 3.6% before s Analytics projects house prices in San Francisco will decline modestly over the short term, experiencing a decline of 3.6% before s Analytics projects house prices in San Francisco will decline modestly over the short term, experiencing a decline of 3.6% before the end of 2011, which reflects some lingering weakness in the labor market and some competition from stillthe end of 2011, which reflects some lingering weakness in the labor market and some competition from stillthe end of 2011, which reflects some lingering weakness in the labor market and some competition from still‐‐‐low apartment rents, which are low apartment rents, which are low apartment rents, which are not included as a factor in the LHPI.not included as a factor in the LHPI.not included as a factor in the LHPI.



SupplySupply

UPDATED: 12/13/2011UPDATED: 12/13/2011UPDATED: 12/13/2011 UPDATED: 12/13/2011UPDATED: 12/13/2011UPDATED: 12/13/2011





DemandDemand






Mortgage MarketMortgage Market






Supply Balance IndicatorSupply Balance Indicator Incorporating data through 2011Q2Incorporating data through 2011Q2Incorporating data through 2011Q2

Last updated on: 12/12/2011Last updated on: 12/12/2011Last updated on: 12/12/2011Last updated on: 12/12/2011

Excess SupplyExcess SupplyExcess SupplyExcess Supply Trend of Excess SupplyTrend of Excess SupplyTrend of Excess SupplyTrend of Excess Supply

FIPFIPFIPFIP Metro AreaMetro AreaMetro AreaMetro Area MonthsMonthsMonthsMonths IndexIndexIndexIndex Q/Q changeQ/Q changeQ/Q changeQ/Q change Y/Y changeY/Y changeY/Y changeY/Y change

101801018010180 Abilene TXAbilene TXAbilene TXAbilene TX ‐‐‐8.48.48.4 999999 no changeno changeno change no changeno changeno change

104201042010420 Akron OHAkron OHAkron OHAkron OH ‐‐‐5.05.05.0 939393 no changeno changeno change upupup

105001050010500 Albany GAAlbany GAAlbany GAAlbany GA ‐‐‐3.73.73.7 878787 upupup upupup

105801058010580 Albany NYAlbany NYAlbany NYAlbany NY ‐‐‐2.22.22.2 757575 no changeno changeno change upupup

107401074010740 Albuquerque NMAlbuquerque NMAlbuquerque NMAlbuquerque NM ‐‐‐6.36.36.3 979797 no changeno changeno change no changeno changeno change

107801078010780 Alexandria LAAlexandria LAAlexandria LAAlexandria LA ‐‐‐0.50.50.5 565656 upupup upupup

109001090010900 Allentown PAAllentown PAAllentown PAAllentown PA ‐‐‐2.62.62.6 787878 upupup upupup

110201102011020 Altoona PAAltoona PAAltoona PAAltoona PA ‐‐‐5.95.95.9 969696 no changeno changeno change no changeno changeno change

111001110011100 Amarillo TXAmarillo TXAmarillo TXAmarillo TX ‐‐‐6.56.56.5 979797 no changeno changeno change no changeno changeno change

111801118011180 Ames IAAmes IAAmes IAAmes IA ‐‐‐7.37.37.3 989898 no changeno changeno change no changeno changeno change

112601126011260 Anchorage AKAnchorage AKAnchorage AKAnchorage AK ‐‐‐10.310.310.3 100100100 no changeno changeno change no changeno changeno change

113001130011300 Anderson INAnderson INAnderson INAnderson IN ‐‐‐7.67.67.6 999999 no changeno changeno change upupup

113401134011340 Anderson SCAnderson SCAnderson SCAnderson SC ‐‐‐4.44.44.4 919191 upupup upupup

114601146011460 Ann Arbor MIAnn Arbor MIAnn Arbor MIAnn Arbor MI ‐‐‐6.66.66.6 979797 no changeno changeno change upupup

115001150011500 Anniston ALAnniston ALAnniston ALAnniston AL ‐‐‐3.23.23.2 848484 no changeno changeno change upupup

115401154011540 Appleton WIAppleton WIAppleton WIAppleton WI ‐‐‐5.35.35.3 949494 no changeno changeno change no changeno changeno change

117001170011700 Asheville NCAsheville NCAsheville NCAsheville NC ‐‐‐4.64.64.6 929292 no changeno changeno change upupup

120201202012020 Athens GAAthens GAAthens GAAthens GA ‐‐‐3.33.33.3 848484 upupup upupup

120601206012060 Atlanta GAAtlanta GAAtlanta GAAtlanta GA ‐‐‐5.85.85.8 969696 no changeno changeno change upupup

121001210012100 Atlantic City NJAtlantic City NJAtlantic City NJAtlantic City NJ 1.71.71.7 313131 upupup upupup

122201222012220 Auburn ALAuburn ALAuburn ALAuburn AL ‐‐‐0.70.70.7 585858 upupup upupup

122601226012260 Augusta GAAugusta GAAugusta GAAugusta GA ‐‐‐4.14.14.1 898989 no changeno changeno change no changeno changeno change

124201242012420 Austin TXAustin TXAustin TXAustin TX ‐‐‐4.94.94.9 939393 no changeno changeno change no changeno changeno change

125401254012540 Bakersfield CABakersfield CABakersfield CABakersfield CA ‐‐‐3.93.93.9 888888 upupup upupup

125801258012580 Baltimore MDBaltimore MDBaltimore MDBaltimore MD ‐‐‐6.46.46.4 979797 no changeno changeno change upupup

126201262012620 Bangor MEBangor MEBangor MEBangor ME ‐‐‐1.61.61.6 696969 no changeno changeno change downdowndown

127001270012700 Barnstable Town MABarnstable Town MABarnstable Town MABarnstable Town MA ‐‐‐6.96.96.9 989898 no changeno changeno change upupup

129401294012940 Baton Rouge LABaton Rouge LABaton Rouge LABaton Rouge LA ‐‐‐2.22.22.2 757575 no changeno changeno change upupup

129801298012980 Battle Creek MIBattle Creek MIBattle Creek MIBattle Creek MI ‐‐‐2.52.52.5 787878 upupup upupup

130201302013020 Bay City MIBay City MIBay City MIBay City MI ‐‐‐4.34.34.3 909090 no changeno changeno change downdowndown

131401314013140 Beaumont TXBeaumont TXBeaumont TXBeaumont TX ‐‐‐1.91.91.9 727272 upupup upupup

133801338013380 Bellingham WABellingham WABellingham WABellingham WA ‐‐‐5.85.85.8 969696 no changeno changeno change no changeno changeno change

134601346013460 Bend ORBend ORBend ORBend OR ‐‐‐3.43.43.4 858585 upupup upupup

136441364413644 Bethesda MD [Metropolitan Division]Bethesda MD [Metropolitan Division]Bethesda MD [Metropolitan Division]Bethesda MD [Metropolitan Division] ‐‐‐8.08.08.0 999999 no changeno changeno change no changeno changeno change

137401374013740 Billings MTBillings MTBillings MTBillings MT ‐‐‐5.45.45.4 959595 no changeno changeno change no changeno changeno change

137801378013780 Binghamton NYBinghamton NYBinghamton NYBinghamton NY ‐‐‐2.72.72.7 808080 no changeno changeno change upupup

138201382013820 Birmingham ALBirmingham ALBirmingham ALBirmingham AL ‐‐‐2.22.22.2 757575 upupup upupup

139001390013900 Bismarck NDBismarck NDBismarck NDBismarck ND ‐‐‐3.53.53.5 858585 no changeno changeno change upupup

139801398013980 Blacksburg VABlacksburg VABlacksburg VABlacksburg VA ‐‐‐1.71.71.7 696969 upupup upupup

140601406014060 Bloomington ILBloomington ILBloomington ILBloomington IL ‐‐‐5.15.15.1 949494 no changeno changeno change no changeno changeno change

140201402014020 Bloomington INBloomington INBloomington INBloomington IN ‐‐‐6.66.66.6 979797 no changeno changeno change no changeno changeno change

142601426014260 Boise City IDBoise City IDBoise City IDBoise City ID ‐‐‐2.42.42.4 777777 upupup upupup

144841448414484 Boston MA [Metropolitan Division]Boston MA [Metropolitan Division]Boston MA [Metropolitan Division]Boston MA [Metropolitan Division] ‐‐‐8.58.58.5 999999 no changeno changeno change no changeno changeno change

145001450014500 Boulder COBoulder COBoulder COBoulder CO ‐‐‐8.18.18.1 999999 no changeno changeno change no changeno changeno change

145401454014540 Bowling Green KYBowling Green KYBowling Green KYBowling Green KY ‐‐‐4.74.74.7 929292 no changeno changeno change no changeno changeno change

147401474014740 Bremerton WABremerton WABremerton WABremerton WA ‐‐‐5.55.55.5 959595 no changeno changeno change upupup

148601486014860 Bridgeport CTBridgeport CTBridgeport CTBridgeport CT ‐‐‐7.97.97.9 999999 no changeno changeno change no changeno changeno change

151801518015180 Brownsville TXBrownsville TXBrownsville TXBrownsville TX ‐‐‐4.74.74.7 929292 no changeno changeno change upupup

152601526015260 Brunswick GABrunswick GABrunswick GABrunswick GA ‐‐‐3.83.83.8 888888 no changeno changeno change upupup

153801538015380 Buffalo NYBuffalo NYBuffalo NYBuffalo NY ‐‐‐3.33.33.3 858585 no changeno changeno change upupup

155001550015500 Burlington NCBurlington NCBurlington NCBurlington NC ‐‐‐3.43.43.4 858585 upupup upupup

155401554015540 Burlington VTBurlington VTBurlington VTBurlington VT ‐‐‐4.94.94.9 939393 no changeno changeno change no changeno changeno change



157641576415764 Cambridge MA [Metropolitan Division]Cambridge MA [Metropolitan Division]Cambridge MA [Metropolitan Division]Cambridge MA [Metropolitan Division] ‐‐‐8.48.48.4 999999 no changeno changeno change no changeno changeno change

158041580415804 Camden NJ [Metropolitan Division]Camden NJ [Metropolitan Division]Camden NJ [Metropolitan Division]Camden NJ [Metropolitan Division] ‐‐‐3.33.33.3 848484 no changeno changeno change upupup

159401594015940 Canton OHCanton OHCanton OHCanton OH ‐‐‐3.83.83.8 888888 upupup upupup

159801598015980 Cape Coral FLCape Coral FLCape Coral FLCape Coral FL ‐‐‐4.74.74.7 929292 upupup upupup

160201602016020 Cape Girardeau MOCape Girardeau MOCape Girardeau MOCape Girardeau MO ‐‐‐8.38.38.3 999999 no changeno changeno change no changeno changeno change

161801618016180 Carson City NVCarson City NVCarson City NVCarson City NV ‐‐‐9.99.99.9 100100100 no changeno changeno change no changeno changeno change

162201622016220 Casper WYCasper WYCasper WYCasper WY ‐‐‐2.32.32.3 767676 no changeno changeno change upupup

163001630016300 Cedar Rapids IACedar Rapids IACedar Rapids IACedar Rapids IA ‐‐‐2.92.92.9 818181 no changeno changeno change downdowndown

165801658016580 Champaign ILChampaign ILChampaign ILChampaign IL ‐‐‐5.35.35.3 949494 no changeno changeno change upupup

167001670016700 Charleston SCCharleston SCCharleston SCCharleston SC ‐‐‐2.72.72.7 808080 no changeno changeno change upupup

166201662016620 Charleston WVCharleston WVCharleston WVCharleston WV ‐‐‐7.27.27.2 989898 no changeno changeno change no changeno changeno change

167401674016740 Charlotte NCCharlotte NCCharlotte NCCharlotte NC ‐‐‐3.33.33.3 858585 no changeno changeno change upupup

168201682016820 Charlottesville VACharlottesville VACharlottesville VACharlottesville VA ‐‐‐3.73.73.7 878787 no changeno changeno change upupup

168601686016860 Chattanooga TNChattanooga TNChattanooga TNChattanooga TN ‐‐‐4.84.84.8 939393 no changeno changeno change upupup

169401694016940 Cheyenne WYCheyenne WYCheyenne WYCheyenne WY ‐‐‐7.37.37.3 989898 no changeno changeno change no changeno changeno change

169741697416974 Chicago IL [Metropolitan Division]Chicago IL [Metropolitan Division]Chicago IL [Metropolitan Division]Chicago IL [Metropolitan Division] ‐‐‐8.08.08.0 999999 no changeno changeno change upupup

170201702017020 Chico CAChico CAChico CAChico CA ‐‐‐4.04.04.0 898989 upupup upupup

171401714017140 Cincinnati OHCincinnati OHCincinnati OHCincinnati OH ‐‐‐3.63.63.6 868686 upupup upupup

173001730017300 Clarksville TNClarksville TNClarksville TNClarksville TN ‐‐‐4.84.84.8 929292 no changeno changeno change upupup

174601746017460 Cleveland OHCleveland OHCleveland OHCleveland OH ‐‐‐5.25.25.2 949494 no changeno changeno change upupup

174201742017420 Cleveland TNCleveland TNCleveland TNCleveland TN ‐‐‐2.12.12.1 747474 upupup upupup

176601766017660 Coeur d'Alene IDCoeur d'Alene IDCoeur d'Alene IDCoeur d'Alene ID ‐‐‐1.81.81.8 717171 upupup upupup

177801778017780 College Station TXCollege Station TXCollege Station TXCollege Station TX ‐‐‐4.44.44.4 919191 no changeno changeno change no changeno changeno change

178201782017820 Colorado Springs COColorado Springs COColorado Springs COColorado Springs CO ‐‐‐7.17.17.1 989898 no changeno changeno change no changeno changeno change

178601786017860 Columbia MOColumbia MOColumbia MOColumbia MO ‐‐‐3.83.83.8 888888 no changeno changeno change upupup

179001790017900 Columbia SCColumbia SCColumbia SCColumbia SC ‐‐‐3.03.03.0 828282 no changeno changeno change upupup

179801798017980 Columbus GAColumbus GAColumbus GAColumbus GA ‐‐‐5.55.55.5 959595 no changeno changeno change upupup

180201802018020 Columbus INColumbus INColumbus INColumbus IN ‐‐‐4.64.64.6 919191 no changeno changeno change upupup

181401814018140 Columbus OHColumbus OHColumbus OHColumbus OH ‐‐‐6.46.46.4 979797 no changeno changeno change no changeno changeno change

185801858018580 Corpus Christi TXCorpus Christi TXCorpus Christi TXCorpus Christi TX ‐‐‐5.15.15.1 949494 no changeno changeno change upupup

187001870018700 Corvallis ORCorvallis ORCorvallis ORCorvallis OR ‐‐‐8.78.78.7 999999 no changeno changeno change no changeno changeno change

188801888018880 Crestview FLCrestview FLCrestview FLCrestview FL ‐‐‐4.34.34.3 909090 upupup upupup

190601906019060 Cumberland MDCumberland MDCumberland MDCumberland MD ‐‐‐5.95.95.9 969696 no changeno changeno change upupup

191241912419124 Dallas TX [Metropolitan Division]Dallas TX [Metropolitan Division]Dallas TX [Metropolitan Division]Dallas TX [Metropolitan Division] ‐‐‐4.24.24.2 909090 no changeno changeno change upupup

191401914019140 Dalton GADalton GADalton GADalton GA ‐‐‐7.57.57.5 999999 no changeno changeno change upupup

191801918019180 Danville ILDanville ILDanville ILDanville IL ‐‐‐9.49.49.4 100100100 no changeno changeno change upupup

192601926019260 Danville VADanville VADanville VADanville VA ‐‐‐5.85.85.8 969696 no changeno changeno change upupup

193401934019340 Davenport ILDavenport ILDavenport ILDavenport IL ‐‐‐7.37.37.3 989898 no changeno changeno change no changeno changeno change

193801938019380 Dayton OHDayton OHDayton OHDayton OH ‐‐‐5.25.25.2 949494 no changeno changeno change upupup

194601946019460 Decatur ALDecatur ALDecatur ALDecatur AL ‐‐‐6.36.36.3 979797 no changeno changeno change upupup

195001950019500 Decatur ILDecatur ILDecatur ILDecatur IL ‐‐‐5.55.55.5 959595 no changeno changeno change upupup

196601966019660 Deltona FLDeltona FLDeltona FLDeltona FL ‐‐‐4.24.24.2 909090 upupup upupup

197401974019740 Denver CODenver CODenver CODenver CO ‐‐‐8.48.48.4 999999 no changeno changeno change no changeno changeno change

197801978019780 Des Moines IADes Moines IADes Moines IADes Moines IA ‐‐‐3.23.23.2 838383 no changeno changeno change no changeno changeno change

198041980419804 Detroit MI [Metropolitan Division]Detroit MI [Metropolitan Division]Detroit MI [Metropolitan Division]Detroit MI [Metropolitan Division] 23.223.223.2 333 no changeno changeno change no changeno changeno change

200202002020020 Dothan ALDothan ALDothan ALDothan AL ‐‐‐5.25.25.2 949494 no changeno changeno change no changeno changeno change

201002010020100 Dover DEDover DEDover DEDover DE ‐‐‐2.42.42.4 777777 no changeno changeno change upupup

202202022020220 Dubuque IADubuque IADubuque IADubuque IA ‐‐‐3.23.23.2 838383 no changeno changeno change no changeno changeno change

202602026020260 Duluth MNDuluth MNDuluth MNDuluth MN ‐‐‐6.06.06.0 969696 no changeno changeno change upupup

205002050020500 Durham NCDurham NCDurham NCDurham NC ‐‐‐4.04.04.0 898989 no changeno changeno change upupup

207402074020740 Eau Claire WIEau Claire WIEau Claire WIEau Claire WI ‐‐‐5.05.05.0 939393 no changeno changeno change no changeno changeno change

207642076420764 Edison NJ [Metropolitan Division]Edison NJ [Metropolitan Division]Edison NJ [Metropolitan Division]Edison NJ [Metropolitan Division] ‐‐‐5.25.25.2 949494 no changeno changeno change upupup

209402094020940 El Centro CAEl Centro CAEl Centro CAEl Centro CA ‐‐‐6.96.96.9 989898 no changeno changeno change upupup

213402134021340 El Paso TXEl Paso TXEl Paso TXEl Paso TX ‐‐‐4.74.74.7 929292 no changeno changeno change no changeno changeno change

210602106021060 Elizabethtown KYElizabethtown KYElizabethtown KYElizabethtown KY ‐‐‐5.15.15.1 949494 no changeno changeno change no changeno changeno change

211402114021140 Elkhart INElkhart INElkhart INElkhart IN ‐‐‐0.90.90.9 616161 upupup upupup

213002130021300 Elmira NYElmira NYElmira NYElmira NY ‐‐‐7.97.97.9 999999 no changeno changeno change no changeno changeno change

215002150021500 Erie PAErie PAErie PAErie PA ‐‐‐6.06.06.0 969696 no changeno changeno change no changeno changeno change

216602166021660 Eugene OREugene OREugene OREugene OR ‐‐‐7.57.57.5 999999 no changeno changeno change no changeno changeno change

217802178021780 Evansville INEvansville INEvansville INEvansville IN ‐‐‐5.35.35.3 959595 no changeno changeno change upupup

218202182021820 Fairbanks AKFairbanks AKFairbanks AKFairbanks AK ‐‐‐10.210.210.2 100100100 no changeno changeno change no changeno changeno change



220202202022020 Fargo NDFargo NDFargo NDFargo ND ‐‐‐3.93.93.9 888888 no changeno changeno change no changeno changeno change

221402214022140 Farmington NMFarmington NMFarmington NMFarmington NM ‐‐‐7.07.07.0 989898 no changeno changeno change no changeno changeno change

222202222022220 Fayetteville ARFayetteville ARFayetteville ARFayetteville AR ‐‐‐5.25.25.2 949494 no changeno changeno change upupup

221802218022180 Fayetteville NCFayetteville NCFayetteville NCFayetteville NC ‐‐‐4.44.44.4 919191 no changeno changeno change upupup

223802238022380 Flagstaff AZFlagstaff AZFlagstaff AZFlagstaff AZ ‐‐‐8.28.28.2 999999 no changeno changeno change no changeno changeno change

224202242022420 Flint MIFlint MIFlint MIFlint MI 9.49.49.4 777 no changeno changeno change no changeno changeno change

225202252022520 Florence ALFlorence ALFlorence ALFlorence AL ‐‐‐4.34.34.3 909090 no changeno changeno change upupup

225002250022500 Florence SCFlorence SCFlorence SCFlorence SC ‐‐‐5.15.15.1 949494 no changeno changeno change upupup

225402254022540 Fond du Lac WIFond du Lac WIFond du Lac WIFond du Lac WI ‐‐‐6.06.06.0 969696 no changeno changeno change no changeno changeno change

226602266022660 Fort Collins COFort Collins COFort Collins COFort Collins CO ‐‐‐8.18.18.1 999999 no changeno changeno change no changeno changeno change

227442274422744 Fort Lauderdale FL [Metropolitan Division]Fort Lauderdale FL [Metropolitan Division]Fort Lauderdale FL [Metropolitan Division]Fort Lauderdale FL [Metropolitan Division] ‐‐‐8.88.88.8 100100100 no changeno changeno change upupup

229002290022900 Fort Smith ARFort Smith ARFort Smith ARFort Smith AR ‐‐‐4.74.74.7 929292 no changeno changeno change upupup

230602306023060 Fort Wayne INFort Wayne INFort Wayne INFort Wayne IN ‐‐‐4.74.74.7 929292 no changeno changeno change upupup

231042310423104 Fort Worth TX [Metropolitan Division]Fort Worth TX [Metropolitan Division]Fort Worth TX [Metropolitan Division]Fort Worth TX [Metropolitan Division] ‐‐‐5.15.15.1 949494 no changeno changeno change upupup

234202342023420 Fresno CAFresno CAFresno CAFresno CA ‐‐‐3.73.73.7 878787 upupup upupup

234602346023460 Gadsden ALGadsden ALGadsden ALGadsden AL ‐‐‐3.13.13.1 838383 upupup upupup

235402354023540 Gainesville FLGainesville FLGainesville FLGainesville FL ‐‐‐4.94.94.9 939393 no changeno changeno change upupup

235802358023580 Gainesville GAGainesville GAGainesville GAGainesville GA ‐‐‐4.24.24.2 909090 no changeno changeno change upupup

238442384423844 Gary IN [Metropolitan Division]Gary IN [Metropolitan Division]Gary IN [Metropolitan Division]Gary IN [Metropolitan Division] ‐‐‐4.04.04.0 888888 upupup upupup

240202402024020 Glens Falls NYGlens Falls NYGlens Falls NYGlens Falls NY ‐‐‐2.42.42.4 777777 upupup upupup

241402414024140 Goldsboro NCGoldsboro NCGoldsboro NCGoldsboro NC ‐‐‐6.76.76.7 989898 no changeno changeno change no changeno changeno change

242202422024220 Grand Forks NDGrand Forks NDGrand Forks NDGrand Forks ND ‐‐‐5.55.55.5 959595 no changeno changeno change no changeno changeno change

243002430024300 Grand Junction COGrand Junction COGrand Junction COGrand Junction CO ‐‐‐3.43.43.4 858585 no changeno changeno change upupup

243402434024340 Grand Rapids MIGrand Rapids MIGrand Rapids MIGrand Rapids MI ‐‐‐2.92.92.9 818181 upupup upupup

245002450024500 Great Falls MTGreat Falls MTGreat Falls MTGreat Falls MT ‐‐‐4.44.44.4 919191 upupup upupup

245402454024540 Greeley COGreeley COGreeley COGreeley CO ‐‐‐4.74.74.7 929292 no changeno changeno change upupup

245802458024580 Green Bay WIGreen Bay WIGreen Bay WIGreen Bay WI ‐‐‐4.24.24.2 909090 no changeno changeno change upupup

246602466024660 Greensboro NCGreensboro NCGreensboro NCGreensboro NC ‐‐‐5.05.05.0 949494 no changeno changeno change upupup

247802478024780 Greenville NCGreenville NCGreenville NCGreenville NC ‐‐‐4.94.94.9 939393 no changeno changeno change upupup

248602486024860 Greenville SCGreenville SCGreenville SCGreenville SC ‐‐‐2.22.22.2 757575 upupup upupup

250602506025060 Gulfport MSGulfport MSGulfport MSGulfport MS 1.91.91.9 303030 upupup upupup

251802518025180 Hagerstown MDHagerstown MDHagerstown MDHagerstown MD ‐‐‐0.30.30.3 535353 upupup upupup

252602526025260 Hanford CAHanford CAHanford CAHanford CA ‐‐‐3.43.43.4 858585 upupup upupup

254202542025420 Harrisburg PAHarrisburg PAHarrisburg PAHarrisburg PA ‐‐‐3.83.83.8 878787 no changeno changeno change no changeno changeno change

255002550025500 Harrisonburg VAHarrisonburg VAHarrisonburg VAHarrisonburg VA ‐‐‐1.21.21.2 646464 upupup upupup

255402554025540 Hartford CTHartford CTHartford CTHartford CT ‐‐‐5.45.45.4 959595 no changeno changeno change upupup

256202562025620 Hattiesburg MSHattiesburg MSHattiesburg MSHattiesburg MS ‐‐‐8.68.68.6 999999 no changeno changeno change no changeno changeno change

258602586025860 Hickory NCHickory NCHickory NCHickory NC ‐‐‐5.05.05.0 939393 no changeno changeno change upupup

259802598025980 Hinesville GAHinesville GAHinesville GAHinesville GA ‐‐‐5.05.05.0 939393 no changeno changeno change upupup

261002610026100 Holland MIHolland MIHolland MIHolland MI ‐‐‐4.54.54.5 919191 no changeno changeno change no changeno changeno change

261802618026180 Honolulu HIHonolulu HIHonolulu HIHonolulu HI ‐‐‐6.36.36.3 979797 no changeno changeno change upupup

263002630026300 Hot Springs ARHot Springs ARHot Springs ARHot Springs AR ‐‐‐7.47.47.4 999999 no changeno changeno change no changeno changeno change

263802638026380 Houma LAHouma LAHouma LAHouma LA ‐‐‐0.70.70.7 575757 no changeno changeno change upupup

264202642026420 Houston TXHouston TXHouston TXHouston TX ‐‐‐3.43.43.4 858585 no changeno changeno change upupup

265802658026580 Huntington WVHuntington WVHuntington WVHuntington WV ‐‐‐8.28.28.2 999999 no changeno changeno change no changeno changeno change

266202662026620 Huntsville ALHuntsville ALHuntsville ALHuntsville AL ‐‐‐1.71.71.7 707070 no changeno changeno change upupup

268202682026820 Idaho Falls IDIdaho Falls IDIdaho Falls IDIdaho Falls ID ‐‐‐4.54.54.5 919191 no changeno changeno change upupup

269002690026900 Indianapolis INIndianapolis INIndianapolis INIndianapolis IN ‐‐‐4.74.74.7 929292 no changeno changeno change upupup

269802698026980 Iowa City IAIowa City IAIowa City IAIowa City IA ‐‐‐1.91.91.9 727272 no changeno changeno change downdowndown

270602706027060 Ithaca NYIthaca NYIthaca NYIthaca NY ‐‐‐5.25.25.2 949494 no changeno changeno change no changeno changeno change

271002710027100 Jackson MIJackson MIJackson MIJackson MI ‐‐‐7.37.37.3 989898 no changeno changeno change upupup

271402714027140 Jackson MSJackson MSJackson MSJackson MS ‐‐‐2.42.42.4 777777 upupup upupup

271802718027180 Jackson TNJackson TNJackson TNJackson TN ‐‐‐3.63.63.6 868686 upupup upupup

272602726027260 Jacksonville FLJacksonville FLJacksonville FLJacksonville FL ‐‐‐3.63.63.6 868686 upupup upupup

273402734027340 Jacksonville NCJacksonville NCJacksonville NCJacksonville NC ‐‐‐1.91.91.9 717171 no changeno changeno change downdowndown

275002750027500 Janesville WIJanesville WIJanesville WIJanesville WI ‐‐‐0.70.70.7 595959 upupup upupup

276202762027620 Jefferson City MOJefferson City MOJefferson City MOJefferson City MO ‐‐‐7.37.37.3 989898 no changeno changeno change no changeno changeno change

277402774027740 Johnson City TNJohnson City TNJohnson City TNJohnson City TN ‐‐‐3.83.83.8 888888 no changeno changeno change upupup

277802778027780 Johnstown PAJohnstown PAJohnstown PAJohnstown PA ‐‐‐4.64.64.6 929292 no changeno changeno change upupup

278602786027860 Jonesboro ARJonesboro ARJonesboro ARJonesboro AR ‐‐‐1.31.31.3 666666 no changeno changeno change no changeno changeno change

279002790027900 Joplin MOJoplin MOJoplin MOJoplin MO ‐‐‐7.67.67.6 999999 no changeno changeno change no changeno changeno change



280202802028020 Kalamazoo MIKalamazoo MIKalamazoo MIKalamazoo MI ‐‐‐6.06.06.0 969696 no changeno changeno change no changeno changeno change

281002810028100 Kankakee ILKankakee ILKankakee ILKankakee IL ‐‐‐3.53.53.5 858585 upupup upupup

281402814028140 Kansas City MOKansas City MOKansas City MOKansas City MO ‐‐‐7.37.37.3 989898 no changeno changeno change no changeno changeno change

284202842028420 Kennewick WAKennewick WAKennewick WAKennewick WA ‐‐‐4.34.34.3 909090 no changeno changeno change no changeno changeno change

286602866028660 Killeen TXKilleen TXKilleen TXKilleen TX ‐‐‐3.63.63.6 868686 no changeno changeno change no changeno changeno change

287002870028700 Kingsport TNKingsport TNKingsport TNKingsport TN ‐‐‐4.84.84.8 939393 upupup upupup

287402874028740 Kingston NYKingston NYKingston NYKingston NY ‐‐‐0.30.30.3 545454 upupup upupup

289402894028940 Knoxville TNKnoxville TNKnoxville TNKnoxville TN ‐‐‐2.62.62.6 797979 upupup upupup

290202902029020 Kokomo INKokomo INKokomo INKokomo IN ‐‐‐6.76.76.7 989898 upupup upupup

291002910029100 La Crosse WILa Crosse WILa Crosse WILa Crosse WI ‐‐‐4.34.34.3 909090 no changeno changeno change no changeno changeno change

291402914029140 Lafayette INLafayette INLafayette INLafayette IN ‐‐‐4.74.74.7 929292 no changeno changeno change no changeno changeno change

291802918029180 Lafayette LALafayette LALafayette LALafayette LA ‐‐‐3.93.93.9 888888 no changeno changeno change upupup

293402934029340 Lake Charles LALake Charles LALake Charles LALake Charles LA ‐‐‐0.40.40.4 555555 no changeno changeno change downdowndown

294042940429404 Lake County IL [Metropolitan Division]Lake County IL [Metropolitan Division]Lake County IL [Metropolitan Division]Lake County IL [Metropolitan Division] ‐‐‐7.27.27.2 989898 no changeno changeno change upupup

294202942029420 Lake Havasu AZLake Havasu AZLake Havasu AZLake Havasu AZ ‐‐‐7.07.07.0 989898 no changeno changeno change upupup

294602946029460 Lakeland FLLakeland FLLakeland FLLakeland FL 0.10.10.1 494949 upupup upupup

295402954029540 Lancaster PALancaster PALancaster PALancaster PA ‐‐‐4.74.74.7 929292 no changeno changeno change no changeno changeno change

296202962029620 Lansing MILansing MILansing MILansing MI ‐‐‐7.17.17.1 989898 no changeno changeno change no changeno changeno change

297002970029700 Laredo TXLaredo TXLaredo TXLaredo TX ‐‐‐5.25.25.2 949494 no changeno changeno change upupup

297402974029740 Las Cruces NMLas Cruces NMLas Cruces NMLas Cruces NM ‐‐‐4.24.24.2 909090 no changeno changeno change upupup

298202982029820 Las Vegas NVLas Vegas NVLas Vegas NVLas Vegas NV ‐‐‐0.80.80.8 595959 upupup upupup

299402994029940 Lawrence KSLawrence KSLawrence KSLawrence KS ‐‐‐5.15.15.1 949494 no changeno changeno change upupup

300203002030020 Lawton OKLawton OKLawton OKLawton OK ‐‐‐8.28.28.2 999999 no changeno changeno change no changeno changeno change

301403014030140 Lebanon PALebanon PALebanon PALebanon PA ‐‐‐3.03.03.0 828282 no changeno changeno change no changeno changeno change

303003030030300 Lewiston IDLewiston IDLewiston IDLewiston ID ‐‐‐7.27.27.2 989898 no changeno changeno change no changeno changeno change

303403034030340 Lewiston MELewiston MELewiston MELewiston ME 6.06.06.0 111111 no changeno changeno change downdowndown

304603046030460 Lexington KYLexington KYLexington KYLexington KY ‐‐‐2.52.52.5 787878 no changeno changeno change upupup

306203062030620 Lima OHLima OHLima OHLima OH ‐‐‐4.24.24.2 909090 upupup upupup

307003070030700 Lincoln NELincoln NELincoln NELincoln NE ‐‐‐4.84.84.8 929292 no changeno changeno change no changeno changeno change

307803078030780 Little Rock ARLittle Rock ARLittle Rock ARLittle Rock AR ‐‐‐4.24.24.2 909090 no changeno changeno change no changeno changeno change

308603086030860 Logan UTLogan UTLogan UTLogan UT ‐‐‐4.24.24.2 909090 no changeno changeno change upupup

309803098030980 Longview TXLongview TXLongview TXLongview TX ‐‐‐8.18.18.1 999999 no changeno changeno change no changeno changeno change

310203102031020 Longview WALongview WALongview WALongview WA ‐‐‐4.04.04.0 898989 upupup upupup

310843108431084 Los Angeles CA [Metropolitan Division]Los Angeles CA [Metropolitan Division]Los Angeles CA [Metropolitan Division]Los Angeles CA [Metropolitan Division] ‐‐‐9.79.79.7 100100100 no changeno changeno change no changeno changeno change

311403114031140 Louisville KYLouisville KYLouisville KYLouisville KY ‐‐‐5.15.15.1 949494 no changeno changeno change no changeno changeno change

311803118031180 Lubbock TXLubbock TXLubbock TXLubbock TX ‐‐‐6.06.06.0 969696 no changeno changeno change no changeno changeno change

313403134031340 Lynchburg VALynchburg VALynchburg VALynchburg VA ‐‐‐3.03.03.0 828282 upupup upupup

314203142031420 Macon GAMacon GAMacon GAMacon GA ‐‐‐2.82.82.8 818181 upupup upupup

314603146031460 Madera CAMadera CAMadera CAMadera CA ‐‐‐6.66.66.6 979797 no changeno changeno change upupup

315403154031540 Madison WIMadison WIMadison WIMadison WI ‐‐‐6.36.36.3 979797 no changeno changeno change no changeno changeno change

317003170031700 Manchester NHManchester NHManchester NHManchester NH ‐‐‐5.75.75.7 969696 no changeno changeno change upupup

317403174031740 Manhattan KSManhattan KSManhattan KSManhattan KS ‐‐‐3.93.93.9 888888 no changeno changeno change no changeno changeno change

318603186031860 Mankato MNMankato MNMankato MNMankato MN ‐‐‐5.55.55.5 959595 no changeno changeno change no changeno changeno change

319003190031900 Mansfield OHMansfield OHMansfield OHMansfield OH 0.80.80.8 414141 upupup upupup

325803258032580 McAllen TXMcAllen TXMcAllen TXMcAllen TX ‐‐‐4.04.04.0 898989 no changeno changeno change no changeno changeno change

327803278032780 Medford ORMedford ORMedford ORMedford OR ‐‐‐7.17.17.1 989898 no changeno changeno change upupup

328203282032820 Memphis TNMemphis TNMemphis TNMemphis TN ‐‐‐5.45.45.4 959595 no changeno changeno change upupup

329003290032900 Merced CAMerced CAMerced CAMerced CA ‐‐‐7.97.97.9 999999 no changeno changeno change upupup

331243312433124 Miami FL [Metropolitan Division]Miami FL [Metropolitan Division]Miami FL [Metropolitan Division]Miami FL [Metropolitan Division] ‐‐‐10.010.010.0 100100100 no changeno changeno change no changeno changeno change

331403314033140 Michigan City INMichigan City INMichigan City INMichigan City IN ‐‐‐4.84.84.8 929292 no changeno changeno change upupup

332603326033260 Midland TXMidland TXMidland TXMidland TX ‐‐‐4.94.94.9 939393 no changeno changeno change no changeno changeno change

333403334033340 Milwaukee WIMilwaukee WIMilwaukee WIMilwaukee WI ‐‐‐7.57.57.5 999999 no changeno changeno change no changeno changeno change

334603346033460 Minneapolis MNMinneapolis MNMinneapolis MNMinneapolis MN ‐‐‐8.28.28.2 999999 no changeno changeno change no changeno changeno change

335403354033540 Missoula MTMissoula MTMissoula MTMissoula MT ‐‐‐5.75.75.7 969696 no changeno changeno change no changeno changeno change

336603366033660 Mobile ALMobile ALMobile ALMobile AL 0.70.70.7 424242 upupup upupup

337003370033700 Modesto CAModesto CAModesto CAModesto CA ‐‐‐8.08.08.0 999999 no changeno changeno change upupup

337403374033740 Monroe LAMonroe LAMonroe LAMonroe LA ‐‐‐5.55.55.5 959595 no changeno changeno change upupup

337803378033780 Monroe MIMonroe MIMonroe MIMonroe MI ‐‐‐5.05.05.0 939393 no changeno changeno change upupup

338603386033860 Montgomery ALMontgomery ALMontgomery ALMontgomery AL ‐‐‐5.65.65.6 959595 no changeno changeno change upupup

340603406034060 Morgantown WVMorgantown WVMorgantown WVMorgantown WV ‐‐‐10.510.510.5 100100100 no changeno changeno change no changeno changeno change

341003410034100 Morristown TNMorristown TNMorristown TNMorristown TN ‐‐‐3.53.53.5 868686 upupup upupup



345803458034580 Mount Vernon WAMount Vernon WAMount Vernon WAMount Vernon WA ‐‐‐4.04.04.0 898989 no changeno changeno change upupup

346203462034620 Muncie INMuncie INMuncie INMuncie IN ‐‐‐9.39.39.3 100100100 no changeno changeno change no changeno changeno change

347403474034740 Muskegon MIMuskegon MIMuskegon MIMuskegon MI 3.43.43.4 202020 upupup downdowndown

348203482034820 Myrtle Beach SCMyrtle Beach SCMyrtle Beach SCMyrtle Beach SC ‐‐‐1.21.21.2 656565 upupup upupup

349003490034900 Napa CANapa CANapa CANapa CA ‐‐‐7.77.77.7 999999 no changeno changeno change no changeno changeno change

349403494034940 Naples FLNaples FLNaples FLNaples FL ‐‐‐4.54.54.5 919191 upupup upupup

349803498034980 Nashville TNNashville TNNashville TNNashville TN ‐‐‐3.53.53.5 868686 no changeno changeno change upupup

350043500435004 Nassau NY [Metropolitan Division]Nassau NY [Metropolitan Division]Nassau NY [Metropolitan Division]Nassau NY [Metropolitan Division] ‐‐‐7.77.77.7 999999 no changeno changeno change upupup

353003530035300 New Haven CTNew Haven CTNew Haven CTNew Haven CT ‐‐‐7.17.17.1 989898 no changeno changeno change no changeno changeno change

353803538035380 New Orleans LANew Orleans LANew Orleans LANew Orleans LA ‐‐‐6.26.26.2 979797 no changeno changeno change no changeno changeno change

356443564435644 New York NY [Metropolitan Division]New York NY [Metropolitan Division]New York NY [Metropolitan Division]New York NY [Metropolitan Division] ‐‐‐7.97.97.9 999999 no changeno changeno change no changeno changeno change

350843508435084 Newark NJ [Metropolitan Division]Newark NJ [Metropolitan Division]Newark NJ [Metropolitan Division]Newark NJ [Metropolitan Division] ‐‐‐6.46.46.4 979797 no changeno changeno change upupup

356603566035660 Niles MINiles MINiles MINiles MI ‐‐‐2.52.52.5 787878 upupup upupup

358403584035840 North Port FLNorth Port FLNorth Port FLNorth Port FL ‐‐‐4.54.54.5 919191 upupup upupup

359803598035980 Norwich CTNorwich CTNorwich CTNorwich CT ‐‐‐5.15.15.1 949494 no changeno changeno change upupup

360843608436084 Oakland CA [Metropolitan Division]Oakland CA [Metropolitan Division]Oakland CA [Metropolitan Division]Oakland CA [Metropolitan Division] ‐‐‐9.09.09.0 100100100 no changeno changeno change no changeno changeno change

361003610036100 Ocala FLOcala FLOcala FLOcala FL ‐‐‐1.81.81.8 717171 upupup upupup

361403614036140 Ocean City NJOcean City NJOcean City NJOcean City NJ ‐‐‐3.73.73.7 878787 upupup upupup

362203622036220 Odessa TXOdessa TXOdessa TXOdessa TX ‐‐‐6.06.06.0 969696 no changeno changeno change no changeno changeno change

362603626036260 Ogden UTOgden UTOgden UTOgden UT ‐‐‐5.25.25.2 949494 no changeno changeno change no changeno changeno change

364203642036420 Oklahoma City OKOklahoma City OKOklahoma City OKOklahoma City OK ‐‐‐5.65.65.6 959595 no changeno changeno change no changeno changeno change

365003650036500 Olympia WAOlympia WAOlympia WAOlympia WA ‐‐‐2.82.82.8 808080 no changeno changeno change upupup

365403654036540 Omaha NEOmaha NEOmaha NEOmaha NE ‐‐‐3.53.53.5 868686 no changeno changeno change upupup

367403674036740 Orlando FLOrlando FLOrlando FLOrlando FL ‐‐‐5.15.15.1 949494 no changeno changeno change upupup

367803678036780 Oshkosh WIOshkosh WIOshkosh WIOshkosh WI ‐‐‐4.94.94.9 939393 no changeno changeno change no changeno changeno change

369803698036980 Owensboro KYOwensboro KYOwensboro KYOwensboro KY ‐‐‐2.52.52.5 787878 no changeno changeno change no changeno changeno change

371003710037100 Oxnard CAOxnard CAOxnard CAOxnard CA ‐‐‐10.510.510.5 100100100 no changeno changeno change no changeno changeno change

373403734037340 Palm Bay FLPalm Bay FLPalm Bay FLPalm Bay FL ‐‐‐3.93.93.9 888888 upupup upupup

373803738037380 Palm Coast FLPalm Coast FLPalm Coast FLPalm Coast FL ‐‐‐5.85.85.8 969696 no changeno changeno change no changeno changeno change

374603746037460 Panama City FLPanama City FLPanama City FLPanama City FL ‐‐‐8.08.08.0 999999 no changeno changeno change upupup

376203762037620 Parkersburg WVParkersburg WVParkersburg WVParkersburg WV ‐‐‐7.67.67.6 999999 no changeno changeno change no changeno changeno change

377003770037700 Pascagoula MSPascagoula MSPascagoula MSPascagoula MS ‐‐‐2.02.02.0 737373 upupup upupup

377643776437764 Peabody MAPeabody MAPeabody MAPeabody MA ‐‐‐9.19.19.1 100100100 no changeno changeno change no changeno changeno change

378603786037860 Pensacola FLPensacola FLPensacola FLPensacola FL ‐‐‐5.15.15.1 949494 no changeno changeno change upupup

379003790037900 Peoria ILPeoria ILPeoria ILPeoria IL ‐‐‐5.05.05.0 939393 no changeno changeno change upupup

379643796437964 Philadelphia PA [Metropolitan Division]Philadelphia PA [Metropolitan Division]Philadelphia PA [Metropolitan Division]Philadelphia PA [Metropolitan Division] ‐‐‐7.37.37.3 989898 no changeno changeno change no changeno changeno change

380603806038060 Phoenix AZPhoenix AZPhoenix AZPhoenix AZ ‐‐‐5.85.85.8 969696 no changeno changeno change upupup

382203822038220 Pine Bluff ARPine Bluff ARPine Bluff ARPine Bluff AR 0.40.40.4 464646 upupup upupup

383003830038300 Pittsburgh PAPittsburgh PAPittsburgh PAPittsburgh PA ‐‐‐5.65.65.6 959595 no changeno changeno change no changeno changeno change

383403834038340 Pittsfield MAPittsfield MAPittsfield MAPittsfield MA ‐‐‐6.26.26.2 979797 no changeno changeno change upupup

385403854038540 Pocatello IDPocatello IDPocatello IDPocatello ID ‐‐‐6.26.26.2 979797 no changeno changeno change no changeno changeno change

389403894038940 Port St. Lucie FLPort St. Lucie FLPort St. Lucie FLPort St. Lucie FL ‐‐‐6.06.06.0 969696 no changeno changeno change upupup

388603886038860 Portland MEPortland MEPortland MEPortland ME ‐‐‐0.60.60.6 575757 upupup upupup

389003890038900 Portland ORPortland ORPortland ORPortland OR ‐‐‐7.27.27.2 989898 no changeno changeno change no changeno changeno change

391003910039100 Poughkeepsie NYPoughkeepsie NYPoughkeepsie NYPoughkeepsie NY ‐‐‐3.13.13.1 838383 no changeno changeno change upupup

391403914039140 Prescott AZPrescott AZPrescott AZPrescott AZ ‐‐‐6.36.36.3 979797 no changeno changeno change upupup

393003930039300 Providence RIProvidence RIProvidence RIProvidence RI ‐‐‐6.36.36.3 979797 no changeno changeno change upupup

393403934039340 Provo UTProvo UTProvo UTProvo UT ‐‐‐3.93.93.9 888888 upupup upupup

393803938039380 Pueblo COPueblo COPueblo COPueblo CO ‐‐‐7.17.17.1 989898 no changeno changeno change upupup

394603946039460 Punta Gorda FLPunta Gorda FLPunta Gorda FLPunta Gorda FL ‐‐‐6.36.36.3 979797 upupup upupup

395403954039540 Racine WIRacine WIRacine WIRacine WI ‐‐‐3.13.13.1 838383 upupup upupup

395803958039580 Raleigh NCRaleigh NCRaleigh NCRaleigh NC ‐‐‐2.72.72.7 808080 no changeno changeno change upupup

396603966039660 Rapid City SDRapid City SDRapid City SDRapid City SD ‐‐‐5.25.25.2 949494 no changeno changeno change no changeno changeno change

397403974039740 Reading PAReading PAReading PAReading PA ‐‐‐4.94.94.9 939393 no changeno changeno change upupup

398203982039820 Redding CARedding CARedding CARedding CA ‐‐‐4.84.84.8 929292 upupup upupup

399003990039900 Reno NVReno NVReno NVReno NV ‐‐‐4.74.74.7 929292 no changeno changeno change upupup

400604006040060 Richmond VARichmond VARichmond VARichmond VA ‐‐‐4.54.54.5 919191 no changeno changeno change upupup

401404014040140 Riverside CARiverside CARiverside CARiverside CA ‐‐‐6.26.26.2 979797 no changeno changeno change upupup

402204022040220 Roanoke VARoanoke VARoanoke VARoanoke VA ‐‐‐5.45.45.4 959595 no changeno changeno change upupup

403404034040340 Rochester MNRochester MNRochester MNRochester MN ‐‐‐6.06.06.0 969696 no changeno changeno change no changeno changeno change

403804038040380 Rochester NYRochester NYRochester NYRochester NY ‐‐‐5.55.55.5 959595 no changeno changeno change no changeno changeno change



404204042040420 Rockford ILRockford ILRockford ILRockford IL ‐‐‐1.31.31.3 656565 upupup upupup

404844048440484 Rockingham County NH [Metropolitan Division]Rockingham County NH [Metropolitan Division]Rockingham County NH [Metropolitan Division]Rockingham County NH [Metropolitan Division] ‐‐‐3.73.73.7 878787 no changeno changeno change upupup

405804058040580 Rocky Mount NCRocky Mount NCRocky Mount NCRocky Mount NC ‐‐‐5.65.65.6 959595 no changeno changeno change upupup

406604066040660 Rome GARome GARome GARome GA ‐‐‐6.16.16.1 979797 no changeno changeno change upupup

409004090040900 Sacramento CASacramento CASacramento CASacramento CA ‐‐‐6.86.86.8 989898 no changeno changeno change upupup

409804098040980 Saginaw MISaginaw MISaginaw MISaginaw MI ‐‐‐0.80.80.8 595959 upupup upupup

414204142041420 Salem ORSalem ORSalem ORSalem OR ‐‐‐7.17.17.1 989898 no changeno changeno change upupup

415004150041500 Salinas CASalinas CASalinas CASalinas CA ‐‐‐9.79.79.7 100100100 no changeno changeno change no changeno changeno change

415404154041540 Salisbury MDSalisbury MDSalisbury MDSalisbury MD ‐‐‐4.94.94.9 939393 no changeno changeno change upupup

416204162041620 Salt Lake City UTSalt Lake City UTSalt Lake City UTSalt Lake City UT ‐‐‐6.66.66.6 979797 no changeno changeno change no changeno changeno change

416604166041660 San Angelo TXSan Angelo TXSan Angelo TXSan Angelo TX ‐‐‐6.76.76.7 989898 no changeno changeno change no changeno changeno change

417004170041700 San Antonio TXSan Antonio TXSan Antonio TXSan Antonio TX ‐‐‐6.66.66.6 979797 no changeno changeno change no changeno changeno change

417404174041740 San Diego CASan Diego CASan Diego CASan Diego CA ‐‐‐9.09.09.0 100100100 no changeno changeno change no changeno changeno change

418844188441884 San Francisco CA [Metropolitan Division]San Francisco CA [Metropolitan Division]San Francisco CA [Metropolitan Division]San Francisco CA [Metropolitan Division] ‐‐‐10.410.410.4 100100100 no changeno changeno change no changeno changeno change

419404194041940 San Jose CASan Jose CASan Jose CASan Jose CA ‐‐‐10.010.010.0 100100100 no changeno changeno change no changeno changeno change

420204202042020 San Luis Obispo CASan Luis Obispo CASan Luis Obispo CASan Luis Obispo CA ‐‐‐6.06.06.0 969696 no changeno changeno change upupup

417804178041780 Sandusky OHSandusky OHSandusky OHSandusky OH ‐‐‐7.57.57.5 999999 no changeno changeno change no changeno changeno change

420444204442044 Santa Ana CA [Metropolitan Division]Santa Ana CA [Metropolitan Division]Santa Ana CA [Metropolitan Division]Santa Ana CA [Metropolitan Division] ‐‐‐9.69.69.6 100100100 no changeno changeno change no changeno changeno change

420604206042060 Santa Barbara CASanta Barbara CASanta Barbara CASanta Barbara CA ‐‐‐9.39.39.3 100100100 no changeno changeno change no changeno changeno change

421004210042100 Santa Cruz CASanta Cruz CASanta Cruz CASanta Cruz CA ‐‐‐9.79.79.7 100100100 no changeno changeno change no changeno changeno change

421404214042140 Santa Fe NMSanta Fe NMSanta Fe NMSanta Fe NM ‐‐‐9.99.99.9 100100100 no changeno changeno change no changeno changeno change

422204222042220 Santa Rosa CASanta Rosa CASanta Rosa CASanta Rosa CA ‐‐‐9.69.69.6 100100100 no changeno changeno change no changeno changeno change

423404234042340 Savannah GASavannah GASavannah GASavannah GA ‐‐‐4.14.14.1 898989 no changeno changeno change upupup

425404254042540 Scranton PAScranton PAScranton PAScranton PA ‐‐‐4.34.34.3 909090 no changeno changeno change upupup

426444264442644 Seattle WA [Metropolitan Division]Seattle WA [Metropolitan Division]Seattle WA [Metropolitan Division]Seattle WA [Metropolitan Division] ‐‐‐6.46.46.4 979797 no changeno changeno change no changeno changeno change

426804268042680 Sebastian FLSebastian FLSebastian FLSebastian FL ‐‐‐2.82.82.8 808080 upupup upupup

431004310043100 Sheboygan WISheboygan WISheboygan WISheboygan WI ‐‐‐5.65.65.6 959595 no changeno changeno change no changeno changeno change

433004330043300 Sherman TXSherman TXSherman TXSherman TX ‐‐‐8.48.48.4 999999 no changeno changeno change no changeno changeno change

433404334043340 Shreveport LAShreveport LAShreveport LAShreveport LA ‐‐‐4.44.44.4 919191 no changeno changeno change no changeno changeno change

435804358043580 Sioux City IASioux City IASioux City IASioux City IA ‐‐‐7.27.27.2 989898 no changeno changeno change no changeno changeno change

436204362043620 Sioux Falls SDSioux Falls SDSioux Falls SDSioux Falls SD ‐‐‐2.12.12.1 747474 no changeno changeno change upupup

437804378043780 South Bend INSouth Bend INSouth Bend INSouth Bend IN ‐‐‐4.64.64.6 929292 upupup upupup

439004390043900 Spartanburg SCSpartanburg SCSpartanburg SCSpartanburg SC ‐‐‐2.92.92.9 818181 no changeno changeno change upupup

440604406044060 Spokane WASpokane WASpokane WASpokane WA ‐‐‐5.25.25.2 949494 no changeno changeno change upupup

441004410044100 Springfield ILSpringfield ILSpringfield ILSpringfield IL ‐‐‐5.95.95.9 969696 no changeno changeno change no changeno changeno change

441404414044140 Springfield MASpringfield MASpringfield MASpringfield MA ‐‐‐5.85.85.8 969696 no changeno changeno change upupup

441804418044180 Springfield MOSpringfield MOSpringfield MOSpringfield MO ‐‐‐5.15.15.1 949494 no changeno changeno change upupup

442204422044220 Springfield OHSpringfield OHSpringfield OHSpringfield OH ‐‐‐3.43.43.4 858585 upupup upupup

410604106041060 St. Cloud MNSt. Cloud MNSt. Cloud MNSt. Cloud MN ‐‐‐5.85.85.8 969696 no changeno changeno change upupup

411004110041100 St. George UTSt. George UTSt. George UTSt. George UT ‐‐‐1.11.11.1 646464 upupup upupup

411404114041140 St. Joseph MOSt. Joseph MOSt. Joseph MOSt. Joseph MO ‐‐‐7.47.47.4 999999 no changeno changeno change no changeno changeno change

411804118041180 St. Louis MOSt. Louis MOSt. Louis MOSt. Louis MO ‐‐‐4.94.94.9 939393 no changeno changeno change upupup

443004430044300 State College PAState College PAState College PAState College PA ‐‐‐4.34.34.3 909090 no changeno changeno change no changeno changeno change

446004460044600 Steubenville OHSteubenville OHSteubenville OHSteubenville OH ‐‐‐9.39.39.3 100100100 no changeno changeno change no changeno changeno change

447004470044700 Stockton CAStockton CAStockton CAStockton CA ‐‐‐6.46.46.4 979797 no changeno changeno change upupup

449404494044940 Sumter SCSumter SCSumter SCSumter SC ‐‐‐3.33.33.3 848484 upupup upupup

450604506045060 Syracuse NYSyracuse NYSyracuse NYSyracuse NY ‐‐‐3.13.13.1 838383 no changeno changeno change no changeno changeno change

451044510445104 Tacoma WA [Metropolitan Division]Tacoma WA [Metropolitan Division]Tacoma WA [Metropolitan Division]Tacoma WA [Metropolitan Division] ‐‐‐3.33.33.3 848484 no changeno changeno change upupup

452204522045220 Tallahassee FLTallahassee FLTallahassee FLTallahassee FL ‐‐‐5.35.35.3 959595 no changeno changeno change upupup

453004530045300 Tampa FLTampa FLTampa FLTampa FL ‐‐‐5.65.65.6 959595 no changeno changeno change upupup

454604546045460 Terre Haute INTerre Haute INTerre Haute INTerre Haute IN ‐‐‐6.36.36.3 979797 no changeno changeno change upupup

455004550045500 Texarkana TXTexarkana TXTexarkana TXTexarkana TX ‐‐‐7.27.27.2 989898 no changeno changeno change no changeno changeno change

457804578045780 Toledo OHToledo OHToledo OHToledo OH ‐‐‐1.21.21.2 646464 upupup upupup

458204582045820 Topeka KSTopeka KSTopeka KSTopeka KS ‐‐‐6.46.46.4 979797 no changeno changeno change upupup

459404594045940 Trenton NJTrenton NJTrenton NJTrenton NJ ‐‐‐7.07.07.0 989898 no changeno changeno change no changeno changeno change

460604606046060 Tucson AZTucson AZTucson AZTucson AZ ‐‐‐5.75.75.7 969696 no changeno changeno change upupup

461404614046140 Tulsa OKTulsa OKTulsa OKTulsa OK ‐‐‐4.14.14.1 898989 no changeno changeno change upupup

462204622046220 Tuscaloosa ALTuscaloosa ALTuscaloosa ALTuscaloosa AL ‐‐‐3.43.43.4 858585 no changeno changeno change upupup

463404634046340 Tyler TXTyler TXTyler TXTyler TX ‐‐‐9.19.19.1 100100100 no changeno changeno change no changeno changeno change

465404654046540 Utica NYUtica NYUtica NYUtica NY ‐‐‐2.92.92.9 828282 no changeno changeno change upupup

466604666046660 Valdosta GAValdosta GAValdosta GAValdosta GA ‐‐‐3.33.33.3 848484 no changeno changeno change no changeno changeno change



Notes: Notes: Notes: Excess Supply equals supply less demand. Excess Supply equals supply less demand. Excess Supply equals supply less demand. SingleSingleSingle‐‐‐family housing supply is defined as the threefamily housing supply is defined as the threefamily housing supply is defined as the three‐‐‐year annual average of singleyear annual average of singleyear annual average of single‐‐‐family household completions. family household completions. family household completions. SingleSingleSingle‐‐‐family housing demand is defined as the threefamily housing demand is defined as the threefamily housing demand is defined as the three‐‐‐year annual average of singleyear annual average of singleyear annual average of single‐‐‐family household formations plus estimated family household formations plus estimated family household formations plus estimated obsolescence plus vacation and secondobsolescence plus vacation and secondobsolescence plus vacation and second‐‐‐home demand. home demand. home demand. Months of Excess Supply equals the level of excess supply divided by annual demand. Months of Excess Supply equals the level of excess supply divided by annual demand. Months of Excess Supply equals the level of excess supply divided by annual demand. Index of Excess Supply is a value from 0 to 100 indicating the current excess supply condition relative to conditions over the past 10 years in Index of Excess Supply is a value from 0 to 100 indicating the current excess supply condition relative to conditions over the past 10 years in Index of Excess Supply is a value from 0 to 100 indicating the current excess supply condition relative to conditions over the past 10 years in all metros.all metros.all metros. A value of 0 is extreme excess supply and a value of 100 is extreme excess demand. A value of 0 is extreme excess supply and a value of 100 is extreme excess demand. A value of 0 is extreme excess supply and a value of 100 is extreme excess demand. Trend of Excess Supply. Trend of Excess Supply. Trend of Excess Supply. "Up" means Index of Excess Supply has risen 5 or more points in the last four quarters. "Up" means Index of Excess Supply has risen 5 or more points in the last four quarters. "Up" means Index of Excess Supply has risen 5 or more points in the last four quarters. "Down" means Index of Excess Supply has fallen 5 or more points in the last four quarters. "Down" means Index of Excess Supply has fallen 5 or more points in the last four quarters. "Down" means Index of Excess Supply has fallen 5 or more points in the last four quarters. "No Change""No Change""No Change" otherwise. otherwise. otherwise.

467004670046700 Vallejo CAVallejo CAVallejo CAVallejo CA ‐‐‐8.18.18.1 999999 no changeno changeno change no changeno changeno change

470204702047020 Victoria TXVictoria TXVictoria TXVictoria TX ‐‐‐8.48.48.4 999999 no changeno changeno change no changeno changeno change

472204722047220 Vineland NJVineland NJVineland NJVineland NJ 2.12.12.1 282828 upupup upupup

472604726047260 Virginia Beach VAVirginia Beach VAVirginia Beach VAVirginia Beach VA ‐‐‐4.94.94.9 939393 no changeno changeno change upupup

473004730047300 Visalia CAVisalia CAVisalia CAVisalia CA ‐‐‐4.14.14.1 898989 no changeno changeno change upupup

473804738047380 Waco TXWaco TXWaco TXWaco TX ‐‐‐6.66.66.6 979797 no changeno changeno change upupup

475804758047580 Warner Robins GAWarner Robins GAWarner Robins GAWarner Robins GA ‐‐‐3.63.63.6 868686 no changeno changeno change upupup

476444764447644 Warren MI [Metropolitan Division]Warren MI [Metropolitan Division]Warren MI [Metropolitan Division]Warren MI [Metropolitan Division] ‐‐‐6.76.76.7 989898 no changeno changeno change no changeno changeno change

478944789447894 Washington DC [Metropolitan Division]Washington DC [Metropolitan Division]Washington DC [Metropolitan Division]Washington DC [Metropolitan Division] ‐‐‐7.47.47.4 999999 no changeno changeno change no changeno changeno change

479404794047940 Waterloo IAWaterloo IAWaterloo IAWaterloo IA ‐‐‐5.15.15.1 949494 no changeno changeno change no changeno changeno change

481404814048140 Wausau WIWausau WIWausau WIWausau WI ‐‐‐3.83.83.8 878787 no changeno changeno change no changeno changeno change

483004830048300 Wenatchee WAWenatchee WAWenatchee WAWenatchee WA ‐‐‐4.24.24.2 909090 no changeno changeno change upupup

484244842448424 West Palm Beach FL [Metropolitan Division]West Palm Beach FL [Metropolitan Division]West Palm Beach FL [Metropolitan Division]West Palm Beach FL [Metropolitan Division] ‐‐‐8.18.18.1 999999 no changeno changeno change upupup

485404854048540 Wheeling WVWheeling WVWheeling WVWheeling WV ‐‐‐10.110.110.1 100100100 no changeno changeno change no changeno changeno change

486604866048660 Wichita Falls TXWichita Falls TXWichita Falls TXWichita Falls TX ‐‐‐7.97.97.9 999999 no changeno changeno change upupup

486204862048620 Wichita KSWichita KSWichita KSWichita KS ‐‐‐5.25.25.2 949494 no changeno changeno change no changeno changeno change

487004870048700 Williamsport PAWilliamsport PAWilliamsport PAWilliamsport PA ‐‐‐5.05.05.0 939393 no changeno changeno change upupup

488644886448864 Wilmington DE [Metropolitan Division]Wilmington DE [Metropolitan Division]Wilmington DE [Metropolitan Division]Wilmington DE [Metropolitan Division] ‐‐‐5.25.25.2 949494 no changeno changeno change upupup

489004890048900 Wilmington NCWilmington NCWilmington NCWilmington NC ‐‐‐1.01.01.0 616161 upupup upupup

490204902049020 Winchester VAWinchester VAWinchester VAWinchester VA ‐‐‐4.14.14.1 898989 upupup upupup

491804918049180 Winston NCWinston NCWinston NCWinston NC ‐‐‐2.92.92.9 828282 upupup upupup

493404934049340 Worcester MAWorcester MAWorcester MAWorcester MA ‐‐‐5.05.05.0 939393 no changeno changeno change upupup

494204942049420 Yakima WAYakima WAYakima WAYakima WA ‐‐‐6.36.36.3 979797 no changeno changeno change no changeno changeno change

496204962049620 York PAYork PAYork PAYork PA ‐‐‐1.91.91.9 727272 no changeno changeno change upupup

496604966049660 Youngstown OHYoungstown OHYoungstown OHYoungstown OH ‐‐‐5.75.75.7 969696 upupup upupup

497004970049700 Yuba City CAYuba City CAYuba City CAYuba City CA ‐‐‐1.71.71.7 707070 upupup upupup

497404974049740 Yuma AZYuma AZYuma AZYuma AZ ‐‐‐4.34.34.3 909090 no changeno changeno change upupup



House Price Balance IndicatorHouse Price Balance Indicator Incorporating data through 2011Q2Incorporating data through 2011Q2Incorporating data through 2011Q2


Percent Over Equilibrium PricePercent Over Equilibrium PricePercent Over Equilibrium PricePercent Over Equilibrium Price

FIPFIPFIPFIP Metro AreaMetro AreaMetro AreaMetro Area Current QuarterCurrent QuarterCurrent QuarterCurrent Quarter Historical AverageHistorical AverageHistorical AverageHistorical Average Standard Standard Standard Standard DeviationDeviationDeviationDeviation

Balance Balance Balance Balance Ranking Ranking Ranking Ranking (1=most (1=most (1=most (1=most overpriced, overpriced, overpriced, overpriced, 384=most 384=most 384=most 384=most underpriced)underpriced)underpriced)underpriced)

Balance Current QuarterBalance Current QuarterBalance Current QuarterBalance Current Quarter

101801018010180 Abilene TXAbilene TXAbilene TXAbilene TX ‐‐‐3.63.63.6 ‐‐‐3.43.43.4 7.47.47.4 707070 0.00.00.0

104201042010420 Akron OHAkron OHAkron OHAkron OH ‐‐‐20.820.820.8 ‐‐‐2.52.52.5 6.36.36.3 373373373 ‐‐‐2.02.02.0

105001050010500 Albany GAAlbany GAAlbany GAAlbany GA ‐‐‐4.64.64.6 ‐‐‐0.60.60.6 7.77.77.7 109109109 0.00.00.0

105801058010580 Albany NYAlbany NYAlbany NYAlbany NY 9.39.39.3 5.75.75.7 12.912.912.9 262626 0.00.00.0

107401074010740 Albuquerque NMAlbuquerque NMAlbuquerque NMAlbuquerque NM ‐‐‐7.67.67.6 ‐‐‐1.81.81.8 7.37.37.3 115115115 0.00.00.0

107801078010780 Alexandria LAAlexandria LAAlexandria LAAlexandria LA ‐‐‐4.94.94.9 ‐‐‐4.34.34.3 6.16.16.1 666666 0.00.00.0

109001090010900 Allentown PAAllentown PAAllentown PAAllentown PA ‐‐‐17.617.617.6 ‐‐‐1.51.51.5 11.611.611.6 262262262 ‐‐‐2.02.02.0

110201102011020 Altoona PAAltoona PAAltoona PAAltoona PA 10.110.110.1 4.64.64.6 6.56.56.5 111111 1.01.01.0

111001110011100 Amarillo TXAmarillo TXAmarillo TXAmarillo TX 2.82.82.8 ‐‐‐1.51.51.5 7.57.57.5 212121 0.00.00.0

111801118011180 Ames IAAmes IAAmes IAAmes IA ‐‐‐8.18.18.1 ‐‐‐1.71.71.7 3.83.83.8 285285285 ‐‐‐2.02.02.0

112601126011260 Anchorage AKAnchorage AKAnchorage AKAnchorage AK ‐‐‐10.910.910.9 ‐‐‐4.04.04.0 6.66.66.6 183183183 ‐‐‐1.01.01.0

113001130011300 Anderson INAnderson INAnderson INAnderson IN ‐‐‐12.612.612.6 0.00.00.0 7.77.77.7 244244244 ‐‐‐1.01.01.0

113401134011340 Anderson SCAnderson SCAnderson SCAnderson SC ‐‐‐2.62.62.6 1.11.11.1 5.85.85.8 575757 0.00.00.0

114601146011460 Ann Arbor MIAnn Arbor MIAnn Arbor MIAnn Arbor MI ‐‐‐12.512.512.5 0.10.10.1 8.48.48.4 212212212 ‐‐‐1.01.01.0

115001150011500 Anniston ALAnniston ALAnniston ALAnniston AL ‐‐‐2.32.32.3 0.90.90.9 5.45.45.4 818181 0.00.00.0

115401154011540 Appleton WIAppleton WIAppleton WIAppleton WI ‐‐‐11.711.711.7 ‐‐‐3.23.23.2 4.14.14.1 224224224 ‐‐‐1.01.01.0

117001170011700 Asheville NCAsheville NCAsheville NCAsheville NC 14.114.114.1 3.73.73.7 14.414.414.4 888 1.01.01.0

120201202012020 Athens GAAthens GAAthens GAAthens GA 5.85.85.8 1.81.81.8 12.112.112.1 333333 0.00.00.0

120601206012060 Atlanta GAAtlanta GAAtlanta GAAtlanta GA ‐‐‐11.311.311.3 ‐‐‐0.30.30.3 8.38.38.3 234234234 ‐‐‐1.01.01.0

121001210012100 Atlantic City NJAtlantic City NJAtlantic City NJAtlantic City NJ ‐‐‐15.215.215.2 ‐‐‐1.51.51.5 14.214.214.2 148148148 ‐‐‐1.01.01.0

122201222012220 Auburn ALAuburn ALAuburn ALAuburn AL 1.51.51.5 ‐‐‐0.70.70.7 10.610.610.6 303030 0.00.00.0

122601226012260 Augusta GAAugusta GAAugusta GAAugusta GA ‐‐‐3.33.33.3 ‐‐‐0.90.90.9 6.76.76.7 656565 0.00.00.0

124201242012420 Austin TXAustin TXAustin TXAustin TX 16.016.016.0 ‐‐‐0.80.80.8 12.712.712.7 111 1.01.01.0

125401254012540 Bakersfield CABakersfield CABakersfield CABakersfield CA ‐‐‐61.361.361.3 ‐‐‐33.533.533.5 14.014.014.0 307307307 ‐‐‐2.02.02.0

125801258012580 Baltimore MDBaltimore MDBaltimore MDBaltimore MD ‐‐‐16.716.716.7 ‐‐‐1.61.61.6 9.19.19.1 269269269 ‐‐‐2.02.02.0

126201262012620 Bangor MEBangor MEBangor MEBangor ME ‐‐‐16.716.716.7 0.10.10.1 10.610.610.6 287287287 ‐‐‐2.02.02.0

127001270012700 Barnstable Town MABarnstable Town MABarnstable Town MABarnstable Town MA ‐‐‐23.123.123.1 0.20.20.2 17.217.217.2 343343343 ‐‐‐2.02.02.0

129401294012940 Baton Rouge LABaton Rouge LABaton Rouge LABaton Rouge LA ‐‐‐1.71.71.7 ‐‐‐4.14.14.1 7.67.67.6 505050 0.00.00.0

129801298012980 Battle Creek MIBattle Creek MIBattle Creek MIBattle Creek MI ‐‐‐15.215.215.2 1.11.11.1 11.311.311.3 195195195 ‐‐‐1.01.01.0

130201302013020 Bay City MIBay City MIBay City MIBay City MI ‐‐‐19.019.019.0 0.70.70.7 11.611.611.6 226226226 ‐‐‐1.01.01.0

131401314013140 Beaumont TXBeaumont TXBeaumont TXBeaumont TX ‐‐‐12.912.912.9 ‐‐‐4.74.74.7 7.27.27.2 155155155 ‐‐‐1.01.01.0

133801338013380 Bellingham WABellingham WABellingham WABellingham WA ‐‐‐17.117.117.1 ‐‐‐3.03.03.0 7.37.37.3 316316316 ‐‐‐2.02.02.0

134601346013460 Bend ORBend ORBend ORBend OR ‐‐‐26.826.826.8 ‐‐‐4.44.44.4 10.910.910.9 289289289 ‐‐‐2.02.02.0

136441364413644 Bethesda MD [Metropolitan Division]Bethesda MD [Metropolitan Division]Bethesda MD [Metropolitan Division]Bethesda MD [Metropolitan Division] ‐‐‐11.911.911.9 ‐‐‐0.70.70.7 11.411.411.4 168168168 ‐‐‐1.01.01.0

137401374013740 Billings MTBillings MTBillings MTBillings MT ‐‐‐2.52.52.5 ‐‐‐2.62.62.6 5.15.15.1 787878 0.00.00.0

137801378013780 Binghamton NYBinghamton NYBinghamton NYBinghamton NY ‐‐‐1.01.01.0 0.90.90.9 10.810.810.8 595959 0.00.00.0

138201382013820 Birmingham ALBirmingham ALBirmingham ALBirmingham AL ‐‐‐1.71.71.7 0.60.60.6 5.95.95.9 636363 0.00.00.0

139001390013900 Bismarck NDBismarck NDBismarck NDBismarck ND 3.93.93.9 ‐‐‐1.51.51.5 6.26.26.2 414141 0.00.00.0

139801398013980 Blacksburg VABlacksburg VABlacksburg VABlacksburg VA 17.717.717.7 4.34.34.3 13.513.513.5 555 1.01.01.0

140601406014060 Bloomington ILBloomington ILBloomington ILBloomington IL ‐‐‐8.58.58.5 ‐‐‐2.42.42.4 4.94.94.9 246246246 ‐‐‐1.01.01.0

140201402014020 Bloomington INBloomington INBloomington INBloomington IN ‐‐‐4.24.24.2 ‐‐‐0.60.60.6 3.33.33.3 107107107 0.00.00.0

142601426014260 Boise City IDBoise City IDBoise City IDBoise City ID ‐‐‐17.217.217.2 ‐‐‐2.62.62.6 12.012.012.0 137137137 0.00.00.0

144841448414484 Boston MA [Metropolitan Division]Boston MA [Metropolitan Division]Boston MA [Metropolitan Division]Boston MA [Metropolitan Division] ‐‐‐13.813.813.8 4.04.04.0 15.515.515.5 245245245 ‐‐‐1.01.01.0

145001450014500 Boulder COBoulder COBoulder COBoulder CO ‐‐‐3.33.33.3 ‐‐‐1.01.01.0 8.38.38.3 139139139 0.00.00.0

145401454014540 Bowling Green KYBowling Green KYBowling Green KYBowling Green KY ‐‐‐6.96.96.9 ‐‐‐0.80.80.8 5.95.95.9 196196196 ‐‐‐1.01.01.0

147401474014740 Bremerton WABremerton WABremerton WABremerton WA ‐‐‐22.322.322.3 ‐‐‐2.72.72.7 8.98.98.9 335335335 ‐‐‐2.02.02.0

148601486014860 Bridgeport CTBridgeport CTBridgeport CTBridgeport CT ‐‐‐15.515.515.5 2.12.12.1 15.615.615.6 291291291 ‐‐‐2.02.02.0

151801518015180 Brownsville TXBrownsville TXBrownsville TXBrownsville TX ‐‐‐22.922.922.9 ‐‐‐5.75.75.7 13.313.313.3 219219219 ‐‐‐1.01.01.0

152601526015260 Brunswick GABrunswick GABrunswick GABrunswick GA ‐‐‐6.16.16.1 ‐‐‐0.10.10.1 7.67.67.6 102102102 0.00.00.0



153801538015380 Buffalo NYBuffalo NYBuffalo NYBuffalo NY ‐‐‐16.416.416.4 ‐‐‐2.02.02.0 9.29.29.2 271271271 ‐‐‐2.02.02.0

155001550015500 Burlington NCBurlington NCBurlington NCBurlington NC ‐‐‐9.09.09.0 0.90.90.9 4.84.84.8 336336336 ‐‐‐2.02.02.0

155401554015540 Burlington VTBurlington VTBurlington VTBurlington VT 20.720.720.7 26.726.726.7 9.39.39.3 232323 0.00.00.0

157641576415764 Cambridge MA [Metropolitan Division]Cambridge MA [Metropolitan Division]Cambridge MA [Metropolitan Division]Cambridge MA [Metropolitan Division] ‐‐‐17.017.017.0 2.72.72.7 15.415.415.4 292292292 ‐‐‐2.02.02.0

158041580415804 Camden NJ [Metropolitan Division]Camden NJ [Metropolitan Division]Camden NJ [Metropolitan Division]Camden NJ [Metropolitan Division] ‐‐‐23.123.123.1 ‐‐‐2.12.12.1 11.911.911.9 338338338 ‐‐‐2.02.02.0

159401594015940 Canton OHCanton OHCanton OHCanton OH ‐‐‐22.122.122.1 ‐‐‐2.42.42.4 7.07.07.0 379379379 ‐‐‐2.02.02.0

159801598015980 Cape Coral FLCape Coral FLCape Coral FLCape Coral FL ‐‐‐34.134.134.1 ‐‐‐1.61.61.6 17.217.217.2 276276276 ‐‐‐2.02.02.0

160201602016020 Cape Girardeau MOCape Girardeau MOCape Girardeau MOCape Girardeau MO ‐‐‐14.314.314.3 ‐‐‐1.81.81.8 5.15.15.1 346346346 ‐‐‐2.02.02.0

161801618016180 Carson City NVCarson City NVCarson City NVCarson City NV ‐‐‐20.620.620.6 2.32.32.3 20.520.520.5 105105105 0.00.00.0

162201622016220 Casper WYCasper WYCasper WYCasper WY ‐‐‐14.714.714.7 ‐‐‐3.33.33.3 9.49.49.4 243243243 ‐‐‐1.01.01.0

163001630016300 Cedar Rapids IACedar Rapids IACedar Rapids IACedar Rapids IA ‐‐‐9.69.69.6 ‐‐‐2.12.12.1 3.03.03.0 297297297 ‐‐‐2.02.02.0

165801658016580 Champaign ILChampaign ILChampaign ILChampaign IL ‐‐‐4.34.34.3 ‐‐‐1.71.71.7 5.25.25.2 119119119 0.00.00.0

167001670016700 Charleston SCCharleston SCCharleston SCCharleston SC ‐‐‐1.81.81.8 2.02.02.0 12.812.812.8 868686 0.00.00.0

166201662016620 Charleston WVCharleston WVCharleston WVCharleston WV ‐‐‐7.37.37.3 ‐‐‐2.62.62.6 4.84.84.8 157157157 ‐‐‐1.01.01.0

167401674016740 Charlotte NCCharlotte NCCharlotte NCCharlotte NC ‐‐‐14.814.814.8 ‐‐‐1.71.71.7 5.55.55.5 354354354 ‐‐‐2.02.02.0

168201682016820 Charlottesville VACharlottesville VACharlottesville VACharlottesville VA 9.69.69.6 2.52.52.5 15.015.015.0 171717 0.00.00.0

168601686016860 Chattanooga TNChattanooga TNChattanooga TNChattanooga TN 6.16.16.1 1.51.51.5 8.18.18.1 999 1.01.01.0

169401694016940 Cheyenne WYCheyenne WYCheyenne WYCheyenne WY ‐‐‐14.114.114.1 ‐‐‐2.52.52.5 6.76.76.7 302302302 ‐‐‐2.02.02.0

169741697416974 Chicago IL [Metropolitan Division]Chicago IL [Metropolitan Division]Chicago IL [Metropolitan Division]Chicago IL [Metropolitan Division] ‐‐‐17.817.817.8 2.82.82.8 12.212.212.2 216216216 ‐‐‐1.01.01.0

170201702017020 Chico CAChico CAChico CAChico CA ‐‐‐56.356.356.3 ‐‐‐34.134.134.1 8.18.18.1 347347347 ‐‐‐2.02.02.0

171401714017140 Cincinnati OHCincinnati OHCincinnati OHCincinnati OH ‐‐‐17.717.717.7 ‐‐‐1.61.61.6 4.84.84.8 381381381 ‐‐‐2.02.02.0

173001730017300 Clarksville TNClarksville TNClarksville TNClarksville TN ‐‐‐0.80.80.8 ‐‐‐2.62.62.6 5.95.95.9 696969 0.00.00.0

174601746017460 Cleveland OHCleveland OHCleveland OHCleveland OH ‐‐‐24.124.124.1 ‐‐‐2.22.22.2 7.17.17.1 378378378 ‐‐‐2.02.02.0

174201742017420 Cleveland TNCleveland TNCleveland TNCleveland TN 4.34.34.3 ‐‐‐0.50.50.5 10.310.310.3 191919 0.00.00.0

176601766017660 Coeur d'Alene IDCoeur d'Alene IDCoeur d'Alene IDCoeur d'Alene ID ‐‐‐11.411.411.4 ‐‐‐2.32.32.3 11.011.011.0 133133133 0.00.00.0

177801778017780 College Station TXCollege Station TXCollege Station TXCollege Station TX ‐‐‐4.74.74.7 ‐‐‐2.42.42.4 7.67.67.6 858585 0.00.00.0

178201782017820 Colorado Springs COColorado Springs COColorado Springs COColorado Springs CO ‐‐‐18.018.018.0 ‐‐‐4.04.04.0 8.08.08.0 319319319 ‐‐‐2.02.02.0

178601786017860 Columbia MOColumbia MOColumbia MOColumbia MO ‐‐‐8.38.38.3 ‐‐‐3.33.33.3 6.06.06.0 181181181 ‐‐‐1.01.01.0

179001790017900 Columbia SCColumbia SCColumbia SCColumbia SC ‐‐‐5.05.05.0 ‐‐‐1.41.41.4 4.84.84.8 101101101 0.00.00.0

179801798017980 Columbus GAColumbus GAColumbus GAColumbus GA ‐‐‐14.414.414.4 ‐‐‐0.10.10.1 6.36.36.3 208208208 ‐‐‐1.01.01.0

180201802018020 Columbus INColumbus INColumbus INColumbus IN ‐‐‐8.28.28.2 0.10.10.1 3.83.83.8 228228228 ‐‐‐1.01.01.0

181401814018140 Columbus OHColumbus OHColumbus OHColumbus OH ‐‐‐15.215.215.2 ‐‐‐2.42.42.4 4.74.74.7 364364364 ‐‐‐2.02.02.0

185801858018580 Corpus Christi TXCorpus Christi TXCorpus Christi TXCorpus Christi TX ‐‐‐17.417.417.4 ‐‐‐5.45.45.4 10.210.210.2 218218218 ‐‐‐1.01.01.0

187001870018700 Corvallis ORCorvallis ORCorvallis ORCorvallis OR ‐‐‐13.713.713.7 ‐‐‐5.05.05.0 8.78.78.7 178178178 ‐‐‐1.01.01.0

188801888018880 Crestview FLCrestview FLCrestview FLCrestview FL ‐‐‐13.613.613.6 ‐‐‐5.15.15.1 13.913.913.9 152152152 ‐‐‐1.01.01.0

190601906019060 Cumberland MDCumberland MDCumberland MDCumberland MD ‐‐‐13.513.513.5 ‐‐‐2.92.92.9 6.96.96.9 277277277 ‐‐‐2.02.02.0

191241912419124 Dallas TX [Metropolitan Division]Dallas TX [Metropolitan Division]Dallas TX [Metropolitan Division]Dallas TX [Metropolitan Division] ‐‐‐4.44.44.4 ‐‐‐3.73.73.7 8.28.28.2 737373 0.00.00.0

191401914019140 Dalton GADalton GADalton GADalton GA ‐‐‐0.40.40.4 1.31.31.3 11.411.411.4 393939 0.00.00.0

191801918019180 Danville ILDanville ILDanville ILDanville IL ‐‐‐3.73.73.7 3.93.93.9 7.87.87.8 128128128 0.00.00.0

192601926019260 Danville VADanville VADanville VADanville VA ‐‐‐0.80.80.8 3.33.33.3 6.26.26.2 898989 0.00.00.0

193401934019340 Davenport ILDavenport ILDavenport ILDavenport IL ‐‐‐7.87.87.8 ‐‐‐3.83.83.8 5.05.05.0 190190190 ‐‐‐1.01.01.0

193801938019380 Dayton OHDayton OHDayton OHDayton OH ‐‐‐16.916.916.9 ‐‐‐0.50.50.5 5.15.15.1 382382382 ‐‐‐2.02.02.0

194601946019460 Decatur ALDecatur ALDecatur ALDecatur AL ‐‐‐3.73.73.7 ‐‐‐1.91.91.9 5.85.85.8 606060 0.00.00.0

195001950019500 Decatur ILDecatur ILDecatur ILDecatur IL ‐‐‐12.812.812.8 ‐‐‐0.80.80.8 4.94.94.9 360360360 ‐‐‐2.02.02.0

196601966019660 Deltona FLDeltona FLDeltona FLDeltona FL ‐‐‐30.830.830.8 ‐‐‐1.91.91.9 13.713.713.7 295295295 ‐‐‐2.02.02.0

197401974019740 Denver CODenver CODenver CODenver CO ‐‐‐11.111.111.1 ‐‐‐3.43.43.4 8.88.88.8 214214214 ‐‐‐1.01.01.0

197801978019780 Des Moines IADes Moines IADes Moines IADes Moines IA ‐‐‐9.19.19.1 ‐‐‐2.52.52.5 4.14.14.1 220220220 ‐‐‐1.01.01.0

198041980419804 Detroit MI [Metropolitan Division]Detroit MI [Metropolitan Division]Detroit MI [Metropolitan Division]Detroit MI [Metropolitan Division] ‐‐‐51.451.451.4 1.11.11.1 22.422.422.4 332332332 ‐‐‐2.02.02.0

200202002020020 Dothan ALDothan ALDothan ALDothan AL ‐‐‐8.28.28.2 ‐‐‐1.81.81.8 5.55.55.5 145145145 0.00.00.0

201002010020100 Dover DEDover DEDover DEDover DE ‐‐‐17.217.217.2 ‐‐‐2.42.42.4 8.18.18.1 294294294 ‐‐‐2.02.02.0

202202022020220 Dubuque IADubuque IADubuque IADubuque IA ‐‐‐4.84.84.8 ‐‐‐1.91.91.9 4.24.24.2 163163163 ‐‐‐1.01.01.0

202602026020260 Duluth MNDuluth MNDuluth MNDuluth MN ‐‐‐12.012.012.0 0.20.20.2 4.94.94.9 305305305 ‐‐‐2.02.02.0

205002050020500 Durham NCDurham NCDurham NCDurham NC 1.41.41.4 1.21.21.2 7.37.37.3 434343 0.00.00.0

207402074020740 Eau Claire WIEau Claire WIEau Claire WIEau Claire WI ‐‐‐2.42.42.4 0.30.30.3 7.67.67.6 717171 0.00.00.0

207642076420764 Edison NJ [Metropolitan Division]Edison NJ [Metropolitan Division]Edison NJ [Metropolitan Division]Edison NJ [Metropolitan Division] ‐‐‐11.011.011.0 2.02.02.0 16.216.216.2 175175175 ‐‐‐1.01.01.0

209402094020940 El Centro CAEl Centro CAEl Centro CAEl Centro CA ‐‐‐49.249.249.2 ‐‐‐12.812.812.8 18.218.218.2 340340340 ‐‐‐2.02.02.0

213402134021340 El Paso TXEl Paso TXEl Paso TXEl Paso TX ‐‐‐3.43.43.4 ‐‐‐3.03.03.0 8.18.18.1 767676 0.00.00.0

210602106021060 Elizabethtown KYElizabethtown KYElizabethtown KYElizabethtown KY ‐‐‐0.70.70.7 0.20.20.2 6.56.56.5 525252 0.00.00.0

211402114021140 Elkhart INElkhart INElkhart INElkhart IN ‐‐‐13.513.513.5 ‐‐‐3.83.83.8 4.44.44.4 241241241 ‐‐‐1.01.01.0

213002130021300 Elmira NYElmira NYElmira NYElmira NY 2.92.92.9 3.43.43.4 5.95.95.9 484848 0.00.00.0

215002150021500 Erie PAErie PAErie PAErie PA ‐‐‐8.48.48.4 ‐‐‐0.40.40.4 3.43.43.4 325325325 ‐‐‐2.02.02.0



216602166021660 Eugene OREugene OREugene OREugene OR ‐‐‐14.714.714.7 ‐‐‐1.11.11.1 8.68.68.6 198198198 ‐‐‐1.01.01.0

217802178021780 Evansville INEvansville INEvansville INEvansville IN ‐‐‐11.711.711.7 ‐‐‐2.92.92.9 5.65.65.6 258258258 ‐‐‐2.02.02.0

218202182021820 Fairbanks AKFairbanks AKFairbanks AKFairbanks AK ‐‐‐16.316.316.3 ‐‐‐2.82.82.8 9.99.99.9 270270270 ‐‐‐2.02.02.0

220202202022020 Fargo NDFargo NDFargo NDFargo ND ‐‐‐5.25.25.2 ‐‐‐5.05.05.0 6.96.96.9 111111111 0.00.00.0

221402214022140 Farmington NMFarmington NMFarmington NMFarmington NM ‐‐‐9.19.19.1 2.62.62.6 9.89.89.8 135135135 0.00.00.0

222202222022220 Fayetteville ARFayetteville ARFayetteville ARFayetteville AR ‐‐‐4.44.44.4 ‐‐‐1.41.41.4 8.48.48.4 909090 0.00.00.0

221802218022180 Fayetteville NCFayetteville NCFayetteville NCFayetteville NC ‐‐‐5.75.75.7 ‐‐‐0.50.50.5 4.04.04.0 252252252 ‐‐‐2.02.02.0

223802238022380 Flagstaff AZFlagstaff AZFlagstaff AZFlagstaff AZ ‐‐‐31.331.331.3 ‐‐‐2.82.82.8 11.811.811.8 351351351 ‐‐‐2.02.02.0

224202242022420 Flint MIFlint MIFlint MIFlint MI ‐‐‐25.625.625.6 0.20.20.2 13.013.013.0 279279279 ‐‐‐2.02.02.0

225202252022520 Florence ALFlorence ALFlorence ALFlorence AL ‐‐‐1.91.91.9 ‐‐‐1.71.71.7 6.26.26.2 110110110 0.00.00.0

225002250022500 Florence SCFlorence SCFlorence SCFlorence SC ‐‐‐7.67.67.6 ‐‐‐1.61.61.6 4.74.74.7 156156156 ‐‐‐1.01.01.0

225402254022540 Fond du Lac WIFond du Lac WIFond du Lac WIFond du Lac WI ‐‐‐8.08.08.0 ‐‐‐1.11.11.1 5.85.85.8 167167167 ‐‐‐1.01.01.0

226602266022660 Fort Collins COFort Collins COFort Collins COFort Collins CO ‐‐‐13.313.313.3 ‐‐‐3.83.83.8 7.27.27.2 273273273 ‐‐‐2.02.02.0

227442274422744 Fort Lauderdale FL [Metropolitan Division]Fort Lauderdale FL [Metropolitan Division]Fort Lauderdale FL [Metropolitan Division]Fort Lauderdale FL [Metropolitan Division] ‐‐‐15.715.715.7 1.71.71.7 21.921.921.9 138138138 0.00.00.0

229002290022900 Fort Smith ARFort Smith ARFort Smith ARFort Smith AR ‐‐‐2.02.02.0 ‐‐‐1.31.31.3 5.25.25.2 747474 0.00.00.0

230602306023060 Fort Wayne INFort Wayne INFort Wayne INFort Wayne IN ‐‐‐16.316.316.3 ‐‐‐4.24.24.2 6.66.66.6 248248248 ‐‐‐1.01.01.0

231042310423104 Fort Worth TX [Metropolitan Division]Fort Worth TX [Metropolitan Division]Fort Worth TX [Metropolitan Division]Fort Worth TX [Metropolitan Division] ‐‐‐8.48.48.4 ‐‐‐4.04.04.0 6.06.06.0 130130130 0.00.00.0

234202342023420 Fresno CAFresno CAFresno CAFresno CA ‐‐‐53.553.553.5 ‐‐‐26.626.626.6 13.013.013.0 322322322 ‐‐‐2.02.02.0

234602346023460 Gadsden ALGadsden ALGadsden ALGadsden AL 8.38.38.3 2.52.52.5 10.410.410.4 181818 0.00.00.0

235402354023540 Gainesville FLGainesville FLGainesville FLGainesville FL ‐‐‐13.413.413.4 ‐‐‐2.92.92.9 13.113.113.1 143143143 0.00.00.0

235802358023580 Gainesville GAGainesville GAGainesville GAGainesville GA ‐‐‐10.810.810.8 0.30.30.3 10.210.210.2 197197197 ‐‐‐1.01.01.0

238442384423844 Gary IN [Metropolitan Division]Gary IN [Metropolitan Division]Gary IN [Metropolitan Division]Gary IN [Metropolitan Division] ‐‐‐15.615.615.6 ‐‐‐2.62.62.6 3.93.93.9 370370370 ‐‐‐2.02.02.0

240202402024020 Glens Falls NYGlens Falls NYGlens Falls NYGlens Falls NY ‐‐‐38.938.938.9 2.82.82.8 36.836.836.8 268268268 ‐‐‐2.02.02.0

241402414024140 Goldsboro NCGoldsboro NCGoldsboro NCGoldsboro NC ‐‐‐6.26.26.2 ‐‐‐0.10.10.1 5.15.15.1 959595 0.00.00.0

242202422024220 Grand Forks NDGrand Forks NDGrand Forks NDGrand Forks ND ‐‐‐10.210.210.2 ‐‐‐4.24.24.2 5.45.45.4 187187187 ‐‐‐1.01.01.0

243002430024300 Grand Junction COGrand Junction COGrand Junction COGrand Junction CO ‐‐‐5.75.75.7 ‐‐‐1.21.21.2 14.914.914.9 888888 0.00.00.0

243402434024340 Grand Rapids MIGrand Rapids MIGrand Rapids MIGrand Rapids MI ‐‐‐18.018.018.0 ‐‐‐0.10.10.1 6.46.46.4 356356356 ‐‐‐2.02.02.0

245002450024500 Great Falls MTGreat Falls MTGreat Falls MTGreat Falls MT ‐‐‐8.58.58.5 ‐‐‐3.33.33.3 6.26.26.2 192192192 ‐‐‐1.01.01.0

245402454024540 Greeley COGreeley COGreeley COGreeley CO ‐‐‐12.612.612.6 ‐‐‐3.93.93.9 8.98.98.9 238238238 ‐‐‐1.01.01.0

245802458024580 Green Bay WIGreen Bay WIGreen Bay WIGreen Bay WI ‐‐‐19.519.519.5 ‐‐‐3.43.43.4 5.25.25.2 366366366 ‐‐‐2.02.02.0

246602466024660 Greensboro NCGreensboro NCGreensboro NCGreensboro NC ‐‐‐2.72.72.7 0.30.30.3 5.25.25.2 797979 0.00.00.0

247802478024780 Greenville NCGreenville NCGreenville NCGreenville NC ‐‐‐5.05.05.0 ‐‐‐0.60.60.6 5.65.65.6 160160160 ‐‐‐1.01.01.0

248602486024860 Greenville SCGreenville SCGreenville SCGreenville SC 2.52.52.5 ‐‐‐0.30.30.3 5.55.55.5 373737 0.00.00.0

250602506025060 Gulfport MSGulfport MSGulfport MSGulfport MS ‐‐‐13.913.913.9 ‐‐‐0.90.90.9 11.811.811.8 146146146 0.00.00.0

251802518025180 Hagerstown MDHagerstown MDHagerstown MDHagerstown MD ‐‐‐22.822.822.8 ‐‐‐0.10.10.1 7.47.47.4 304304304 ‐‐‐2.02.02.0

252602526025260 Hanford CAHanford CAHanford CAHanford CA ‐‐‐12.212.212.2 20.220.220.2 16.616.616.6 189189189 ‐‐‐1.01.01.0

254202542025420 Harrisburg PAHarrisburg PAHarrisburg PAHarrisburg PA 0.30.30.3 ‐‐‐1.11.11.1 5.65.65.6 474747 0.00.00.0

255002550025500 Harrisonburg VAHarrisonburg VAHarrisonburg VAHarrisonburg VA 15.015.015.0 2.62.62.6 15.515.515.5 101010 1.01.01.0

255402554025540 Hartford CTHartford CTHartford CTHartford CT ‐‐‐26.526.526.5 ‐‐‐2.52.52.5 19.219.219.2 283283283 ‐‐‐2.02.02.0

256202562025620 Hattiesburg MSHattiesburg MSHattiesburg MSHattiesburg MS ‐‐‐6.16.16.1 ‐‐‐3.43.43.4 8.38.38.3 125125125 0.00.00.0

258602586025860 Hickory NCHickory NCHickory NCHickory NC 3.63.63.6 2.52.52.5 8.48.48.4 222222 0.00.00.0

259802598025980 Hinesville GAHinesville GAHinesville GAHinesville GA 9.69.69.6 7.27.27.2 14.414.414.4 252525 0.00.00.0

261002610026100 Holland MIHolland MIHolland MIHolland MI ‐‐‐13.213.213.2 ‐‐‐0.10.10.1 7.67.67.6 236236236 ‐‐‐1.01.01.0

261802618026180 Honolulu HIHonolulu HIHonolulu HIHonolulu HI ‐‐‐1.81.81.8 3.63.63.6 12.012.012.0 103103103 0.00.00.0

263002630026300 Hot Springs ARHot Springs ARHot Springs ARHot Springs AR 0.20.20.2 ‐‐‐2.32.32.3 8.68.68.6 929292 0.00.00.0

263802638026380 Houma LAHouma LAHouma LAHouma LA ‐‐‐3.43.43.4 ‐‐‐3.13.13.1 7.47.47.4 424242 0.00.00.0

264202642026420 Houston TXHouston TXHouston TXHouston TX ‐‐‐7.57.57.5 ‐‐‐4.54.54.5 8.48.48.4 104104104 0.00.00.0

265802658026580 Huntington WVHuntington WVHuntington WVHuntington WV 0.50.50.5 ‐‐‐2.12.12.1 6.16.16.1 515151 0.00.00.0

266202662026620 Huntsville ALHuntsville ALHuntsville ALHuntsville AL ‐‐‐3.33.33.3 ‐‐‐3.43.43.4 5.05.05.0 808080 0.00.00.0

268202682026820 Idaho Falls IDIdaho Falls IDIdaho Falls IDIdaho Falls ID ‐‐‐22.322.322.3 ‐‐‐7.67.67.6 7.77.77.7 263263263 ‐‐‐2.02.02.0

269002690026900 Indianapolis INIndianapolis INIndianapolis INIndianapolis IN ‐‐‐11.911.911.9 ‐‐‐2.62.62.6 4.44.44.4 274274274 ‐‐‐2.02.02.0

269802698026980 Iowa City IAIowa City IAIowa City IAIowa City IA ‐‐‐4.04.04.0 ‐‐‐1.61.61.6 3.93.93.9 144144144 0.00.00.0

270602706027060 Ithaca NYIthaca NYIthaca NYIthaca NY 21.921.921.9 9.59.59.5 13.613.613.6 777 1.01.01.0

271002710027100 Jackson MIJackson MIJackson MIJackson MI ‐‐‐20.420.420.4 2.42.42.4 11.711.711.7 257257257 ‐‐‐2.02.02.0

271402714027140 Jackson MSJackson MSJackson MSJackson MS ‐‐‐5.55.55.5 ‐‐‐2.92.92.9 6.76.76.7 121121121 0.00.00.0

271802718027180 Jackson TNJackson TNJackson TNJackson TN ‐‐‐14.014.014.0 ‐‐‐2.72.72.7 5.25.25.2 266266266 ‐‐‐2.02.02.0

272602726027260 Jacksonville FLJacksonville FLJacksonville FLJacksonville FL ‐‐‐20.720.720.7 ‐‐‐3.43.43.4 11.511.511.5 264264264 ‐‐‐2.02.02.0

273402734027340 Jacksonville NCJacksonville NCJacksonville NCJacksonville NC ‐‐‐13.413.413.4 ‐‐‐0.80.80.8 5.85.85.8 357357357 ‐‐‐2.02.02.0

275002750027500 Janesville WIJanesville WIJanesville WIJanesville WI ‐‐‐3.53.53.5 ‐‐‐0.90.90.9 10.110.110.1 828282 0.00.00.0

276202762027620 Jefferson City MOJefferson City MOJefferson City MOJefferson City MO ‐‐‐10.810.810.8 ‐‐‐1.91.91.9 6.16.16.1 260260260 ‐‐‐2.02.02.0

277402774027740 Johnson City TNJohnson City TNJohnson City TNJohnson City TN 0.70.70.7 ‐‐‐2.22.22.2 6.86.86.8 313131 0.00.00.0



277802778027780 Johnstown PAJohnstown PAJohnstown PAJohnstown PA ‐‐‐9.89.89.8 3.43.43.4 9.99.99.9 176176176 ‐‐‐1.01.01.0

278602786027860 Jonesboro ARJonesboro ARJonesboro ARJonesboro AR ‐‐‐13.313.313.3 ‐‐‐5.15.15.1 7.57.57.5 193193193 ‐‐‐1.01.01.0

279002790027900 Joplin MOJoplin MOJoplin MOJoplin MO ‐‐‐8.78.78.7 ‐‐‐2.12.12.1 5.85.85.8 199199199 ‐‐‐1.01.01.0

280202802028020 Kalamazoo MIKalamazoo MIKalamazoo MIKalamazoo MI ‐‐‐15.615.615.6 ‐‐‐2.02.02.0 6.56.56.5 342342342 ‐‐‐2.02.02.0

281002810028100 Kankakee ILKankakee ILKankakee ILKankakee IL ‐‐‐0.40.40.4 5.45.45.4 7.47.47.4 727272 0.00.00.0

281402814028140 Kansas City MOKansas City MOKansas City MOKansas City MO ‐‐‐11.711.711.7 ‐‐‐3.33.33.3 5.85.85.8 211211211 ‐‐‐1.01.01.0

284202842028420 Kennewick WAKennewick WAKennewick WAKennewick WA ‐‐‐21.921.921.9 ‐‐‐2.42.42.4 9.19.19.1 355355355 ‐‐‐2.02.02.0

286602866028660 Killeen TXKilleen TXKilleen TXKilleen TX ‐‐‐18.518.518.5 ‐‐‐6.76.76.7 8.28.28.2 240240240 ‐‐‐1.01.01.0

287002870028700 Kingsport TNKingsport TNKingsport TNKingsport TN 9.69.69.6 1.11.11.1 9.19.19.1 444 1.01.01.0

287402874028740 Kingston NYKingston NYKingston NYKingston NY ‐‐‐10.510.510.5 4.64.64.6 16.116.116.1 131131131 0.00.00.0

289402894028940 Knoxville TNKnoxville TNKnoxville TNKnoxville TN 9.39.39.3 1.41.41.4 9.19.19.1 121212 1.01.01.0

290202902029020 Kokomo INKokomo INKokomo INKokomo IN ‐‐‐18.118.118.1 ‐‐‐3.13.13.1 6.26.26.2 284284284 ‐‐‐2.02.02.0

291002910029100 La Crosse WILa Crosse WILa Crosse WILa Crosse WI 0.40.40.4 ‐‐‐1.11.11.1 9.09.09.0 565656 0.00.00.0

291402914029140 Lafayette INLafayette INLafayette INLafayette IN ‐‐‐15.315.315.3 ‐‐‐1.01.01.0 5.65.65.6 339339339 ‐‐‐2.02.02.0

291802918029180 Lafayette LALafayette LALafayette LALafayette LA ‐‐‐7.17.17.1 ‐‐‐5.65.65.6 5.75.75.7 949494 0.00.00.0

293402934029340 Lake Charles LALake Charles LALake Charles LALake Charles LA ‐‐‐9.29.29.2 ‐‐‐3.73.73.7 9.69.69.6 352352352 ‐‐‐2.02.02.0

294042940429404 Lake County IL [Metropolitan Division]Lake County IL [Metropolitan Division]Lake County IL [Metropolitan Division]Lake County IL [Metropolitan Division] ‐‐‐4.84.84.8 1.71.71.7 7.27.27.2 999999 0.00.00.0

294202942029420 Lake Havasu AZLake Havasu AZLake Havasu AZLake Havasu AZ ‐‐‐18.218.218.2 ‐‐‐0.50.50.5 15.015.015.0 165165165 ‐‐‐1.01.01.0

294602946029460 Lakeland FLLakeland FLLakeland FLLakeland FL ‐‐‐45.845.845.8 ‐‐‐6.16.16.1 17.717.717.7 334334334 ‐‐‐2.02.02.0

295402954029540 Lancaster PALancaster PALancaster PALancaster PA 3.43.43.4 ‐‐‐0.40.40.4 7.37.37.3 242424 0.00.00.0

296202962029620 Lansing MILansing MILansing MILansing MI ‐‐‐30.730.730.7 ‐‐‐2.02.02.0 11.311.311.3 365365365 ‐‐‐2.02.02.0

297002970029700 Laredo TXLaredo TXLaredo TXLaredo TX ‐‐‐13.213.213.2 ‐‐‐6.26.26.2 14.514.514.5 127127127 0.00.00.0

297402974029740 Las Cruces NMLas Cruces NMLas Cruces NMLas Cruces NM ‐‐‐19.519.519.5 ‐‐‐3.43.43.4 6.46.46.4 353353353 ‐‐‐2.02.02.0

298202982029820 Las Vegas NVLas Vegas NVLas Vegas NVLas Vegas NV ‐‐‐38.138.138.1 ‐‐‐2.92.92.9 19.019.019.0 259259259 ‐‐‐2.02.02.0

299402994029940 Lawrence KSLawrence KSLawrence KSLawrence KS 4.04.04.0 0.70.70.7 9.39.39.3 323232 0.00.00.0

300203002030020 Lawton OKLawton OKLawton OKLawton OK ‐‐‐20.020.020.0 ‐‐‐7.87.87.8 7.97.97.9 207207207 ‐‐‐1.01.01.0

301403014030140 Lebanon PALebanon PALebanon PALebanon PA 2.42.42.4 4.44.44.4 6.26.26.2 363636 0.00.00.0

303003030030300 Lewiston IDLewiston IDLewiston IDLewiston ID ‐‐‐3.13.13.1 ‐‐‐1.21.21.2 10.610.610.6 464646 0.00.00.0

303403034030340 Lewiston MELewiston MELewiston MELewiston ME ‐‐‐18.318.318.3 0.90.90.9 10.810.810.8 303303303 ‐‐‐2.02.02.0

304603046030460 Lexington KYLexington KYLexington KYLexington KY 5.15.15.1 ‐‐‐0.80.80.8 7.97.97.9 161616 1.01.01.0

306203062030620 Lima OHLima OHLima OHLima OH ‐‐‐7.77.77.7 ‐‐‐1.11.11.1 5.35.35.3 162162162 ‐‐‐1.01.01.0

307003070030700 Lincoln NELincoln NELincoln NELincoln NE ‐‐‐5.55.55.5 ‐‐‐2.62.62.6 4.24.24.2 172172172 ‐‐‐1.01.01.0

307803078030780 Little Rock ARLittle Rock ARLittle Rock ARLittle Rock AR ‐‐‐2.92.92.9 ‐‐‐2.32.32.3 5.95.95.9 939393 0.00.00.0

308603086030860 Logan UTLogan UTLogan UTLogan UT ‐‐‐3.33.33.3 ‐‐‐1.11.11.1 8.18.18.1 848484 0.00.00.0

309803098030980 Longview TXLongview TXLongview TXLongview TX ‐‐‐3.53.53.5 ‐‐‐2.22.22.2 6.96.96.9 646464 0.00.00.0

310203102031020 Longview WALongview WALongview WALongview WA ‐‐‐20.120.120.1 ‐‐‐1.71.71.7 11.111.111.1 275275275 ‐‐‐2.02.02.0

310843108431084 Los Angeles CA [Metropolitan Division]Los Angeles CA [Metropolitan Division]Los Angeles CA [Metropolitan Division]Los Angeles CA [Metropolitan Division] ‐‐‐10.710.710.7 12.012.012.0 18.918.918.9 154154154 ‐‐‐1.01.01.0

311403114031140 Louisville KYLouisville KYLouisville KYLouisville KY 3.73.73.7 1.71.71.7 7.87.87.8 272727 0.00.00.0

311803118031180 Lubbock TXLubbock TXLubbock TXLubbock TX ‐‐‐7.77.77.7 ‐‐‐4.54.54.5 5.95.95.9 141141141 0.00.00.0

313403134031340 Lynchburg VALynchburg VALynchburg VALynchburg VA 11.311.311.3 2.82.82.8 9.19.19.1 333 1.01.01.0

314203142031420 Macon GAMacon GAMacon GAMacon GA ‐‐‐11.811.811.8 ‐‐‐0.80.80.8 5.25.25.2 235235235 ‐‐‐1.01.01.0

314603146031460 Madera CAMadera CAMadera CAMadera CA ‐‐‐15.515.515.5 29.229.229.2 18.918.918.9 186186186 ‐‐‐1.01.01.0

315403154031540 Madison WIMadison WIMadison WIMadison WI 3.93.93.9 0.70.70.7 9.29.29.2 383838 0.00.00.0

317003170031700 Manchester NHManchester NHManchester NHManchester NH ‐‐‐18.818.818.8 ‐‐‐0.30.30.3 17.517.517.5 249249249 ‐‐‐1.01.01.0

317403174031740 Manhattan KSManhattan KSManhattan KSManhattan KS ‐‐‐13.013.013.0 ‐‐‐2.62.62.6 8.08.08.0 299299299 ‐‐‐2.02.02.0

318603186031860 Mankato MNMankato MNMankato MNMankato MN ‐‐‐7.67.67.6 ‐‐‐0.20.20.2 7.47.47.4 112112112 0.00.00.0

319003190031900 Mansfield OHMansfield OHMansfield OHMansfield OH ‐‐‐16.516.516.5 ‐‐‐1.41.41.4 7.97.97.9 318318318 ‐‐‐2.02.02.0

325803258032580 McAllen TXMcAllen TXMcAllen TXMcAllen TX ‐‐‐21.821.821.8 ‐‐‐5.95.95.9 12.712.712.7 209209209 ‐‐‐1.01.01.0

327803278032780 Medford ORMedford ORMedford ORMedford OR ‐‐‐21.821.821.8 ‐‐‐2.12.12.1 14.714.714.7 188188188 ‐‐‐1.01.01.0

328203282032820 Memphis TNMemphis TNMemphis TNMemphis TN ‐‐‐32.832.832.8 ‐‐‐5.35.35.3 11.811.811.8 328328328 ‐‐‐2.02.02.0

329003290032900 Merced CAMerced CAMerced CAMerced CA ‐‐‐60.360.360.3 ‐‐‐21.621.621.6 18.718.718.7 315315315 ‐‐‐2.02.02.0

331243312433124 Miami FL [Metropolitan Division]Miami FL [Metropolitan Division]Miami FL [Metropolitan Division]Miami FL [Metropolitan Division] ‐‐‐12.812.812.8 4.34.34.3 30.130.130.1 118118118 0.00.00.0

331403314033140 Michigan City INMichigan City INMichigan City INMichigan City IN ‐‐‐8.58.58.5 1.41.41.4 6.26.26.2 180180180 ‐‐‐1.01.01.0

332603326033260 Midland TXMidland TXMidland TXMidland TX 2.42.42.4 ‐‐‐3.83.83.8 10.310.310.3 292929 0.00.00.0

333403334033340 Milwaukee WIMilwaukee WIMilwaukee WIMilwaukee WI ‐‐‐4.04.04.0 0.20.20.2 10.510.510.5 106106106 0.00.00.0

334603346033460 Minneapolis MNMinneapolis MNMinneapolis MNMinneapolis MN ‐‐‐17.817.817.8 ‐‐‐0.20.20.2 16.516.516.5 174174174 ‐‐‐1.01.01.0

335403354033540 Missoula MTMissoula MTMissoula MTMissoula MT 7.37.37.3 ‐‐‐1.71.71.7 11.311.311.3 141414 1.01.01.0

336603366033660 Mobile ALMobile ALMobile ALMobile AL ‐‐‐23.523.523.5 ‐‐‐2.22.22.2 8.78.78.7 345345345 ‐‐‐2.02.02.0

337003370033700 Modesto CAModesto CAModesto CAModesto CA ‐‐‐31.731.731.7 15.215.215.2 23.123.123.1 231231231 ‐‐‐1.01.01.0

337403374033740 Monroe LAMonroe LAMonroe LAMonroe LA ‐‐‐5.35.35.3 ‐‐‐3.23.23.2 6.26.26.2 494949 0.00.00.0

337803378033780 Monroe MIMonroe MIMonroe MIMonroe MI ‐‐‐17.517.517.5 0.40.40.4 9.49.49.4 254254254 ‐‐‐2.02.02.0



338603386033860 Montgomery ALMontgomery ALMontgomery ALMontgomery AL ‐‐‐10.210.210.2 ‐‐‐2.92.92.9 6.06.06.0 173173173 ‐‐‐1.01.01.0

340603406034060 Morgantown WVMorgantown WVMorgantown WVMorgantown WV ‐‐‐5.05.05.0 ‐‐‐3.73.73.7 7.07.07.0 777777 0.00.00.0

341003410034100 Morristown TNMorristown TNMorristown TNMorristown TN ‐‐‐1.71.71.7 ‐‐‐2.12.12.1 11.511.511.5 555555 0.00.00.0

345803458034580 Mount Vernon WAMount Vernon WAMount Vernon WAMount Vernon WA ‐‐‐18.018.018.0 0.00.00.0 7.47.47.4 312312312 ‐‐‐2.02.02.0

346203462034620 Muncie INMuncie INMuncie INMuncie IN ‐‐‐14.114.114.1 ‐‐‐2.12.12.1 5.05.05.0 314314314 ‐‐‐2.02.02.0

347403474034740 Muskegon MIMuskegon MIMuskegon MIMuskegon MI ‐‐‐23.223.223.2 ‐‐‐1.31.31.3 7.47.47.4 374374374 ‐‐‐2.02.02.0

348203482034820 Myrtle Beach SCMyrtle Beach SCMyrtle Beach SCMyrtle Beach SC ‐‐‐15.515.515.5 ‐‐‐3.83.83.8 9.29.29.2 227227227 ‐‐‐1.01.01.0

349003490034900 Napa CANapa CANapa CANapa CA ‐‐‐30.530.530.5 6.96.96.9 16.416.416.4 311311311 ‐‐‐2.02.02.0

349403494034940 Naples FLNaples FLNaples FLNaples FL ‐‐‐7.27.27.2 3.73.73.7 20.820.820.8 969696 0.00.00.0

349803498034980 Nashville TNNashville TNNashville TNNashville TN 2.52.52.5 ‐‐‐0.70.70.7 8.78.78.7 444444 0.00.00.0

350043500435004 Nassau NY [Metropolitan Division]Nassau NY [Metropolitan Division]Nassau NY [Metropolitan Division]Nassau NY [Metropolitan Division] ‐‐‐3.13.13.1 7.67.67.6 16.516.516.5 919191 0.00.00.0

353003530035300 New Haven CTNew Haven CTNew Haven CTNew Haven CT ‐‐‐23.023.023.0 0.50.50.5 17.117.117.1 327327327 ‐‐‐2.02.02.0

353803538035380 New Orleans LANew Orleans LANew Orleans LANew Orleans LA ‐‐‐26.526.526.5 6.16.16.1 108.8108.8108.8 363363363 ‐‐‐2.02.02.0

356443564435644 New York NY [Metropolitan Division]New York NY [Metropolitan Division]New York NY [Metropolitan Division]New York NY [Metropolitan Division] ‐‐‐8.38.38.3 5.95.95.9 15.415.415.4 136136136 0.00.00.0

350843508435084 Newark NJ [Metropolitan Division]Newark NJ [Metropolitan Division]Newark NJ [Metropolitan Division]Newark NJ [Metropolitan Division] ‐‐‐10.810.810.8 3.73.73.7 15.115.115.1 170170170 ‐‐‐1.01.01.0

356603566035660 Niles MINiles MINiles MINiles MI ‐‐‐21.121.121.1 1.31.31.3 5.85.85.8 384384384 ‐‐‐2.02.02.0

358403584035840 North Port FLNorth Port FLNorth Port FLNorth Port FL ‐‐‐29.529.529.5 ‐‐‐1.61.61.6 12.412.412.4 310310310 ‐‐‐2.02.02.0

359803598035980 Norwich CTNorwich CTNorwich CTNorwich CT ‐‐‐23.623.623.6 ‐‐‐0.50.50.5 17.917.917.9 308308308 ‐‐‐2.02.02.0

360843608436084 Oakland CA [Metropolitan Division]Oakland CA [Metropolitan Division]Oakland CA [Metropolitan Division]Oakland CA [Metropolitan Division] ‐‐‐29.329.329.3 5.25.25.2 16.716.716.7 286286286 ‐‐‐2.02.02.0

361003610036100 Ocala FLOcala FLOcala FLOcala FL ‐‐‐35.635.635.6 ‐‐‐7.87.87.8 12.612.612.6 320320320 ‐‐‐2.02.02.0

361403614036140 Ocean City NJOcean City NJOcean City NJOcean City NJ ‐‐‐15.915.915.9 5.35.35.3 14.514.514.5 251251251 ‐‐‐2.02.02.0

362203622036220 Odessa TXOdessa TXOdessa TXOdessa TX 3.73.73.7 ‐‐‐3.03.03.0 11.311.311.3 404040 0.00.00.0

362603626036260 Ogden UTOgden UTOgden UTOgden UT ‐‐‐10.710.710.7 ‐‐‐2.32.32.3 7.47.47.4 177177177 ‐‐‐1.01.01.0

364203642036420 Oklahoma City OKOklahoma City OKOklahoma City OKOklahoma City OK ‐‐‐4.64.64.6 ‐‐‐4.54.54.5 6.36.36.3 979797 0.00.00.0

365003650036500 Olympia WAOlympia WAOlympia WAOlympia WA ‐‐‐23.223.223.2 ‐‐‐1.61.61.6 8.28.28.2 372372372 ‐‐‐2.02.02.0

365403654036540 Omaha NEOmaha NEOmaha NEOmaha NE ‐‐‐13.013.013.0 ‐‐‐3.63.63.6 4.44.44.4 272272272 ‐‐‐2.02.02.0

367403674036740 Orlando FLOrlando FLOrlando FLOrlando FL ‐‐‐30.230.230.2 ‐‐‐3.03.03.0 17.117.117.1 242242242 ‐‐‐1.01.01.0

367803678036780 Oshkosh WIOshkosh WIOshkosh WIOshkosh WI ‐‐‐14.214.214.2 ‐‐‐2.82.82.8 4.44.44.4 333333333 ‐‐‐2.02.02.0

369803698036980 Owensboro KYOwensboro KYOwensboro KYOwensboro KY ‐‐‐5.95.95.9 ‐‐‐0.30.30.3 4.34.34.3 200200200 ‐‐‐1.01.01.0

371003710037100 Oxnard CAOxnard CAOxnard CAOxnard CA ‐‐‐11.011.011.0 17.417.417.4 17.017.017.0 184184184 ‐‐‐1.01.01.0

373403734037340 Palm Bay FLPalm Bay FLPalm Bay FLPalm Bay FL ‐‐‐29.529.529.5 ‐‐‐4.24.24.2 15.515.515.5 237237237 ‐‐‐1.01.01.0

373803738037380 Palm Coast FLPalm Coast FLPalm Coast FLPalm Coast FL ‐‐‐12.512.512.5 ‐‐‐3.83.83.8 10.610.610.6 171171171 ‐‐‐1.01.01.0

374603746037460 Panama City FLPanama City FLPanama City FLPanama City FL ‐‐‐31.831.831.8 ‐‐‐1.91.91.9 11.811.811.8 329329329 ‐‐‐2.02.02.0

376203762037620 Parkersburg WVParkersburg WVParkersburg WVParkersburg WV ‐‐‐6.06.06.0 ‐‐‐2.72.72.7 4.04.04.0 159159159 ‐‐‐1.01.01.0

377003770037700 Pascagoula MSPascagoula MSPascagoula MSPascagoula MS ‐‐‐15.115.115.1 ‐‐‐2.42.42.4 11.411.411.4 149149149 ‐‐‐1.01.01.0

377643776437764 Peabody MAPeabody MAPeabody MAPeabody MA ‐‐‐20.320.320.3 3.73.73.7 17.017.017.0 301301301 ‐‐‐2.02.02.0

378603786037860 Pensacola FLPensacola FLPensacola FLPensacola FL ‐‐‐17.617.617.6 ‐‐‐3.73.73.7 11.411.411.4 221221221 ‐‐‐1.01.01.0

379003790037900 Peoria ILPeoria ILPeoria ILPeoria IL ‐‐‐5.95.95.9 ‐‐‐2.52.52.5 5.45.45.4 153153153 ‐‐‐1.01.01.0

379643796437964 Philadelphia PA [Metropolitan Division]Philadelphia PA [Metropolitan Division]Philadelphia PA [Metropolitan Division]Philadelphia PA [Metropolitan Division] ‐‐‐8.78.78.7 1.31.31.3 9.69.69.6 185185185 ‐‐‐1.01.01.0

380603806038060 Phoenix AZPhoenix AZPhoenix AZPhoenix AZ ‐‐‐34.834.834.8 ‐‐‐4.64.64.6 17.617.617.6 265265265 ‐‐‐2.02.02.0

382203822038220 Pine Bluff ARPine Bluff ARPine Bluff ARPine Bluff AR ‐‐‐6.56.56.5 ‐‐‐3.03.03.0 6.96.96.9 166166166 ‐‐‐1.01.01.0

383003830038300 Pittsburgh PAPittsburgh PAPittsburgh PAPittsburgh PA ‐‐‐7.07.07.0 ‐‐‐0.40.40.4 2.82.82.8 371371371 ‐‐‐2.02.02.0

383403834038340 Pittsfield MAPittsfield MAPittsfield MAPittsfield MA ‐‐‐20.420.420.4 2.12.12.1 19.619.619.6 288288288 ‐‐‐2.02.02.0

385403854038540 Pocatello IDPocatello IDPocatello IDPocatello ID ‐‐‐7.77.77.7 ‐‐‐1.81.81.8 6.16.16.1 114114114 0.00.00.0

389403894038940 Port St. Lucie FLPort St. Lucie FLPort St. Lucie FLPort St. Lucie FL ‐‐‐35.935.935.9 ‐‐‐2.82.82.8 15.015.015.0 309309309 ‐‐‐2.02.02.0

388603886038860 Portland MEPortland MEPortland MEPortland ME ‐‐‐12.512.512.5 0.60.60.6 11.311.311.3 230230230 ‐‐‐1.01.01.0

389003890038900 Portland ORPortland ORPortland ORPortland OR ‐‐‐14.614.614.6 ‐‐‐1.91.91.9 12.212.212.2 179179179 ‐‐‐1.01.01.0

391003910039100 Poughkeepsie NYPoughkeepsie NYPoughkeepsie NYPoughkeepsie NY ‐‐‐13.113.113.1 2.92.92.9 13.213.213.2 215215215 ‐‐‐1.01.01.0

391403914039140 Prescott AZPrescott AZPrescott AZPrescott AZ ‐‐‐25.425.425.4 0.50.50.5 16.916.916.9 233233233 ‐‐‐1.01.01.0

393003930039300 Providence RIProvidence RIProvidence RIProvidence RI ‐‐‐20.320.320.3 2.62.62.6 14.214.214.2 298298298 ‐‐‐2.02.02.0

393403934039340 Provo UTProvo UTProvo UTProvo UT ‐‐‐7.67.67.6 ‐‐‐1.71.71.7 7.97.97.9 134134134 0.00.00.0

393803938039380 Pueblo COPueblo COPueblo COPueblo CO ‐‐‐22.922.922.9 ‐‐‐3.83.83.8 7.17.17.1 367367367 ‐‐‐2.02.02.0

394603946039460 Punta Gorda FLPunta Gorda FLPunta Gorda FLPunta Gorda FL ‐‐‐35.035.035.0 1.91.91.9 18.018.018.0 255255255 ‐‐‐2.02.02.0

395403954039540 Racine WIRacine WIRacine WIRacine WI ‐‐‐10.910.910.9 ‐‐‐1.71.71.7 7.97.97.9 169169169 ‐‐‐1.01.01.0

395803958039580 Raleigh NCRaleigh NCRaleigh NCRaleigh NC 6.16.16.1 0.40.40.4 7.17.17.1 666 1.01.01.0

396603966039660 Rapid City SDRapid City SDRapid City SDRapid City SD ‐‐‐4.54.54.5 ‐‐‐0.90.90.9 7.47.47.4 757575 0.00.00.0

397403974039740 Reading PAReading PAReading PAReading PA 2.92.92.9 1.01.01.0 9.49.49.4 343434 0.00.00.0

398203982039820 Redding CARedding CARedding CARedding CA ‐‐‐61.361.361.3 ‐‐‐41.841.841.8 7.37.37.3 313313313 ‐‐‐2.02.02.0

399003990039900 Reno NVReno NVReno NVReno NV ‐‐‐23.323.323.3 0.40.40.4 16.616.616.6 161161161 ‐‐‐1.01.01.0

400604006040060 Richmond VARichmond VARichmond VARichmond VA 8.48.48.4 1.41.41.4 12.812.812.8 202020 0.00.00.0

401404014040140 Riverside CARiverside CARiverside CARiverside CA ‐‐‐26.926.926.9 2.02.02.0 16.116.116.1 232232232 ‐‐‐1.01.01.0



402204022040220 Roanoke VARoanoke VARoanoke VARoanoke VA 6.56.56.5 2.62.62.6 7.57.57.5 151515 1.01.01.0

403404034040340 Rochester MNRochester MNRochester MNRochester MN ‐‐‐11.611.611.6 ‐‐‐2.82.82.8 5.15.15.1 253253253 ‐‐‐2.02.02.0

403804038040380 Rochester NYRochester NYRochester NYRochester NY ‐‐‐14.214.214.2 ‐‐‐2.12.12.1 11.711.711.7 229229229 ‐‐‐1.01.01.0

404204042040420 Rockford ILRockford ILRockford ILRockford IL ‐‐‐13.713.713.7 ‐‐‐3.53.53.5 4.34.34.3 217217217 ‐‐‐1.01.01.0

404844048440484 Rockingham County NH [Metropolitan Division]Rockingham County NH [Metropolitan Division]Rockingham County NH [Metropolitan Division]Rockingham County NH [Metropolitan Division] ‐‐‐19.319.319.3 0.30.30.3 17.817.817.8 293293293 ‐‐‐2.02.02.0

405804058040580 Rocky Mount NCRocky Mount NCRocky Mount NCRocky Mount NC ‐‐‐15.715.715.7 ‐‐‐1.61.61.6 4.14.14.1 368368368 ‐‐‐2.02.02.0

406604066040660 Rome GARome GARome GARome GA ‐‐‐3.43.43.4 1.61.61.6 9.39.39.3 616161 0.00.00.0

409004090040900 Sacramento CASacramento CASacramento CASacramento CA ‐‐‐48.948.948.9 ‐‐‐16.416.416.4 13.313.313.3 324324324 ‐‐‐2.02.02.0

409804098040980 Saginaw MISaginaw MISaginaw MISaginaw MI ‐‐‐22.522.522.5 ‐‐‐2.12.12.1 7.77.77.7 361361361 ‐‐‐2.02.02.0

414204142041420 Salem ORSalem ORSalem ORSalem OR ‐‐‐18.818.818.8 ‐‐‐3.13.13.1 9.39.39.3 250250250 ‐‐‐2.02.02.0

415004150041500 Salinas CASalinas CASalinas CASalinas CA ‐‐‐51.951.951.9 ‐‐‐10.810.810.8 20.320.320.3 331331331 ‐‐‐2.02.02.0

415404154041540 Salisbury MDSalisbury MDSalisbury MDSalisbury MD ‐‐‐28.428.428.4 ‐‐‐6.36.36.3 10.710.710.7 323323323 ‐‐‐2.02.02.0

416204162041620 Salt Lake City UTSalt Lake City UTSalt Lake City UTSalt Lake City UT ‐‐‐4.24.24.2 1.01.01.0 10.010.010.0 878787 0.00.00.0

416604166041660 San Angelo TXSan Angelo TXSan Angelo TXSan Angelo TX ‐‐‐0.30.30.3 ‐‐‐1.41.41.4 7.07.07.0 353535 0.00.00.0

417004170041700 San Antonio TXSan Antonio TXSan Antonio TXSan Antonio TX ‐‐‐4.44.44.4 ‐‐‐5.45.45.4 8.88.88.8 838383 0.00.00.0

417404174041740 San Diego CASan Diego CASan Diego CASan Diego CA ‐‐‐31.131.131.1 ‐‐‐6.36.36.3 11.711.711.7 321321321 ‐‐‐2.02.02.0

418844188441884 San Francisco CA [Metropolitan Division]San Francisco CA [Metropolitan Division]San Francisco CA [Metropolitan Division]San Francisco CA [Metropolitan Division] ‐‐‐22.122.122.1 3.83.83.8 13.513.513.5 341341341 ‐‐‐2.02.02.0

419404194041940 San Jose CASan Jose CASan Jose CASan Jose CA ‐‐‐24.624.624.6 3.33.33.3 14.814.814.8 282282282 ‐‐‐2.02.02.0

420204202042020 San Luis Obispo CASan Luis Obispo CASan Luis Obispo CASan Luis Obispo CA ‐‐‐40.240.240.2 ‐‐‐4.34.34.3 14.914.914.9 377377377 ‐‐‐2.02.02.0

417804178041780 Sandusky OHSandusky OHSandusky OHSandusky OH ‐‐‐27.727.727.7 ‐‐‐1.71.71.7 7.27.27.2 383383383 ‐‐‐2.02.02.0

420444204442044 Santa Ana CA [Metropolitan Division]Santa Ana CA [Metropolitan Division]Santa Ana CA [Metropolitan Division]Santa Ana CA [Metropolitan Division] ‐‐‐13.513.513.5 ‐‐‐3.33.33.3 13.813.813.8 150150150 ‐‐‐1.01.01.0

420604206042060 Santa Barbara CASanta Barbara CASanta Barbara CASanta Barbara CA ‐‐‐28.128.128.1 10.510.510.5 20.020.020.0 225225225 ‐‐‐1.01.01.0

421004210042100 Santa Cruz CASanta Cruz CASanta Cruz CASanta Cruz CA ‐‐‐40.940.940.9 6.56.56.5 19.419.419.4 369369369 ‐‐‐2.02.02.0

421404214042140 Santa Fe NMSanta Fe NMSanta Fe NMSanta Fe NM ‐‐‐11.611.611.6 ‐‐‐2.92.92.9 5.85.85.8 205205205 ‐‐‐1.01.01.0

422204222042220 Santa Rosa CASanta Rosa CASanta Rosa CASanta Rosa CA ‐‐‐50.650.650.6 ‐‐‐25.525.525.5 10.310.310.3 349349349 ‐‐‐2.02.02.0

423404234042340 Savannah GASavannah GASavannah GASavannah GA 2.22.22.2 3.23.23.2 13.513.513.5 535353 0.00.00.0

425404254042540 Scranton PAScranton PAScranton PAScranton PA ‐‐‐4.04.04.0 4.94.94.9 6.86.86.8 989898 0.00.00.0

426444264442644 Seattle WA [Metropolitan Division]Seattle WA [Metropolitan Division]Seattle WA [Metropolitan Division]Seattle WA [Metropolitan Division] ‐‐‐19.119.119.1 ‐‐‐1.21.21.2 9.49.49.4 300300300 ‐‐‐2.02.02.0

426804268042680 Sebastian FLSebastian FLSebastian FLSebastian FL ‐‐‐34.234.234.2 ‐‐‐1.21.21.2 13.413.413.4 330330330 ‐‐‐2.02.02.0

431004310043100 Sheboygan WISheboygan WISheboygan WISheboygan WI ‐‐‐11.511.511.5 ‐‐‐1.41.41.4 6.36.36.3 222222222 ‐‐‐1.01.01.0

433004330043300 Sherman TXSherman TXSherman TXSherman TX ‐‐‐16.416.416.4 ‐‐‐5.55.55.5 8.48.48.4 213213213 ‐‐‐1.01.01.0

433404334043340 Shreveport LAShreveport LAShreveport LAShreveport LA ‐‐‐5.25.25.2 ‐‐‐4.94.94.9 7.57.57.5 626262 0.00.00.0

435804358043580 Sioux City IASioux City IASioux City IASioux City IA ‐‐‐9.59.59.5 ‐‐‐3.43.43.4 4.94.94.9 223223223 ‐‐‐1.01.01.0

436204362043620 Sioux Falls SDSioux Falls SDSioux Falls SDSioux Falls SD ‐‐‐6.16.16.1 ‐‐‐2.42.42.4 4.14.14.1 120120120 0.00.00.0

437804378043780 South Bend INSouth Bend INSouth Bend INSouth Bend IN ‐‐‐15.015.015.0 ‐‐‐1.21.21.2 5.15.15.1 337337337 ‐‐‐2.02.02.0

439004390043900 Spartanburg SCSpartanburg SCSpartanburg SCSpartanburg SC ‐‐‐3.63.63.6 0.20.20.2 5.45.45.4 100100100 0.00.00.0

440604406044060 Spokane WASpokane WASpokane WASpokane WA ‐‐‐15.815.815.8 ‐‐‐2.72.72.7 7.57.57.5 278278278 ‐‐‐2.02.02.0

441004410044100 Springfield ILSpringfield ILSpringfield ILSpringfield IL ‐‐‐12.612.612.6 ‐‐‐3.53.53.5 6.66.66.6 239239239 ‐‐‐1.01.01.0

441404414044140 Springfield MASpringfield MASpringfield MASpringfield MA ‐‐‐16.016.016.0 3.83.83.8 16.616.616.6 247247247 ‐‐‐1.01.01.0

441804418044180 Springfield MOSpringfield MOSpringfield MOSpringfield MO ‐‐‐10.510.510.5 ‐‐‐2.82.82.8 5.65.65.6 201201201 ‐‐‐1.01.01.0

442204422044220 Springfield OHSpringfield OHSpringfield OHSpringfield OH ‐‐‐16.216.216.2 ‐‐‐1.61.61.6 7.07.07.0 362362362 ‐‐‐2.02.02.0

410604106041060 St. Cloud MNSt. Cloud MNSt. Cloud MNSt. Cloud MN ‐‐‐10.110.110.1 ‐‐‐1.21.21.2 8.08.08.0 158158158 ‐‐‐1.01.01.0

411004110041100 St. George UTSt. George UTSt. George UTSt. George UT ‐‐‐19.819.819.8 ‐‐‐4.24.24.2 8.28.28.2 202202202 ‐‐‐1.01.01.0

411404114041140 St. Joseph MOSt. Joseph MOSt. Joseph MOSt. Joseph MO ‐‐‐8.68.68.6 1.51.51.5 7.47.47.4 117117117 0.00.00.0

411804118041180 St. Louis MOSt. Louis MOSt. Louis MOSt. Louis MO ‐‐‐5.75.75.7 ‐‐‐0.90.90.9 6.46.46.4 108108108 0.00.00.0

443004430044300 State College PAState College PAState College PAState College PA 11.811.811.8 4.54.54.5 6.16.16.1 222 1.01.01.0

446004460044600 Steubenville OHSteubenville OHSteubenville OHSteubenville OH ‐‐‐7.67.67.6 0.40.40.4 7.07.07.0 164164164 ‐‐‐1.01.01.0

447004470044700 Stockton CAStockton CAStockton CAStockton CA ‐‐‐47.747.747.7 ‐‐‐12.612.612.6 16.116.116.1 296296296 ‐‐‐2.02.02.0

449404494044940 Sumter SCSumter SCSumter SCSumter SC 10.410.410.4 ‐‐‐0.10.10.1 6.96.96.9 131313 1.01.01.0

450604506045060 Syracuse NYSyracuse NYSyracuse NYSyracuse NY ‐‐‐17.917.917.9 ‐‐‐2.12.12.1 9.99.99.9 256256256 ‐‐‐2.02.02.0

451044510445104 Tacoma WA [Metropolitan Division]Tacoma WA [Metropolitan Division]Tacoma WA [Metropolitan Division]Tacoma WA [Metropolitan Division] ‐‐‐33.833.833.8 ‐‐‐3.43.43.4 9.89.89.8 380380380 ‐‐‐2.02.02.0

452204522045220 Tallahassee FLTallahassee FLTallahassee FLTallahassee FL ‐‐‐18.318.318.3 ‐‐‐9.79.79.7 10.710.710.7 206206206 ‐‐‐1.01.01.0

453004530045300 Tampa FLTampa FLTampa FLTampa FL ‐‐‐28.728.728.7 ‐‐‐2.42.42.4 12.612.612.6 280280280 ‐‐‐2.02.02.0

454604546045460 Terre Haute INTerre Haute INTerre Haute INTerre Haute IN ‐‐‐15.015.015.0 ‐‐‐1.31.31.3 5.15.15.1 359359359 ‐‐‐2.02.02.0

455004550045500 Texarkana TXTexarkana TXTexarkana TXTexarkana TX ‐‐‐6.56.56.5 ‐‐‐5.55.55.5 7.27.27.2 132132132 0.00.00.0

457804578045780 Toledo OHToledo OHToledo OHToledo OH ‐‐‐24.024.024.0 ‐‐‐2.92.92.9 6.86.86.8 375375375 ‐‐‐2.02.02.0

458204582045820 Topeka KSTopeka KSTopeka KSTopeka KS ‐‐‐14.214.214.2 ‐‐‐4.14.14.1 4.74.74.7 267267267 ‐‐‐2.02.02.0

459404594045940 Trenton NJTrenton NJTrenton NJTrenton NJ ‐‐‐13.713.713.7 1.51.51.5 15.215.215.2 210210210 ‐‐‐1.01.01.0

460604606046060 Tucson AZTucson AZTucson AZTucson AZ ‐‐‐33.833.833.8 ‐‐‐5.15.15.1 11.711.711.7 344344344 ‐‐‐2.02.02.0

461404614046140 Tulsa OKTulsa OKTulsa OKTulsa OK ‐‐‐6.36.36.3 ‐‐‐2.82.82.8 6.06.06.0 129129129 0.00.00.0

462204622046220 Tuscaloosa ALTuscaloosa ALTuscaloosa ALTuscaloosa AL ‐‐‐4.24.24.2 ‐‐‐0.50.50.5 4.94.94.9 122122122 0.00.00.0



463404634046340 Tyler TXTyler TXTyler TXTyler TX ‐‐‐6.16.16.1 ‐‐‐3.83.83.8 6.16.16.1 113113113 0.00.00.0

465404654046540 Utica NYUtica NYUtica NYUtica NY ‐‐‐6.46.46.4 4.04.04.0 8.98.98.9 124124124 0.00.00.0

466604666046660 Valdosta GAValdosta GAValdosta GAValdosta GA ‐‐‐4.84.84.8 ‐‐‐0.50.50.5 8.08.08.0 676767 0.00.00.0

467004670046700 Vallejo CAVallejo CAVallejo CAVallejo CA ‐‐‐48.648.648.6 ‐‐‐16.316.316.3 17.317.317.3 306306306 ‐‐‐2.02.02.0

470204702047020 Victoria TXVictoria TXVictoria TXVictoria TX ‐‐‐19.019.019.0 ‐‐‐5.15.15.1 14.814.814.8 194194194 ‐‐‐1.01.01.0

472204722047220 Vineland NJVineland NJVineland NJVineland NJ ‐‐‐7.47.47.4 6.66.66.6 9.09.09.0 126126126 0.00.00.0

472604726047260 Virginia Beach VAVirginia Beach VAVirginia Beach VAVirginia Beach VA ‐‐‐2.02.02.0 ‐‐‐2.02.02.0 11.011.011.0 545454 0.00.00.0

473004730047300 Visalia CAVisalia CAVisalia CAVisalia CA ‐‐‐64.664.664.6 ‐‐‐38.138.138.1 12.212.212.2 290290290 ‐‐‐2.02.02.0

473804738047380 Waco TXWaco TXWaco TXWaco TX ‐‐‐1.91.91.9 ‐‐‐3.03.03.0 6.66.66.6 686868 0.00.00.0

475804758047580 Warner Robins GAWarner Robins GAWarner Robins GAWarner Robins GA ‐‐‐10.910.910.9 ‐‐‐1.61.61.6 5.75.75.7 203203203 ‐‐‐1.01.01.0

476444764447644 Warren MI [Metropolitan Division]Warren MI [Metropolitan Division]Warren MI [Metropolitan Division]Warren MI [Metropolitan Division] ‐‐‐31.031.031.0 ‐‐‐0.80.80.8 13.213.213.2 326326326 ‐‐‐2.02.02.0

478944789447894 Washington DC [Metropolitan Division]Washington DC [Metropolitan Division]Washington DC [Metropolitan Division]Washington DC [Metropolitan Division] ‐‐‐8.48.48.4 0.10.10.1 14.014.014.0 140140140 0.00.00.0

479404794047940 Waterloo IAWaterloo IAWaterloo IAWaterloo IA 3.73.73.7 ‐‐‐1.11.11.1 9.69.69.6 454545 0.00.00.0

481404814048140 Wausau WIWausau WIWausau WIWausau WI ‐‐‐5.65.65.6 ‐‐‐1.11.11.1 4.74.74.7 147147147 ‐‐‐1.01.01.0

483004830048300 Wenatchee WAWenatchee WAWenatchee WAWenatchee WA ‐‐‐16.416.416.4 ‐‐‐1.01.01.0 6.96.96.9 317317317 ‐‐‐2.02.02.0

484244842448424 West Palm Beach FL [Metropolitan Division]West Palm Beach FL [Metropolitan Division]West Palm Beach FL [Metropolitan Division]West Palm Beach FL [Metropolitan Division] ‐‐‐23.723.723.7 ‐‐‐0.30.30.3 15.515.515.5 204204204 ‐‐‐1.01.01.0

485404854048540 Wheeling WVWheeling WVWheeling WVWheeling WV ‐‐‐5.35.35.3 ‐‐‐2.12.12.1 4.74.74.7 142142142 0.00.00.0

486604866048660 Wichita Falls TXWichita Falls TXWichita Falls TXWichita Falls TX ‐‐‐8.08.08.0 ‐‐‐4.24.24.2 6.06.06.0 123123123 0.00.00.0

486204862048620 Wichita KSWichita KSWichita KSWichita KS ‐‐‐11.211.211.2 ‐‐‐4.04.04.0 6.26.26.2 191191191 ‐‐‐1.01.01.0

487004870048700 Williamsport PAWilliamsport PAWilliamsport PAWilliamsport PA ‐‐‐3.63.63.6 4.84.84.8 7.87.87.8 151151151 ‐‐‐1.01.01.0

488644886448864 Wilmington DE [Metropolitan Division]Wilmington DE [Metropolitan Division]Wilmington DE [Metropolitan Division]Wilmington DE [Metropolitan Division] ‐‐‐15.015.015.0 ‐‐‐1.11.11.1 8.78.78.7 261261261 ‐‐‐2.02.02.0

489004890048900 Wilmington NCWilmington NCWilmington NCWilmington NC ‐‐‐10.010.010.0 ‐‐‐1.61.61.6 10.210.210.2 116116116 0.00.00.0

490204902049020 Winchester VAWinchester VAWinchester VAWinchester VA ‐‐‐19.919.919.9 ‐‐‐3.03.03.0 10.710.710.7 281281281 ‐‐‐2.02.02.0

491804918049180 Winston NCWinston NCWinston NCWinston NC 1.71.71.7 0.60.60.6 5.15.15.1 282828 0.00.00.0

493404934049340 Worcester MAWorcester MAWorcester MAWorcester MA ‐‐‐27.327.327.3 1.11.11.1 17.717.717.7 348348348 ‐‐‐2.02.02.0

494204942049420 Yakima WAYakima WAYakima WAYakima WA ‐‐‐17.717.717.7 ‐‐‐1.31.31.3 7.77.77.7 358358358 ‐‐‐2.02.02.0

496204962049620 York PAYork PAYork PAYork PA ‐‐‐1.41.41.4 1.41.41.4 7.67.67.6 585858 0.00.00.0

496604966049660 Youngstown OHYoungstown OHYoungstown OHYoungstown OH ‐‐‐22.322.322.3 ‐‐‐0.80.80.8 7.87.87.8 376376376 ‐‐‐2.02.02.0

497004970049700 Yuba City CAYuba City CAYuba City CAYuba City CA ‐‐‐39.839.839.8 ‐‐‐3.23.23.2 13.413.413.4 350350350 ‐‐‐2.02.02.0

497404974049740 Yuma AZYuma AZYuma AZYuma AZ ‐‐‐20.620.620.6 ‐‐‐2.02.02.0 14.514.514.5 182182182 ‐‐‐1.01.01.0



LHPILHPI®®

Incorporating data through 2011Q2Incorporating data through 2011Q2Incorporating data through 2011Q2


FIPFIPFIPFIP Metro AreaMetro AreaMetro AreaMetro Area LHPI, %LHPI, %LHPI, %LHPI, % House Price House Price House Price House Price Overvaluation, %Overvaluation, %Overvaluation, %Overvaluation, %

NonNonNonNon‐‐‐‐Housing Housing Housing Housing Employment, Employment, Employment, Employment, Y/Y % chgY/Y % chgY/Y % chgY/Y % chg

Housing Housing Housing Housing Affordability IndexAffordability IndexAffordability IndexAffordability Index

Excess Supply Excess Supply Excess Supply Excess Supply Indicator, MonthsIndicator, MonthsIndicator, MonthsIndicator, Months

Q/Q Price Change Q/Q Price Change Q/Q Price Change Q/Q Price Change (Decline=1)(Decline=1)(Decline=1)(Decline=1)

Y/Y Price Change Y/Y Price Change Y/Y Price Change Y/Y Price Change (Decline=1)(Decline=1)(Decline=1)(Decline=1)

101801018010180 Abilene TXAbilene TXAbilene TXAbilene TX 49.449.449.4 ‐‐‐3.63.63.6 ‐‐‐3.23.23.2 234234234 ‐‐‐8.48.48.4 111 111

104201042010420 Akron OHAkron OHAkron OHAkron OH 11.411.411.4 ‐‐‐20.820.820.8 2.12.12.1 325325325 ‐‐‐5.05.05.0 111 111

105001050010500 Albany GAAlbany GAAlbany GAAlbany GA 60.060.060.0 ‐‐‐4.64.64.6 3.13.13.1 253253253 ‐‐‐3.73.73.7 000 111

105801058010580 Albany NYAlbany NYAlbany NYAlbany NY 29.929.929.9 9.39.39.3 ‐‐‐1.21.21.2 199199199 ‐‐‐2.22.22.2 111 111

107401074010740 Albuquerque NMAlbuquerque NMAlbuquerque NMAlbuquerque NM 61.061.061.0 ‐‐‐7.67.67.6 ‐‐‐0.20.20.2 171171171 ‐‐‐6.36.36.3 111 111

107801078010780 Alexandria LAAlexandria LAAlexandria LAAlexandria LA 40.640.640.6 ‐‐‐4.94.94.9 2.92.92.9 275275275 ‐‐‐0.50.50.5 000 000

109001090010900 Allentown PAAllentown PAAllentown PAAllentown PA 40.440.440.4 ‐‐‐17.617.617.6 0.80.80.8 185185185 ‐‐‐2.62.62.6 111 111

110201102011020 Altoona PAAltoona PAAltoona PAAltoona PA 44.044.044.0 10.110.110.1 1.01.01.0 262262262 ‐‐‐5.95.95.9 000 000

111001110011100 Amarillo TXAmarillo TXAmarillo TXAmarillo TX 20.620.620.6 2.82.82.8 1.81.81.8 220220220 ‐‐‐6.56.56.5 111 111

111801118011180 Ames IAAmes IAAmes IAAmes IA 5.75.75.7 ‐‐‐8.18.18.1 ‐‐‐2.32.32.3 279279279 ‐‐‐7.37.37.3 000 111

112601126011260 Anchorage AKAnchorage AKAnchorage AKAnchorage AK 32.932.932.9 ‐‐‐10.910.910.9 0.80.80.8 204204204 ‐‐‐10.310.310.3 111 000

113001130011300 Anderson INAnderson INAnderson INAnderson IN 61.361.361.3 ‐‐‐12.612.612.6 ‐‐‐2.92.92.9 327327327 ‐‐‐7.67.67.6 111 111

113401134011340 Anderson SCAnderson SCAnderson SCAnderson SC 51.651.651.6 ‐‐‐2.62.62.6 5.05.05.0 270270270 ‐‐‐4.44.44.4 111 111

114601146011460 Ann Arbor MIAnn Arbor MIAnn Arbor MIAnn Arbor MI 26.526.526.5 ‐‐‐12.512.512.5 0.60.60.6 256256256 ‐‐‐6.66.66.6 111 111

115001150011500 Anniston ALAnniston ALAnniston ALAnniston AL 43.243.243.2 ‐‐‐2.32.32.3 1.01.01.0 263263263 ‐‐‐3.23.23.2 111 111

115401154011540 Appleton WIAppleton WIAppleton WIAppleton WI 21.721.721.7 ‐‐‐11.711.711.7 ‐‐‐0.10.10.1 286286286 ‐‐‐5.35.35.3 111 111

117001170011700 Asheville NCAsheville NCAsheville NCAsheville NC 78.778.778.7 14.114.114.1 0.10.10.1 170170170 ‐‐‐4.64.64.6 111 111

120201202012020 Athens GAAthens GAAthens GAAthens GA 77.977.977.9 5.85.85.8 1.21.21.2 220220220 ‐‐‐3.33.33.3 111 111

120601206012060 Atlanta GAAtlanta GAAtlanta GAAtlanta GA 38.938.938.9 ‐‐‐11.311.311.3 ‐‐‐0.20.20.2 330330330 ‐‐‐5.85.85.8 000 111

121001210012100 Atlantic City NJAtlantic City NJAtlantic City NJAtlantic City NJ 23.723.723.7 ‐‐‐15.215.215.2 ‐‐‐1.61.61.6 143143143 1.71.71.7 111 111

122201222012220 Auburn ALAuburn ALAuburn ALAuburn AL 38.038.038.0 1.51.51.5 2.52.52.5 201201201 ‐‐‐0.70.70.7 111 111

122601226012260 Augusta GAAugusta GAAugusta GAAugusta GA 61.461.461.4 ‐‐‐3.33.33.3 ‐‐‐1.21.21.2 249249249 ‐‐‐4.14.14.1 111 111

124201242012420 Austin TXAustin TXAustin TXAustin TX 63.463.463.4 16.016.016.0 1.51.51.5 178178178 ‐‐‐4.94.94.9 111 111

125401254012540 Bakersfield CABakersfield CABakersfield CABakersfield CA 23.023.023.0 ‐‐‐61.361.361.3 0.00.00.0 201201201 ‐‐‐3.93.93.9 111 111

125801258012580 Baltimore MDBaltimore MDBaltimore MDBaltimore MD 8.28.28.2 ‐‐‐16.716.716.7 ‐‐‐0.10.10.1 179179179 ‐‐‐6.46.46.4 111 111

126201262012620 Bangor MEBangor MEBangor MEBangor ME 22.922.922.9 ‐‐‐16.716.716.7 0.00.00.0 222222222 ‐‐‐1.61.61.6 111 111

127001270012700 Barnstable Town MABarnstable Town MABarnstable Town MABarnstable Town MA 45.845.845.8 ‐‐‐23.123.123.1 1.51.51.5 125125125 ‐‐‐6.96.96.9 111 111

129401294012940 Baton Rouge LABaton Rouge LABaton Rouge LABaton Rouge LA 49.949.949.9 ‐‐‐1.71.71.7 ‐‐‐0.30.30.3 183183183 ‐‐‐2.22.22.2 000 111

129801298012980 Battle Creek MIBattle Creek MIBattle Creek MIBattle Creek MI 70.770.770.7 ‐‐‐15.215.215.2 ‐‐‐0.20.20.2 308308308 ‐‐‐2.52.52.5 111 111

130201302013020 Bay City MIBay City MIBay City MIBay City MI 43.043.043.0 ‐‐‐19.019.019.0 1.01.01.0 342342342 ‐‐‐4.34.34.3 111 111

131401314013140 Beaumont TXBeaumont TXBeaumont TXBeaumont TX 59.959.959.9 ‐‐‐12.912.912.9 1.81.81.8 212212212 ‐‐‐1.91.91.9 111 111

133801338013380 Bellingham WABellingham WABellingham WABellingham WA 54.354.354.3 ‐‐‐17.117.117.1 ‐‐‐1.21.21.2 170170170 ‐‐‐5.85.85.8 111 111

134601346013460 Bend ORBend ORBend ORBend OR 88.788.788.7 ‐‐‐26.826.826.8 ‐‐‐0.50.50.5 236236236 ‐‐‐3.43.43.4 111 111

136441364413644 Bethesda MD [Metropolitan Division]Bethesda MD [Metropolitan Division]Bethesda MD [Metropolitan Division]Bethesda MD [Metropolitan Division] 19.619.619.6 ‐‐‐11.911.911.9 1.51.51.5 162162162 ‐‐‐8.08.08.0 111 111

137401374013740 Billings MTBillings MTBillings MTBillings MT 27.527.527.5 ‐‐‐2.52.52.5 2.92.92.9 257257257 ‐‐‐5.45.45.4 111 111

137801378013780 Binghamton NYBinghamton NYBinghamton NYBinghamton NY 50.050.050.0 ‐‐‐1.01.01.0 0.90.90.9 264264264 ‐‐‐2.72.72.7 111 111

138201382013820 Birmingham ALBirmingham ALBirmingham ALBirmingham AL 75.175.175.1 ‐‐‐1.71.71.7 ‐‐‐0.20.20.2 194194194 ‐‐‐2.22.22.2 111 111

139001390013900 Bismarck NDBismarck NDBismarck NDBismarck ND 26.426.426.4 3.93.93.9 2.02.02.0 239239239 ‐‐‐3.53.53.5 000 000

139801398013980 Blacksburg VABlacksburg VABlacksburg VABlacksburg VA 67.167.167.1 17.717.717.7 0.80.80.8 213213213 ‐‐‐1.71.71.7 000 000

140601406014060 Bloomington ILBloomington ILBloomington ILBloomington IL 21.421.421.4 ‐‐‐8.58.58.5 0.00.00.0 249249249 ‐‐‐5.15.15.1 000 111

140201402014020 Bloomington INBloomington INBloomington INBloomington IN 6.76.76.7 ‐‐‐4.24.24.2 ‐‐‐2.72.72.7 234234234 ‐‐‐6.66.66.6 111 111

142601426014260 Boise City IDBoise City IDBoise City IDBoise City ID 63.763.763.7 ‐‐‐17.217.217.2 0.60.60.6 211211211 ‐‐‐2.42.42.4 111 111

144841448414484 Boston MA [Metropolitan Division]Boston MA [Metropolitan Division]Boston MA [Metropolitan Division]Boston MA [Metropolitan Division] 17.617.617.6 ‐‐‐13.813.813.8 1.41.41.4 123123123 ‐‐‐8.58.58.5 000 111

145001450014500 Boulder COBoulder COBoulder COBoulder CO 28.728.728.7 ‐‐‐3.33.33.3 1.31.31.3 116116116 ‐‐‐8.18.18.1 000 111

145401454014540 Bowling Green KYBowling Green KYBowling Green KYBowling Green KY 14.114.114.1 ‐‐‐6.96.96.9 0.30.30.3 262262262 ‐‐‐4.74.74.7 111 111

147401474014740 Bremerton WABremerton WABremerton WABremerton WA 49.049.049.0 ‐‐‐22.322.322.3 ‐‐‐1.41.41.4 223223223 ‐‐‐5.55.55.5 111 111

148601486014860 Bridgeport CTBridgeport CTBridgeport CTBridgeport CT 33.133.133.1 ‐‐‐15.515.515.5 0.90.90.9 120120120 ‐‐‐7.97.97.9 111 111

151801518015180 Brownsville TXBrownsville TXBrownsville TXBrownsville TX 28.728.728.7 ‐‐‐22.922.922.9 ‐‐‐0.20.20.2 262262262 ‐‐‐4.74.74.7 111 000

152601526015260 Brunswick GABrunswick GABrunswick GABrunswick GA 78.278.278.2 ‐‐‐6.16.16.1 2.12.12.1 206206206 ‐‐‐3.83.83.8 111 111

153801538015380 Buffalo NYBuffalo NYBuffalo NYBuffalo NY 6.86.86.8 ‐‐‐16.416.416.4 0.60.60.6 291291291 ‐‐‐3.33.33.3 111 111

155001550015500 Burlington NCBurlington NCBurlington NCBurlington NC 28.228.228.2 ‐‐‐9.09.09.0 1.01.01.0 246246246 ‐‐‐3.43.43.4 000 111



155401554015540 Burlington VTBurlington VTBurlington VTBurlington VT 57.857.857.8 20.720.720.7 3.33.33.3 133133133 ‐‐‐4.94.94.9 111 111

157641576415764 Cambridge MA [Metropolitan Division]Cambridge MA [Metropolitan Division]Cambridge MA [Metropolitan Division]Cambridge MA [Metropolitan Division] 12.312.312.3 ‐‐‐17.017.017.0 1.11.11.1 139139139 ‐‐‐8.48.48.4 000 111

158041580415804 Camden NJ [Metropolitan Division]Camden NJ [Metropolitan Division]Camden NJ [Metropolitan Division]Camden NJ [Metropolitan Division] 22.022.022.0 ‐‐‐23.123.123.1 ‐‐‐1.11.11.1 226226226 ‐‐‐3.33.33.3 111 111

159401594015940 Canton OHCanton OHCanton OHCanton OH 64.264.264.2 ‐‐‐22.122.122.1 ‐‐‐0.10.10.1 290290290 ‐‐‐3.83.83.8 000 111

159801598015980 Cape Coral FLCape Coral FLCape Coral FLCape Coral FL 60.360.360.3 ‐‐‐34.134.134.1 ‐‐‐0.60.60.6 237237237 ‐‐‐4.74.74.7 000 000

160201602016020 Cape Girardeau MOCape Girardeau MOCape Girardeau MOCape Girardeau MO 24.124.124.1 ‐‐‐14.314.314.3 0.50.50.5 278278278 ‐‐‐8.38.38.3 111 111

161801618016180 Carson City NVCarson City NVCarson City NVCarson City NV 80.680.680.6 ‐‐‐20.620.620.6 0.10.10.1 289289289 ‐‐‐9.99.99.9 111 111

162201622016220 Casper WYCasper WYCasper WYCasper WY 43.643.643.6 ‐‐‐14.714.714.7 1.91.91.9 314314314 ‐‐‐2.32.32.3 111 111

163001630016300 Cedar Rapids IACedar Rapids IACedar Rapids IACedar Rapids IA 13.713.713.7 ‐‐‐9.69.69.6 1.61.61.6 241241241 ‐‐‐2.92.92.9 111 111

165801658016580 Champaign ILChampaign ILChampaign ILChampaign IL 28.628.628.6 ‐‐‐4.34.34.3 ‐‐‐2.62.62.6 220220220 ‐‐‐5.35.35.3 111 111

167001670016700 Charleston SCCharleston SCCharleston SCCharleston SC 76.976.976.9 ‐‐‐1.81.81.8 1.41.41.4 152152152 ‐‐‐2.72.72.7 000 111

166201662016620 Charleston WVCharleston WVCharleston WVCharleston WV 36.136.136.1 ‐‐‐7.37.37.3 1.21.21.2 201201201 ‐‐‐7.27.27.2 111 000

167401674016740 Charlotte NCCharlotte NCCharlotte NCCharlotte NC 63.463.463.4 ‐‐‐14.814.814.8 0.10.10.1 156156156 ‐‐‐3.33.33.3 000 111

168201682016820 Charlottesville VACharlottesville VACharlottesville VACharlottesville VA 54.054.054.0 9.69.69.6 2.12.12.1 182182182 ‐‐‐3.73.73.7 111 111

168601686016860 Chattanooga TNChattanooga TNChattanooga TNChattanooga TN 78.278.278.2 6.16.16.1 1.21.21.2 234234234 ‐‐‐4.84.84.8 111 111

169401694016940 Cheyenne WYCheyenne WYCheyenne WYCheyenne WY 36.136.136.1 ‐‐‐14.114.114.1 0.20.20.2 275275275 ‐‐‐7.37.37.3 000 111

169741697416974 Chicago IL [Metropolitan Division]Chicago IL [Metropolitan Division]Chicago IL [Metropolitan Division]Chicago IL [Metropolitan Division] 67.567.567.5 ‐‐‐17.817.817.8 0.80.80.8 192192192 ‐‐‐8.08.08.0 111 111

170201702017020 Chico CAChico CAChico CAChico CA 27.927.927.9 ‐‐‐56.356.356.3 0.80.80.8 126126126 ‐‐‐4.04.04.0 111 111

171401714017140 Cincinnati OHCincinnati OHCincinnati OHCincinnati OH 21.821.821.8 ‐‐‐17.717.717.7 0.90.90.9 269269269 ‐‐‐3.63.63.6 111 111

173001730017300 Clarksville TNClarksville TNClarksville TNClarksville TN 18.618.618.6 ‐‐‐0.80.80.8 1.61.61.6 235235235 ‐‐‐4.84.84.8 000 000

174601746017460 Cleveland OHCleveland OHCleveland OHCleveland OH 12.512.512.5 ‐‐‐24.124.124.1 0.70.70.7 288288288 ‐‐‐5.25.25.2 111 111

174201742017420 Cleveland TNCleveland TNCleveland TNCleveland TN 80.780.780.7 4.34.34.3 0.90.90.9 231231231 ‐‐‐2.12.12.1 111 111

176601766017660 Coeur d'Alene IDCoeur d'Alene IDCoeur d'Alene IDCoeur d'Alene ID 60.160.160.1 ‐‐‐11.411.411.4 1.21.21.2 206206206 ‐‐‐1.81.81.8 111 111

177801778017780 College Station TXCollege Station TXCollege Station TXCollege Station TX 12.412.412.4 ‐‐‐4.74.74.7 2.72.72.7 229229229 ‐‐‐4.44.44.4 000 111

178201782017820 Colorado Springs COColorado Springs COColorado Springs COColorado Springs CO 25.825.825.8 ‐‐‐18.018.018.0 ‐‐‐0.60.60.6 186186186 ‐‐‐7.17.17.1 111 111

178601786017860 Columbia MOColumbia MOColumbia MOColumbia MO 27.427.427.4 ‐‐‐8.38.38.3 ‐‐‐0.30.30.3 215215215 ‐‐‐3.83.83.8 111 111

179001790017900 Columbia SCColumbia SCColumbia SCColumbia SC 56.656.656.6 ‐‐‐5.05.05.0 ‐‐‐0.10.10.1 200200200 ‐‐‐3.03.03.0 111 111

179801798017980 Columbus GAColumbus GAColumbus GAColumbus GA 46.046.046.0 ‐‐‐14.414.414.4 ‐‐‐0.20.20.2 238238238 ‐‐‐5.55.55.5 111 111

180201802018020 Columbus INColumbus INColumbus INColumbus IN 21.521.521.5 ‐‐‐8.28.28.2 2.32.32.3 262262262 ‐‐‐4.64.64.6 111 111

181401814018140 Columbus OHColumbus OHColumbus OHColumbus OH 12.512.512.5 ‐‐‐15.215.215.2 0.80.80.8 258258258 ‐‐‐6.46.46.4 000 111

185801858018580 Corpus Christi TXCorpus Christi TXCorpus Christi TXCorpus Christi TX 40.340.340.3 ‐‐‐17.417.417.4 2.32.32.3 190190190 ‐‐‐5.15.15.1 111 111

187001870018700 Corvallis ORCorvallis ORCorvallis ORCorvallis OR 40.740.740.7 ‐‐‐13.713.713.7 2.82.82.8 182182182 ‐‐‐8.78.78.7 111 111

188801888018880 Crestview FLCrestview FLCrestview FLCrestview FL 53.453.453.4 ‐‐‐13.613.613.6 0.90.90.9 167167167 ‐‐‐4.34.34.3 000 111

190601906019060 Cumberland MDCumberland MDCumberland MDCumberland MD 7.97.97.9 ‐‐‐13.513.513.5 1.21.21.2 293293293 ‐‐‐5.95.95.9 111 111

191241912419124 Dallas TX [Metropolitan Division]Dallas TX [Metropolitan Division]Dallas TX [Metropolitan Division]Dallas TX [Metropolitan Division] 15.715.715.7 ‐‐‐4.44.44.4 2.82.82.8 196196196 ‐‐‐4.24.24.2 000 111

191401914019140 Dalton GADalton GADalton GADalton GA 81.581.581.5 ‐‐‐0.40.40.4 0.50.50.5 232232232 ‐‐‐7.57.57.5 111 111

191801918019180 Danville ILDanville ILDanville ILDanville IL 45.245.245.2 ‐‐‐3.73.73.7 0.20.20.2 427427427 ‐‐‐9.49.49.4 000 000

192601926019260 Danville VADanville VADanville VADanville VA 57.457.457.4 ‐‐‐0.80.80.8 4.64.64.6 232232232 ‐‐‐5.85.85.8 111 000

193401934019340 Davenport ILDavenport ILDavenport ILDavenport IL 33.133.133.1 ‐‐‐7.87.87.8 1.61.61.6 275275275 ‐‐‐7.37.37.3 111 000

193801938019380 Dayton OHDayton OHDayton OHDayton OH 29.429.429.4 ‐‐‐16.916.916.9 0.20.20.2 319319319 ‐‐‐5.25.25.2 111 111

194601946019460 Decatur ALDecatur ALDecatur ALDecatur AL 42.542.542.5 ‐‐‐3.73.73.7 0.40.40.4 235235235 ‐‐‐6.36.36.3 111 111

195001950019500 Decatur ILDecatur ILDecatur ILDecatur IL 22.922.922.9 ‐‐‐12.812.812.8 ‐‐‐0.40.40.4 346346346 ‐‐‐5.55.55.5 000 111

196601966019660 Deltona FLDeltona FLDeltona FLDeltona FL 55.355.355.3 ‐‐‐30.830.830.8 0.60.60.6 236236236 ‐‐‐4.24.24.2 111 111

197401974019740 Denver CODenver CODenver CODenver CO 35.735.735.7 ‐‐‐11.111.111.1 1.01.01.0 158158158 ‐‐‐8.48.48.4 111 111

197801978019780 Des Moines IADes Moines IADes Moines IADes Moines IA 49.649.649.6 ‐‐‐9.19.19.1 ‐‐‐0.80.80.8 231231231 ‐‐‐3.23.23.2 111 111

198041980419804 Detroit MI [Metropolitan Division]Detroit MI [Metropolitan Division]Detroit MI [Metropolitan Division]Detroit MI [Metropolitan Division] 52.752.752.7 ‐‐‐51.451.451.4 ‐‐‐0.30.30.3 304304304 23.223.223.2 111 111

200202002020020 Dothan ALDothan ALDothan ALDothan AL 36.136.136.1 ‐‐‐8.28.28.2 ‐‐‐2.22.22.2 249249249 ‐‐‐5.25.25.2 111 111

201002010020100 Dover DEDover DEDover DEDover DE 43.443.443.4 ‐‐‐17.217.217.2 ‐‐‐0.10.10.1 179179179 ‐‐‐2.42.42.4 111 111

202202022020220 Dubuque IADubuque IADubuque IADubuque IA 6.06.06.0 ‐‐‐4.84.84.8 2.02.02.0 254254254 ‐‐‐3.23.23.2 111 111

202602026020260 Duluth MNDuluth MNDuluth MNDuluth MN 32.732.732.7 ‐‐‐12.012.012.0 0.90.90.9 276276276 ‐‐‐6.06.06.0 111 111

205002050020500 Durham NCDurham NCDurham NCDurham NC 70.070.070.0 1.41.41.4 0.00.00.0 202202202 ‐‐‐4.04.04.0 111 111

207402074020740 Eau Claire WIEau Claire WIEau Claire WIEau Claire WI 27.027.027.0 ‐‐‐2.42.42.4 1.01.01.0 273273273 ‐‐‐5.05.05.0 111 111

207642076420764 Edison NJ [Metropolitan Division]Edison NJ [Metropolitan Division]Edison NJ [Metropolitan Division]Edison NJ [Metropolitan Division] 48.248.248.2 ‐‐‐11.011.011.0 ‐‐‐0.40.40.4 143143143 ‐‐‐5.25.25.2 000 111

209402094020940 El Centro CAEl Centro CAEl Centro CAEl Centro CA 14.214.214.2 ‐‐‐49.249.249.2 0.20.20.2 291291291 ‐‐‐6.96.96.9 111 111

213402134021340 El Paso TXEl Paso TXEl Paso TXEl Paso TX 31.831.831.8 ‐‐‐3.43.43.4 1.41.41.4 153153153 ‐‐‐4.74.74.7 111 111

210602106021060 Elizabethtown KYElizabethtown KYElizabethtown KYElizabethtown KY 11.711.711.7 ‐‐‐0.70.70.7 6.66.66.6 248248248 ‐‐‐5.15.15.1 111 111

211402114021140 Elkhart INElkhart INElkhart INElkhart IN 29.629.629.6 ‐‐‐13.513.513.5 2.22.22.2 249249249 ‐‐‐0.90.90.9 000 111

213002130021300 Elmira NYElmira NYElmira NYElmira NY 17.417.417.4 2.92.92.9 0.30.30.3 243243243 ‐‐‐7.97.97.9 000 000

215002150021500 Erie PAErie PAErie PAErie PA 20.520.520.5 ‐‐‐8.48.48.4 1.71.71.7 255255255 ‐‐‐6.06.06.0 111 111

216602166021660 Eugene OREugene OREugene OREugene OR 59.159.159.1 ‐‐‐14.714.714.7 ‐‐‐0.10.10.1 142142142 ‐‐‐7.57.57.5 111 111

217802178021780 Evansville INEvansville INEvansville INEvansville IN 16.316.316.3 ‐‐‐11.711.711.7 1.01.01.0 327327327 ‐‐‐5.35.35.3 111 111



218202182021820 Fairbanks AKFairbanks AKFairbanks AKFairbanks AK 3.53.53.5 ‐‐‐16.316.316.3 ‐‐‐0.10.10.1 269269269 ‐‐‐10.210.210.2 000 000

220202202022020 Fargo NDFargo NDFargo NDFargo ND 28.828.828.8 ‐‐‐5.25.25.2 0.90.90.9 245245245 ‐‐‐3.93.93.9 111 000

221402214022140 Farmington NMFarmington NMFarmington NMFarmington NM 45.245.245.2 ‐‐‐9.19.19.1 2.42.42.4 169169169 ‐‐‐7.07.07.0 111 111

222202222022220 Fayetteville ARFayetteville ARFayetteville ARFayetteville AR 91.591.591.5 ‐‐‐4.44.44.4 1.11.11.1 248248248 ‐‐‐5.25.25.2 111 111

221802218022180 Fayetteville NCFayetteville NCFayetteville NCFayetteville NC 8.88.88.8 ‐‐‐5.75.75.7 0.70.70.7 219219219 ‐‐‐4.44.44.4 000 000

223802238022380 Flagstaff AZFlagstaff AZFlagstaff AZFlagstaff AZ 56.756.756.7 ‐‐‐31.331.331.3 3.33.33.3 196196196 ‐‐‐8.28.28.2 111 111

224202242022420 Flint MIFlint MIFlint MIFlint MI 78.578.578.5 ‐‐‐25.625.625.6 ‐‐‐1.41.41.4 376376376 9.49.49.4 111 111

225202252022520 Florence ALFlorence ALFlorence ALFlorence AL 25.925.925.9 ‐‐‐1.91.91.9 3.13.13.1 239239239 ‐‐‐4.34.34.3 000 000

225002250022500 Florence SCFlorence SCFlorence SCFlorence SC 33.933.933.9 ‐‐‐7.67.67.6 ‐‐‐1.01.01.0 218218218 ‐‐‐5.15.15.1 111 111

225402254022540 Fond du Lac WIFond du Lac WIFond du Lac WIFond du Lac WI 26.026.026.0 ‐‐‐8.08.08.0 0.80.80.8 271271271 ‐‐‐6.06.06.0 111 111

226602266022660 Fort Collins COFort Collins COFort Collins COFort Collins CO 10.410.410.4 ‐‐‐13.313.313.3 2.52.52.5 241241241 ‐‐‐8.18.18.1 000 111

227442274422744 Fort Lauderdale FL [Metropolitan Division]Fort Lauderdale FL [Metropolitan Division]Fort Lauderdale FL [Metropolitan Division]Fort Lauderdale FL [Metropolitan Division] 70.370.370.3 ‐‐‐15.715.715.7 0.90.90.9 159159159 ‐‐‐8.88.88.8 000 111

229002290022900 Fort Smith ARFort Smith ARFort Smith ARFort Smith AR 49.949.949.9 ‐‐‐2.02.02.0 0.50.50.5 284284284 ‐‐‐4.74.74.7 111 000

230602306023060 Fort Wayne INFort Wayne INFort Wayne INFort Wayne IN 22.522.522.5 ‐‐‐16.316.316.3 2.52.52.5 317317317 ‐‐‐4.74.74.7 111 111

231042310423104 Fort Worth TX [Metropolitan Division]Fort Worth TX [Metropolitan Division]Fort Worth TX [Metropolitan Division]Fort Worth TX [Metropolitan Division] 39.739.739.7 ‐‐‐8.48.48.4 2.22.22.2 253253253 ‐‐‐5.15.15.1 111 111

234202342023420 Fresno CAFresno CAFresno CAFresno CA 18.418.418.4 ‐‐‐53.553.553.5 0.20.20.2 195195195 ‐‐‐3.73.73.7 111 111

234602346023460 Gadsden ALGadsden ALGadsden ALGadsden AL 46.646.646.6 8.38.38.3 ‐‐‐0.90.90.9 260260260 ‐‐‐3.13.13.1 000 000

235402354023540 Gainesville FLGainesville FLGainesville FLGainesville FL 55.155.155.1 ‐‐‐13.413.413.4 ‐‐‐0.20.20.2 187187187 ‐‐‐4.94.94.9 111 111

235802358023580 Gainesville GAGainesville GAGainesville GAGainesville GA 72.572.572.5 ‐‐‐10.810.810.8 0.40.40.4 258258258 ‐‐‐4.24.24.2 000 111

238442384423844 Gary IN [Metropolitan Division]Gary IN [Metropolitan Division]Gary IN [Metropolitan Division]Gary IN [Metropolitan Division] 47.947.947.9 ‐‐‐15.615.615.6 ‐‐‐2.02.02.0 241241241 ‐‐‐4.04.04.0 111 111

240202402024020 Glens Falls NYGlens Falls NYGlens Falls NYGlens Falls NY 2.02.02.0 ‐‐‐38.938.938.9 ‐‐‐2.22.22.2 198198198 ‐‐‐2.42.42.4 111 111

241402414024140 Goldsboro NCGoldsboro NCGoldsboro NCGoldsboro NC 67.867.867.8 ‐‐‐6.26.26.2 ‐‐‐2.02.02.0 251251251 ‐‐‐6.76.76.7 111 111

242202422024220 Grand Forks NDGrand Forks NDGrand Forks NDGrand Forks ND 26.926.926.9 ‐‐‐10.210.210.2 2.32.32.3 284284284 ‐‐‐5.55.55.5 000 000

243002430024300 Grand Junction COGrand Junction COGrand Junction COGrand Junction CO 68.568.568.5 ‐‐‐5.75.75.7 ‐‐‐3.03.03.0 256256256 ‐‐‐3.43.43.4 111 111

243402434024340 Grand Rapids MIGrand Rapids MIGrand Rapids MIGrand Rapids MI 66.666.666.6 ‐‐‐18.018.018.0 1.91.91.9 280280280 ‐‐‐2.92.92.9 000 111

245002450024500 Great Falls MTGreat Falls MTGreat Falls MTGreat Falls MT 24.624.624.6 ‐‐‐8.58.58.5 0.40.40.4 287287287 ‐‐‐4.44.44.4 111 111

245402454024540 Greeley COGreeley COGreeley COGreeley CO 45.945.945.9 ‐‐‐12.612.612.6 1.71.71.7 302302302 ‐‐‐4.74.74.7 000 111

245802458024580 Green Bay WIGreen Bay WIGreen Bay WIGreen Bay WI 23.123.123.1 ‐‐‐19.519.519.5 ‐‐‐0.20.20.2 235235235 ‐‐‐4.24.24.2 111 111

246602466024660 Greensboro NCGreensboro NCGreensboro NCGreensboro NC 56.756.756.7 ‐‐‐2.72.72.7 0.20.20.2 218218218 ‐‐‐5.05.05.0 111 111

247802478024780 Greenville NCGreenville NCGreenville NCGreenville NC 26.826.826.8 ‐‐‐5.05.05.0 ‐‐‐1.31.31.3 241241241 ‐‐‐4.94.94.9 000 111

248602486024860 Greenville SCGreenville SCGreenville SCGreenville SC 65.765.765.7 2.52.52.5 0.40.40.4 188188188 ‐‐‐2.22.22.2 111 111

250602506025060 Gulfport MSGulfport MSGulfport MSGulfport MS 63.863.863.8 ‐‐‐13.913.913.9 0.40.40.4 219219219 1.91.91.9 000 111

251802518025180 Hagerstown MDHagerstown MDHagerstown MDHagerstown MD 38.038.038.0 ‐‐‐22.822.822.8 ‐‐‐1.21.21.2 215215215 ‐‐‐0.30.30.3 111 111

252602526025260 Hanford CAHanford CAHanford CAHanford CA 90.890.890.8 ‐‐‐12.212.212.2 ‐‐‐0.10.10.1 176176176 ‐‐‐3.43.43.4 111 111

254202542025420 Harrisburg PAHarrisburg PAHarrisburg PAHarrisburg PA 50.150.150.1 0.30.30.3 ‐‐‐0.30.30.3 244244244 ‐‐‐3.83.83.8 111 000

255002550025500 Harrisonburg VAHarrisonburg VAHarrisonburg VAHarrisonburg VA 72.272.272.2 15.015.015.0 1.41.41.4 176176176 ‐‐‐1.21.21.2 000 111

255402554025540 Hartford CTHartford CTHartford CTHartford CT 26.126.126.1 ‐‐‐26.526.526.5 1.21.21.2 186186186 ‐‐‐5.45.45.4 000 111

256202562025620 Hattiesburg MSHattiesburg MSHattiesburg MSHattiesburg MS 35.635.635.6 ‐‐‐6.16.16.1 0.30.30.3 272272272 ‐‐‐8.68.68.6 000 111

258602586025860 Hickory NCHickory NCHickory NCHickory NC 69.769.769.7 3.63.63.6 ‐‐‐1.51.51.5 235235235 ‐‐‐5.05.05.0 111 111

259802598025980 Hinesville GAHinesville GAHinesville GAHinesville GA 75.875.875.8 9.69.69.6 ‐‐‐0.90.90.9 220220220 ‐‐‐5.05.05.0 111 111

261002610026100 Holland MIHolland MIHolland MIHolland MI 56.156.156.1 ‐‐‐13.213.213.2 1.11.11.1 251251251 ‐‐‐4.54.54.5 111 111

261802618026180 Honolulu HIHonolulu HIHonolulu HIHonolulu HI 54.454.454.4 ‐‐‐1.81.81.8 1.51.51.5 656565 ‐‐‐6.36.36.3 000 000

263002630026300 Hot Springs ARHot Springs ARHot Springs ARHot Springs AR 77.377.377.3 0.20.20.2 4.04.04.0 191191191 ‐‐‐7.47.47.4 000 000

263802638026380 Houma LAHouma LAHouma LAHouma LA 7.57.57.5 ‐‐‐3.43.43.4 1.51.51.5 246246246 ‐‐‐0.70.70.7 111 111

264202642026420 Houston TXHouston TXHouston TXHouston TX 19.219.219.2 ‐‐‐7.57.57.5 2.42.42.4 205205205 ‐‐‐3.43.43.4 000 111

265802658026580 Huntington WVHuntington WVHuntington WVHuntington WV 9.09.09.0 0.50.50.5 ‐‐‐0.50.50.5 264264264 ‐‐‐8.28.28.2 111 111

266202662026620 Huntsville ALHuntsville ALHuntsville ALHuntsville AL 64.064.064.0 ‐‐‐3.33.33.3 0.60.60.6 259259259 ‐‐‐1.71.71.7 111 111

268202682026820 Idaho Falls IDIdaho Falls IDIdaho Falls IDIdaho Falls ID 18.118.118.1 ‐‐‐22.322.322.3 1.11.11.1 304304304 ‐‐‐4.54.54.5 111 111

269002690026900 Indianapolis INIndianapolis INIndianapolis INIndianapolis IN 41.141.141.1 ‐‐‐11.911.911.9 ‐‐‐0.30.30.3 261261261 ‐‐‐4.74.74.7 111 111

269802698026980 Iowa City IAIowa City IAIowa City IAIowa City IA 40.940.940.9 ‐‐‐4.04.04.0 0.20.20.2 243243243 ‐‐‐1.91.91.9 000 111

270602706027060 Ithaca NYIthaca NYIthaca NYIthaca NY 30.730.730.7 21.921.921.9 2.12.12.1 221221221 ‐‐‐5.25.25.2 000 111

271002710027100 Jackson MIJackson MIJackson MIJackson MI 26.326.326.3 ‐‐‐20.420.420.4 1.51.51.5 343343343 ‐‐‐7.37.37.3 000 111

271402714027140 Jackson MSJackson MSJackson MSJackson MS 54.854.854.8 ‐‐‐5.55.55.5 0.50.50.5 193193193 ‐‐‐2.42.42.4 000 111

271802718027180 Jackson TNJackson TNJackson TNJackson TN 54.254.254.2 ‐‐‐14.014.014.0 0.80.80.8 272272272 ‐‐‐3.63.63.6 111 111

272602726027260 Jacksonville FLJacksonville FLJacksonville FLJacksonville FL 57.757.757.7 ‐‐‐20.720.720.7 1.01.01.0 231231231 ‐‐‐3.63.63.6 000 111

273402734027340 Jacksonville NCJacksonville NCJacksonville NCJacksonville NC 32.632.632.6 ‐‐‐13.413.413.4 ‐‐‐2.92.92.9 170170170 ‐‐‐1.91.91.9 111 111

275002750027500 Janesville WIJanesville WIJanesville WIJanesville WI 46.746.746.7 ‐‐‐3.53.53.5 0.90.90.9 281281281 ‐‐‐0.70.70.7 111 111

276202762027620 Jefferson City MOJefferson City MOJefferson City MOJefferson City MO 4.44.44.4 ‐‐‐10.810.810.8 0.40.40.4 301301301 ‐‐‐7.37.37.3 111 111

277402774027740 Johnson City TNJohnson City TNJohnson City TNJohnson City TN 45.545.545.5 0.70.70.7 0.80.80.8 201201201 ‐‐‐3.83.83.8 111 111

277802778027780 Johnstown PAJohnstown PAJohnstown PAJohnstown PA 15.015.015.0 ‐‐‐9.89.89.8 1.81.81.8 326326326 ‐‐‐4.64.64.6 111 000

278602786027860 Jonesboro ARJonesboro ARJonesboro ARJonesboro AR 4.74.74.7 ‐‐‐13.313.313.3 0.20.20.2 300300300 ‐‐‐1.31.31.3 111 111



279002790027900 Joplin MOJoplin MOJoplin MOJoplin MO 32.532.532.5 ‐‐‐8.78.78.7 2.12.12.1 271271271 ‐‐‐7.67.67.6 111 111

280202802028020 Kalamazoo MIKalamazoo MIKalamazoo MIKalamazoo MI 72.672.672.6 ‐‐‐15.615.615.6 1.61.61.6 268268268 ‐‐‐6.06.06.0 000 111

281002810028100 Kankakee ILKankakee ILKankakee ILKankakee IL 68.268.268.2 ‐‐‐0.40.40.4 4.24.24.2 265265265 ‐‐‐3.53.53.5 111 111

281402814028140 Kansas City MOKansas City MOKansas City MOKansas City MO 65.765.765.7 ‐‐‐11.711.711.7 ‐‐‐0.50.50.5 261261261 ‐‐‐7.37.37.3 111 111

284202842028420 Kennewick WAKennewick WAKennewick WAKennewick WA 2.42.42.4 ‐‐‐21.921.921.9 1.21.21.2 183183183 ‐‐‐4.34.34.3 000 000

286602866028660 Killeen TXKilleen TXKilleen TXKilleen TX 26.426.426.4 ‐‐‐18.518.518.5 1.21.21.2 286286286 ‐‐‐3.63.63.6 000 111

287002870028700 Kingsport TNKingsport TNKingsport TNKingsport TN 51.451.451.4 9.69.69.6 1.71.71.7 199199199 ‐‐‐4.84.84.8 000 111

287402874028740 Kingston NYKingston NYKingston NYKingston NY 18.918.918.9 ‐‐‐10.510.510.5 ‐‐‐1.91.91.9 180180180 ‐‐‐0.30.30.3 111 111

289402894028940 Knoxville TNKnoxville TNKnoxville TNKnoxville TN 76.576.576.5 9.39.39.3 1.21.21.2 206206206 ‐‐‐2.62.62.6 000 111

290202902029020 Kokomo INKokomo INKokomo INKokomo IN 22.822.822.8 ‐‐‐18.118.118.1 3.43.43.4 356356356 ‐‐‐6.76.76.7 111 111

291002910029100 La Crosse WILa Crosse WILa Crosse WILa Crosse WI 26.426.426.4 0.40.40.4 ‐‐‐1.11.11.1 284284284 ‐‐‐4.34.34.3 111 111

291402914029140 Lafayette INLafayette INLafayette INLafayette IN 31.031.031.0 ‐‐‐15.315.315.3 1.51.51.5 276276276 ‐‐‐4.74.74.7 111 111

291802918029180 Lafayette LALafayette LALafayette LALafayette LA 35.235.235.2 ‐‐‐7.17.17.1 0.40.40.4 222222222 ‐‐‐3.93.93.9 111 111

293402934029340 Lake Charles LALake Charles LALake Charles LALake Charles LA 22.422.422.4 ‐‐‐9.29.29.2 2.12.12.1 272272272 ‐‐‐0.40.40.4 111 111

294042940429404 Lake County IL [Metropolitan Division]Lake County IL [Metropolitan Division]Lake County IL [Metropolitan Division]Lake County IL [Metropolitan Division] 81.681.681.6 ‐‐‐4.84.84.8 0.60.60.6 211211211 ‐‐‐7.27.27.2 111 111

294202942029420 Lake Havasu AZLake Havasu AZLake Havasu AZLake Havasu AZ 91.891.891.8 ‐‐‐18.218.218.2 1.21.21.2 274274274 ‐‐‐7.07.07.0 111 111

294602946029460 Lakeland FLLakeland FLLakeland FLLakeland FL 30.430.430.4 ‐‐‐45.845.845.8 ‐‐‐1.21.21.2 275275275 0.10.10.1 111 111

295402954029540 Lancaster PALancaster PALancaster PALancaster PA 55.355.355.3 3.43.43.4 ‐‐‐0.30.30.3 209209209 ‐‐‐4.74.74.7 111 111

296202962029620 Lansing MILansing MILansing MILansing MI 18.118.118.1 ‐‐‐30.730.730.7 1.11.11.1 384384384 ‐‐‐7.17.17.1 111 111

297002970029700 Laredo TXLaredo TXLaredo TXLaredo TX 44.444.444.4 ‐‐‐13.213.213.2 1.11.11.1 214214214 ‐‐‐5.25.25.2 000 000

297402974029740 Las Cruces NMLas Cruces NMLas Cruces NMLas Cruces NM 30.130.130.1 ‐‐‐19.519.519.5 ‐‐‐1.21.21.2 219219219 ‐‐‐4.24.24.2 111 111

298202982029820 Las Vegas NVLas Vegas NVLas Vegas NVLas Vegas NV 91.391.391.3 ‐‐‐38.138.138.1 1.11.11.1 234234234 ‐‐‐0.80.80.8 111 111

299402994029940 Lawrence KSLawrence KSLawrence KSLawrence KS 40.040.040.0 4.04.04.0 0.10.10.1 233233233 ‐‐‐5.15.15.1 111 111

300203002030020 Lawton OKLawton OKLawton OKLawton OK 5.85.85.8 ‐‐‐20.020.020.0 ‐‐‐0.60.60.6 265265265 ‐‐‐8.28.28.2 111 111

301403014030140 Lebanon PALebanon PALebanon PALebanon PA 27.327.327.3 2.42.42.4 2.42.42.4 238238238 ‐‐‐3.03.03.0 111 111

303003030030300 Lewiston IDLewiston IDLewiston IDLewiston ID 36.136.136.1 ‐‐‐3.13.13.1 ‐‐‐2.72.72.7 225225225 ‐‐‐7.27.27.2 111 111

303403034030340 Lewiston MELewiston MELewiston MELewiston ME 18.918.918.9 ‐‐‐18.318.318.3 ‐‐‐0.70.70.7 223223223 6.06.06.0 111 111

304603046030460 Lexington KYLexington KYLexington KYLexington KY 51.651.651.6 5.15.15.1 1.01.01.0 239239239 ‐‐‐2.52.52.5 111 111

306203062030620 Lima OHLima OHLima OHLima OH 46.846.846.8 ‐‐‐7.77.77.7 1.51.51.5 287287287 ‐‐‐4.24.24.2 111 111

307003070030700 Lincoln NELincoln NELincoln NELincoln NE 25.425.425.4 ‐‐‐5.55.55.5 1.71.71.7 233233233 ‐‐‐4.84.84.8 000 000

307803078030780 Little Rock ARLittle Rock ARLittle Rock ARLittle Rock AR 16.916.916.9 ‐‐‐2.92.92.9 0.10.10.1 215215215 ‐‐‐4.24.24.2 111 111

308603086030860 Logan UTLogan UTLogan UTLogan UT 46.546.546.5 ‐‐‐3.33.33.3 5.15.15.1 212212212 ‐‐‐4.24.24.2 111 111

309803098030980 Longview TXLongview TXLongview TXLongview TX 37.337.337.3 ‐‐‐3.53.53.5 1.31.31.3 291291291 ‐‐‐8.18.18.1 111 111

310203102031020 Longview WALongview WALongview WALongview WA 44.244.244.2 ‐‐‐20.120.120.1 ‐‐‐2.32.32.3 236236236 ‐‐‐4.04.04.0 111 111

310843108431084 Los Angeles CA [Metropolitan Division]Los Angeles CA [Metropolitan Division]Los Angeles CA [Metropolitan Division]Los Angeles CA [Metropolitan Division] 31.031.031.0 ‐‐‐10.710.710.7 0.20.20.2 102102102 ‐‐‐9.79.79.7 111 111

311403114031140 Louisville KYLouisville KYLouisville KYLouisville KY 62.862.862.8 3.73.73.7 1.11.11.1 236236236 ‐‐‐5.15.15.1 111 111

311803118031180 Lubbock TXLubbock TXLubbock TXLubbock TX 23.823.823.8 ‐‐‐7.77.77.7 0.70.70.7 294294294 ‐‐‐6.06.06.0 000 000

313403134031340 Lynchburg VALynchburg VALynchburg VALynchburg VA 62.862.862.8 11.311.311.3 3.03.03.0 190190190 ‐‐‐3.03.03.0 111 111

314203142031420 Macon GAMacon GAMacon GAMacon GA 73.373.373.3 ‐‐‐11.811.811.8 0.70.70.7 295295295 ‐‐‐2.82.82.8 111 111

314603146031460 Madera CAMadera CAMadera CAMadera CA 95.595.595.5 ‐‐‐15.515.515.5 ‐‐‐1.21.21.2 211211211 ‐‐‐6.66.66.6 111 111

315403154031540 Madison WIMadison WIMadison WIMadison WI 56.556.556.5 3.93.93.9 0.80.80.8 180180180 ‐‐‐6.36.36.3 000 111

317003170031700 Manchester NHManchester NHManchester NHManchester NH 59.659.659.6 ‐‐‐18.818.818.8 1.11.11.1 183183183 ‐‐‐5.75.75.7 111 111

317403174031740 Manhattan KSManhattan KSManhattan KSManhattan KS 22.722.722.7 ‐‐‐13.013.013.0 4.34.34.3 238238238 ‐‐‐3.93.93.9 111 111

318603186031860 Mankato MNMankato MNMankato MNMankato MN 26.426.426.4 ‐‐‐7.67.67.6 0.10.10.1 275275275 ‐‐‐5.55.55.5 111 111

319003190031900 Mansfield OHMansfield OHMansfield OHMansfield OH 75.575.575.5 ‐‐‐16.516.516.5 ‐‐‐0.70.70.7 309309309 0.80.80.8 111 111

325803258032580 McAllen TXMcAllen TXMcAllen TXMcAllen TX 3.63.63.6 ‐‐‐21.821.821.8 1.21.21.2 257257257 ‐‐‐4.04.04.0 111 111

327803278032780 Medford ORMedford ORMedford ORMedford OR 74.974.974.9 ‐‐‐21.821.821.8 1.31.31.3 222222222 ‐‐‐7.17.17.1 111 111

328203282032820 Memphis TNMemphis TNMemphis TNMemphis TN 9.59.59.5 ‐‐‐32.832.832.8 ‐‐‐1.11.11.1 243243243 ‐‐‐5.45.45.4 111 111

329003290032900 Merced CAMerced CAMerced CAMerced CA 37.537.537.5 ‐‐‐60.360.360.3 1.01.01.0 201201201 ‐‐‐7.97.97.9 111 111

331243312433124 Miami FL [Metropolitan Division]Miami FL [Metropolitan Division]Miami FL [Metropolitan Division]Miami FL [Metropolitan Division] 77.677.677.6 ‐‐‐12.812.812.8 1.41.41.4 136136136 ‐‐‐10.010.010.0 000 111

331403314033140 Michigan City INMichigan City INMichigan City INMichigan City IN 47.347.347.3 ‐‐‐8.58.58.5 ‐‐‐0.70.70.7 266266266 ‐‐‐4.84.84.8 111 111

332603326033260 Midland TXMidland TXMidland TXMidland TX 11.111.111.1 2.42.42.4 2.92.92.9 249249249 ‐‐‐4.94.94.9 111 111

333403334033340 Milwaukee WIMilwaukee WIMilwaukee WIMilwaukee WI 42.142.142.1 ‐‐‐4.04.04.0 3.13.13.1 180180180 ‐‐‐7.57.57.5 111 111

334603346033460 Minneapolis MNMinneapolis MNMinneapolis MNMinneapolis MN 41.841.841.8 ‐‐‐17.817.817.8 0.70.70.7 279279279 ‐‐‐8.28.28.2 111 111

335403354033540 Missoula MTMissoula MTMissoula MTMissoula MT 60.560.560.5 7.37.37.3 ‐‐‐3.63.63.6 174174174 ‐‐‐5.75.75.7 111 111

336603366033660 Mobile ALMobile ALMobile ALMobile AL 77.277.277.2 ‐‐‐23.523.523.5 0.80.80.8 211211211 0.70.70.7 111 111

337003370033700 Modesto CAModesto CAModesto CAModesto CA 60.860.860.8 ‐‐‐31.731.731.7 0.10.10.1 169169169 ‐‐‐8.08.08.0 111 111

337403374033740 Monroe LAMonroe LAMonroe LAMonroe LA 24.524.524.5 ‐‐‐5.35.35.3 ‐‐‐0.40.40.4 248248248 ‐‐‐5.55.55.5 111 111

337803378033780 Monroe MIMonroe MIMonroe MIMonroe MI 71.171.171.1 ‐‐‐17.517.517.5 ‐‐‐0.50.50.5 280280280 ‐‐‐5.05.05.0 111 111

338603386033860 Montgomery ALMontgomery ALMontgomery ALMontgomery AL 49.449.449.4 ‐‐‐10.210.210.2 ‐‐‐0.90.90.9 205205205 ‐‐‐5.65.65.6 111 111

340603406034060 Morgantown WVMorgantown WVMorgantown WVMorgantown WV 18.818.818.8 ‐‐‐5.05.05.0 ‐‐‐0.30.30.3 209209209 ‐‐‐10.510.510.5 111 111



341003410034100 Morristown TNMorristown TNMorristown TNMorristown TN 71.371.371.3 ‐‐‐1.71.71.7 ‐‐‐1.21.21.2 230230230 ‐‐‐3.53.53.5 111 111

345803458034580 Mount Vernon WAMount Vernon WAMount Vernon WAMount Vernon WA 59.959.959.9 ‐‐‐18.018.018.0 ‐‐‐1.31.31.3 197197197 ‐‐‐4.04.04.0 111 111

346203462034620 Muncie INMuncie INMuncie INMuncie IN 15.015.015.0 ‐‐‐14.114.114.1 ‐‐‐1.91.91.9 346346346 ‐‐‐9.39.39.3 111 111

347403474034740 Muskegon MIMuskegon MIMuskegon MIMuskegon MI 91.791.791.7 ‐‐‐23.223.223.2 0.00.00.0 316316316 3.43.43.4 111 111

348203482034820 Myrtle Beach SCMyrtle Beach SCMyrtle Beach SCMyrtle Beach SC 52.252.252.2 ‐‐‐15.515.515.5 5.95.95.9 174174174 ‐‐‐1.21.21.2 000 111

349003490034900 Napa CANapa CANapa CANapa CA 20.420.420.4 ‐‐‐30.530.530.5 ‐‐‐0.50.50.5 125125125 ‐‐‐7.77.77.7 111 111

349403494034940 Naples FLNaples FLNaples FLNaples FL 54.854.854.8 ‐‐‐7.27.27.2 ‐‐‐1.11.11.1 999999 ‐‐‐4.54.54.5 111 111

349803498034980 Nashville TNNashville TNNashville TNNashville TN 62.562.562.5 2.52.52.5 1.01.01.0 186186186 ‐‐‐3.53.53.5 111 111

350043500435004 Nassau NY [Metropolitan Division]Nassau NY [Metropolitan Division]Nassau NY [Metropolitan Division]Nassau NY [Metropolitan Division] 37.537.537.5 ‐‐‐3.13.13.1 ‐‐‐0.10.10.1 140140140 ‐‐‐7.77.77.7 111 111

353003530035300 New Haven CTNew Haven CTNew Haven CTNew Haven CT 41.141.141.1 ‐‐‐23.023.023.0 1.11.11.1 184184184 ‐‐‐7.17.17.1 111 111

353803538035380 New Orleans LANew Orleans LANew Orleans LANew Orleans LA 61.261.261.2 ‐‐‐26.526.526.5 1.41.41.4 180180180 ‐‐‐6.26.26.2 111 111

356443564435644 New York NY [Metropolitan Division]New York NY [Metropolitan Division]New York NY [Metropolitan Division]New York NY [Metropolitan Division] 12.612.612.6 ‐‐‐8.38.38.3 0.30.30.3 797979 ‐‐‐7.97.97.9 000 111

350843508435084 Newark NJ [Metropolitan Division]Newark NJ [Metropolitan Division]Newark NJ [Metropolitan Division]Newark NJ [Metropolitan Division] 19.119.119.1 ‐‐‐10.810.810.8 ‐‐‐0.90.90.9 121121121 ‐‐‐6.46.46.4 111 111

356603566035660 Niles MINiles MINiles MINiles MI 69.569.569.5 ‐‐‐21.121.121.1 1.31.31.3 252252252 ‐‐‐2.52.52.5 111 111

358403584035840 North Port FLNorth Port FLNorth Port FLNorth Port FL 59.159.159.1 ‐‐‐29.529.529.5 ‐‐‐0.60.60.6 190190190 ‐‐‐4.54.54.5 000 111

359803598035980 Norwich CTNorwich CTNorwich CTNorwich CT 14.014.014.0 ‐‐‐23.623.623.6 0.40.40.4 224224224 ‐‐‐5.15.15.1 111 111

360843608436084 Oakland CA [Metropolitan Division]Oakland CA [Metropolitan Division]Oakland CA [Metropolitan Division]Oakland CA [Metropolitan Division] 25.425.425.4 ‐‐‐29.329.329.3 ‐‐‐0.30.30.3 878787 ‐‐‐9.09.09.0 111 111

361003610036100 Ocala FLOcala FLOcala FLOcala FL 51.551.551.5 ‐‐‐35.635.635.6 ‐‐‐1.01.01.0 290290290 ‐‐‐1.81.81.8 111 111

361403614036140 Ocean City NJOcean City NJOcean City NJOcean City NJ 24.524.524.5 ‐‐‐15.915.915.9 ‐‐‐0.30.30.3 128128128 ‐‐‐3.73.73.7 000 111

362203622036220 Odessa TXOdessa TXOdessa TXOdessa TX 47.947.947.9 3.73.73.7 4.04.04.0 328328328 ‐‐‐6.06.06.0 000 000

362603626036260 Ogden UTOgden UTOgden UTOgden UT 58.158.158.1 ‐‐‐10.710.710.7 2.72.72.7 265265265 ‐‐‐5.25.25.2 111 111

364203642036420 Oklahoma City OKOklahoma City OKOklahoma City OKOklahoma City OK 45.045.045.0 ‐‐‐4.64.64.6 1.61.61.6 206206206 ‐‐‐5.65.65.6 000 111

365003650036500 Olympia WAOlympia WAOlympia WAOlympia WA 44.544.544.5 ‐‐‐23.223.223.2 ‐‐‐0.90.90.9 228228228 ‐‐‐2.82.82.8 111 111

365403654036540 Omaha NEOmaha NEOmaha NEOmaha NE 21.421.421.4 ‐‐‐13.013.013.0 1.31.31.3 234234234 ‐‐‐3.53.53.5 111 111

367403674036740 Orlando FLOrlando FLOrlando FLOrlando FL 51.551.551.5 ‐‐‐30.230.230.2 1.51.51.5 220220220 ‐‐‐5.15.15.1 000 111

367803678036780 Oshkosh WIOshkosh WIOshkosh WIOshkosh WI 22.522.522.5 ‐‐‐14.214.214.2 ‐‐‐0.20.20.2 270270270 ‐‐‐4.94.94.9 111 111

369803698036980 Owensboro KYOwensboro KYOwensboro KYOwensboro KY 13.713.713.7 ‐‐‐5.95.95.9 0.80.80.8 318318318 ‐‐‐2.52.52.5 111 000

371003710037100 Oxnard CAOxnard CAOxnard CAOxnard CA 38.938.938.9 ‐‐‐11.011.011.0 0.20.20.2 969696 ‐‐‐10.510.510.5 111 111

373403734037340 Palm Bay FLPalm Bay FLPalm Bay FLPalm Bay FL 39.039.039.0 ‐‐‐29.529.529.5 ‐‐‐2.52.52.5 264264264 ‐‐‐3.93.93.9 000 111

373803738037380 Palm Coast FLPalm Coast FLPalm Coast FLPalm Coast FL 38.838.838.8 ‐‐‐12.512.512.5 ‐‐‐2.12.12.1 209209209 ‐‐‐5.85.85.8 000 111

374603746037460 Panama City FLPanama City FLPanama City FLPanama City FL 12.712.712.7 ‐‐‐31.831.831.8 2.02.02.0 199199199 ‐‐‐8.08.08.0 111 111

376203762037620 Parkersburg WVParkersburg WVParkersburg WVParkersburg WV 38.038.038.0 ‐‐‐6.06.06.0 1.51.51.5 279279279 ‐‐‐7.67.67.6 111 111

377003770037700 Pascagoula MSPascagoula MSPascagoula MSPascagoula MS 35.235.235.2 ‐‐‐15.115.115.1 ‐‐‐2.42.42.4 273273273 ‐‐‐2.02.02.0 111 111

377643776437764 Peabody MAPeabody MAPeabody MAPeabody MA 14.114.114.1 ‐‐‐20.320.320.3 0.30.30.3 142142142 ‐‐‐9.19.19.1 111 111

378603786037860 Pensacola FLPensacola FLPensacola FLPensacola FL 40.240.240.2 ‐‐‐17.617.617.6 0.60.60.6 208208208 ‐‐‐5.15.15.1 111 111

379003790037900 Peoria ILPeoria ILPeoria ILPeoria IL 8.88.88.8 ‐‐‐5.95.95.9 2.92.92.9 300300300 ‐‐‐5.05.05.0 111 111

379643796437964 Philadelphia PA [Metropolitan Division]Philadelphia PA [Metropolitan Division]Philadelphia PA [Metropolitan Division]Philadelphia PA [Metropolitan Division] 50.550.550.5 ‐‐‐8.78.78.7 0.70.70.7 171171171 ‐‐‐7.37.37.3 111 111

380603806038060 Phoenix AZPhoenix AZPhoenix AZPhoenix AZ 52.052.052.0 ‐‐‐34.834.834.8 0.80.80.8 238238238 ‐‐‐5.85.85.8 111 111

382203822038220 Pine Bluff ARPine Bluff ARPine Bluff ARPine Bluff AR 34.734.734.7 ‐‐‐6.56.56.5 ‐‐‐3.63.63.6 303303303 0.40.40.4 000 111

383003830038300 Pittsburgh PAPittsburgh PAPittsburgh PAPittsburgh PA 14.214.214.2 ‐‐‐7.07.07.0 1.11.11.1 261261261 ‐‐‐5.65.65.6 000 000

383403834038340 Pittsfield MAPittsfield MAPittsfield MAPittsfield MA 11.611.611.6 ‐‐‐20.420.420.4 0.30.30.3 177177177 ‐‐‐6.26.26.2 000 111

385403854038540 Pocatello IDPocatello IDPocatello IDPocatello ID 50.450.450.4 ‐‐‐7.77.77.7 ‐‐‐0.80.80.8 303303303 ‐‐‐6.26.26.2 111 111

389403894038940 Port St. Lucie FLPort St. Lucie FLPort St. Lucie FLPort St. Lucie FL 30.930.930.9 ‐‐‐35.935.935.9 ‐‐‐0.70.70.7 253253253 ‐‐‐6.06.06.0 111 111

388603886038860 Portland MEPortland MEPortland MEPortland ME 41.841.841.8 ‐‐‐12.512.512.5 0.20.20.2 156156156 ‐‐‐0.60.60.6 111 111

389003890038900 Portland ORPortland ORPortland ORPortland OR 21.121.121.1 ‐‐‐14.614.614.6 0.90.90.9 153153153 ‐‐‐7.27.27.2 111 111

391003910039100 Poughkeepsie NYPoughkeepsie NYPoughkeepsie NYPoughkeepsie NY 21.821.821.8 ‐‐‐13.113.113.1 ‐‐‐0.30.30.3 213213213 ‐‐‐3.13.13.1 000 111

391403914039140 Prescott AZPrescott AZPrescott AZPrescott AZ 88.588.588.5 ‐‐‐25.425.425.4 0.40.40.4 209209209 ‐‐‐6.36.36.3 111 111

393003930039300 Providence RIProvidence RIProvidence RIProvidence RI 41.441.441.4 ‐‐‐20.320.320.3 1.41.41.4 156156156 ‐‐‐6.36.36.3 111 111

393403934039340 Provo UTProvo UTProvo UTProvo UT 80.280.280.2 ‐‐‐7.67.67.6 2.82.82.8 245245245 ‐‐‐3.93.93.9 111 111

393803938039380 Pueblo COPueblo COPueblo COPueblo CO 48.448.448.4 ‐‐‐22.922.922.9 2.62.62.6 316316316 ‐‐‐7.17.17.1 111 111

394603946039460 Punta Gorda FLPunta Gorda FLPunta Gorda FLPunta Gorda FL 24.124.124.1 ‐‐‐35.035.035.0 ‐‐‐0.60.60.6 242242242 ‐‐‐6.36.36.3 111 111

395403954039540 Racine WIRacine WIRacine WIRacine WI 63.963.963.9 ‐‐‐10.910.910.9 0.50.50.5 256256256 ‐‐‐3.13.13.1 111 111

395803958039580 Raleigh NCRaleigh NCRaleigh NCRaleigh NC 71.471.471.4 6.16.16.1 1.71.71.7 172172172 ‐‐‐2.72.72.7 111 111

396603966039660 Rapid City SDRapid City SDRapid City SDRapid City SD 30.030.030.0 ‐‐‐4.54.54.5 ‐‐‐0.30.30.3 226226226 ‐‐‐5.25.25.2 111 111

397403974039740 Reading PAReading PAReading PAReading PA 36.236.236.2 2.92.92.9 1.41.41.4 230230230 ‐‐‐4.94.94.9 111 111

398203982039820 Redding CARedding CARedding CARedding CA 28.728.728.7 ‐‐‐61.361.361.3 ‐‐‐1.11.11.1 181181181 ‐‐‐4.84.84.8 111 111

399003990039900 Reno NVReno NVReno NVReno NV 81.581.581.5 ‐‐‐23.323.323.3 ‐‐‐1.31.31.3 195195195 ‐‐‐4.74.74.7 111 111

400604006040060 Richmond VARichmond VARichmond VARichmond VA 76.176.176.1 8.48.48.4 ‐‐‐1.11.11.1 162162162 ‐‐‐4.54.54.5 111 111

401404014040140 Riverside CARiverside CARiverside CARiverside CA 45.245.245.2 ‐‐‐26.926.926.9 ‐‐‐0.60.60.6 181181181 ‐‐‐6.26.26.2 111 111

402204022040220 Roanoke VARoanoke VARoanoke VARoanoke VA 62.862.862.8 6.56.56.5 ‐‐‐0.10.10.1 208208208 ‐‐‐5.45.45.4 111 111

403404034040340 Rochester MNRochester MNRochester MNRochester MN 28.228.228.2 ‐‐‐11.611.611.6 1.51.51.5 309309309 ‐‐‐6.06.06.0 111 111



403804038040380 Rochester NYRochester NYRochester NYRochester NY 3.83.83.8 ‐‐‐14.214.214.2 2.22.22.2 295295295 ‐‐‐5.55.55.5 111 000

404204042040420 Rockford ILRockford ILRockford ILRockford IL 68.168.168.1 ‐‐‐13.713.713.7 0.50.50.5 323323323 ‐‐‐1.31.31.3 111 111

404844048440484 Rockingham County NH [Metropolitan Division]Rockingham County NH [Metropolitan Division]Rockingham County NH [Metropolitan Division]Rockingham County NH [Metropolitan Division] 47.047.047.0 ‐‐‐19.319.319.3 1.11.11.1 208208208 ‐‐‐3.73.73.7 000 111

405804058040580 Rocky Mount NCRocky Mount NCRocky Mount NCRocky Mount NC 38.538.538.5 ‐‐‐15.715.715.7 1.71.71.7 252252252 ‐‐‐5.65.65.6 111 111

406604066040660 Rome GARome GARome GARome GA 66.066.066.0 ‐‐‐3.43.43.4 ‐‐‐0.20.20.2 276276276 ‐‐‐6.16.16.1 111 111

409004090040900 Sacramento CASacramento CASacramento CASacramento CA 22.322.322.3 ‐‐‐48.948.948.9 ‐‐‐1.11.11.1 217217217 ‐‐‐6.86.86.8 111 111

409804098040980 Saginaw MISaginaw MISaginaw MISaginaw MI 37.937.937.9 ‐‐‐22.522.522.5 1.81.81.8 449449449 ‐‐‐0.80.80.8 111 111

414204142041420 Salem ORSalem ORSalem ORSalem OR 62.362.362.3 ‐‐‐18.818.818.8 ‐‐‐1.41.41.4 203203203 ‐‐‐7.17.17.1 111 111

415004150041500 Salinas CASalinas CASalinas CASalinas CA 6.06.06.0 ‐‐‐51.951.951.9 ‐‐‐1.61.61.6 121121121 ‐‐‐9.79.79.7 111 111

415404154041540 Salisbury MDSalisbury MDSalisbury MDSalisbury MD 28.828.828.8 ‐‐‐28.428.428.4 0.90.90.9 220220220 ‐‐‐4.94.94.9 111 111

416204162041620 Salt Lake City UTSalt Lake City UTSalt Lake City UTSalt Lake City UT 76.776.776.7 ‐‐‐4.24.24.2 1.11.11.1 175175175 ‐‐‐6.66.66.6 111 111

416604166041660 San Angelo TXSan Angelo TXSan Angelo TXSan Angelo TX 41.141.141.1 ‐‐‐0.30.30.3 ‐‐‐0.70.70.7 276276276 ‐‐‐6.76.76.7 111 111

417004170041700 San Antonio TXSan Antonio TXSan Antonio TXSan Antonio TX 58.158.158.1 ‐‐‐4.44.44.4 1.41.41.4 189189189 ‐‐‐6.66.66.6 111 000

417404174041740 San Diego CASan Diego CASan Diego CASan Diego CA 15.415.415.4 ‐‐‐31.131.131.1 1.31.31.3 999999 ‐‐‐9.09.09.0 111 111

418844188441884 San Francisco CA [Metropolitan Division]San Francisco CA [Metropolitan Division]San Francisco CA [Metropolitan Division]San Francisco CA [Metropolitan Division] 10.710.710.7 ‐‐‐22.122.122.1 0.10.10.1 717171 ‐‐‐10.410.410.4 000 111

419404194041940 San Jose CASan Jose CASan Jose CASan Jose CA 13.013.013.0 ‐‐‐24.624.624.6 1.71.71.7 868686 ‐‐‐10.010.010.0 111 111

420204202042020 San Luis Obispo CASan Luis Obispo CASan Luis Obispo CASan Luis Obispo CA 48.648.648.6 ‐‐‐40.240.240.2 2.72.72.7 969696 ‐‐‐6.06.06.0 111 111

417804178041780 Sandusky OHSandusky OHSandusky OHSandusky OH 43.843.843.8 ‐‐‐27.727.727.7 10.310.310.3 288288288 ‐‐‐7.57.57.5 111 111

420444204442044 Santa Ana CA [Metropolitan Division]Santa Ana CA [Metropolitan Division]Santa Ana CA [Metropolitan Division]Santa Ana CA [Metropolitan Division] 21.921.921.9 ‐‐‐13.513.513.5 0.60.60.6 797979 ‐‐‐9.69.69.6 111 111

420604206042060 Santa Barbara CASanta Barbara CASanta Barbara CASanta Barbara CA 23.323.323.3 ‐‐‐28.128.128.1 0.70.70.7 858585 ‐‐‐9.39.39.3 111 111

421004210042100 Santa Cruz CASanta Cruz CASanta Cruz CASanta Cruz CA 19.719.719.7 ‐‐‐40.940.940.9 2.52.52.5 868686 ‐‐‐9.79.79.7 111 111

421404214042140 Santa Fe NMSanta Fe NMSanta Fe NMSanta Fe NM 55.755.755.7 ‐‐‐11.611.611.6 0.60.60.6 175175175 ‐‐‐9.99.99.9 111 111

422204222042220 Santa Rosa CASanta Rosa CASanta Rosa CASanta Rosa CA 11.011.011.0 ‐‐‐50.650.650.6 1.21.21.2 120120120 ‐‐‐9.69.69.6 111 111

423404234042340 Savannah GASavannah GASavannah GASavannah GA 70.770.770.7 2.22.22.2 0.40.40.4 219219219 ‐‐‐4.14.14.1 111 111

425404254042540 Scranton PAScranton PAScranton PAScranton PA 55.055.055.0 ‐‐‐4.04.04.0 1.41.41.4 244244244 ‐‐‐4.34.34.3 111 111

426444264442644 Seattle WA [Metropolitan Division]Seattle WA [Metropolitan Division]Seattle WA [Metropolitan Division]Seattle WA [Metropolitan Division] 61.161.161.1 ‐‐‐19.119.119.1 2.12.12.1 137137137 ‐‐‐6.46.46.4 000 111

426804268042680 Sebastian FLSebastian FLSebastian FLSebastian FL 37.937.937.9 ‐‐‐34.234.234.2 0.30.30.3 219219219 ‐‐‐2.82.82.8 111 111

431004310043100 Sheboygan WISheboygan WISheboygan WISheboygan WI 46.546.546.5 ‐‐‐11.511.511.5 1.71.71.7 286286286 ‐‐‐5.65.65.6 111 111

433004330043300 Sherman TXSherman TXSherman TXSherman TX 30.930.930.9 ‐‐‐16.416.416.4 0.30.30.3 316316316 ‐‐‐8.48.48.4 111 111

433404334043340 Shreveport LAShreveport LAShreveport LAShreveport LA 10.410.410.4 ‐‐‐5.25.25.2 1.61.61.6 176176176 ‐‐‐4.44.44.4 111 111

435804358043580 Sioux City IASioux City IASioux City IASioux City IA 18.118.118.1 ‐‐‐9.59.59.5 ‐‐‐0.60.60.6 298298298 ‐‐‐7.27.27.2 111 111

436204362043620 Sioux Falls SDSioux Falls SDSioux Falls SDSioux Falls SD 44.744.744.7 ‐‐‐6.16.16.1 1.61.61.6 220220220 ‐‐‐2.12.12.1 111 000

437804378043780 South Bend INSouth Bend INSouth Bend INSouth Bend IN 40.240.240.2 ‐‐‐15.015.015.0 0.00.00.0 349349349 ‐‐‐4.64.64.6 111 111

439004390043900 Spartanburg SCSpartanburg SCSpartanburg SCSpartanburg SC 24.624.624.6 ‐‐‐3.63.63.6 0.80.80.8 224224224 ‐‐‐2.92.92.9 111 111

440604406044060 Spokane WASpokane WASpokane WASpokane WA 39.439.439.4 ‐‐‐15.815.815.8 0.90.90.9 188188188 ‐‐‐5.25.25.2 111 111

441004410044100 Springfield ILSpringfield ILSpringfield ILSpringfield IL 4.44.44.4 ‐‐‐12.612.612.6 0.80.80.8 270270270 ‐‐‐5.95.95.9 000 000

441404414044140 Springfield MASpringfield MASpringfield MASpringfield MA 7.77.77.7 ‐‐‐16.016.016.0 0.30.30.3 187187187 ‐‐‐5.85.85.8 111 111

441804418044180 Springfield MOSpringfield MOSpringfield MOSpringfield MO 51.051.051.0 ‐‐‐10.510.510.5 0.90.90.9 220220220 ‐‐‐5.15.15.1 111 111

442204422044220 Springfield OHSpringfield OHSpringfield OHSpringfield OH 21.121.121.1 ‐‐‐16.216.216.2 3.83.83.8 287287287 ‐‐‐3.43.43.4 000 111

410604106041060 St. Cloud MNSt. Cloud MNSt. Cloud MNSt. Cloud MN 26.226.226.2 ‐‐‐10.110.110.1 ‐‐‐0.60.60.6 263263263 ‐‐‐5.85.85.8 000 111

411004110041100 St. George UTSt. George UTSt. George UTSt. George UT 95.895.895.8 ‐‐‐19.819.819.8 0.90.90.9 218218218 ‐‐‐1.11.11.1 111 111

411404114041140 St. Joseph MOSt. Joseph MOSt. Joseph MOSt. Joseph MO 47.447.447.4 ‐‐‐8.68.68.6 ‐‐‐0.70.70.7 324324324 ‐‐‐7.47.47.4 111 111

411804118041180 St. Louis MOSt. Louis MOSt. Louis MOSt. Louis MO 41.541.541.5 ‐‐‐5.75.75.7 1.01.01.0 267267267 ‐‐‐4.94.94.9 111 111

443004430044300 State College PAState College PAState College PAState College PA 12.012.012.0 11.811.811.8 0.30.30.3 197197197 ‐‐‐4.34.34.3 000 000

446004460044600 Steubenville OHSteubenville OHSteubenville OHSteubenville OH 43.243.243.2 ‐‐‐7.67.67.6 2.22.22.2 321321321 ‐‐‐9.39.39.3 000 111

447004470044700 Stockton CAStockton CAStockton CAStockton CA 32.132.132.1 ‐‐‐47.747.747.7 ‐‐‐1.11.11.1 173173173 ‐‐‐6.46.46.4 111 111

449404494044940 Sumter SCSumter SCSumter SCSumter SC 64.164.164.1 10.410.410.4 0.70.70.7 201201201 ‐‐‐3.33.33.3 000 000

450604506045060 Syracuse NYSyracuse NYSyracuse NYSyracuse NY 7.87.87.8 ‐‐‐17.917.917.9 0.60.60.6 268268268 ‐‐‐3.13.13.1 111 111

451044510445104 Tacoma WA [Metropolitan Division]Tacoma WA [Metropolitan Division]Tacoma WA [Metropolitan Division]Tacoma WA [Metropolitan Division] 57.757.757.7 ‐‐‐33.833.833.8 ‐‐‐0.20.20.2 190190190 ‐‐‐3.33.33.3 111 111

452204522045220 Tallahassee FLTallahassee FLTallahassee FLTallahassee FL 31.631.631.6 ‐‐‐18.318.318.3 0.40.40.4 202202202 ‐‐‐5.35.35.3 000 111

453004530045300 Tampa FLTampa FLTampa FLTampa FL 40.940.940.9 ‐‐‐28.728.728.7 0.80.80.8 210210210 ‐‐‐5.65.65.6 111 111

454604546045460 Terre Haute INTerre Haute INTerre Haute INTerre Haute IN 6.76.76.7 ‐‐‐15.015.015.0 ‐‐‐0.90.90.9 330330330 ‐‐‐6.36.36.3 111 111

455004550045500 Texarkana TXTexarkana TXTexarkana TXTexarkana TX 22.522.522.5 ‐‐‐6.56.56.5 0.00.00.0 273273273 ‐‐‐7.27.27.2 000 000

457804578045780 Toledo OHToledo OHToledo OHToledo OH 46.546.546.5 ‐‐‐24.024.024.0 1.41.41.4 405405405 ‐‐‐1.21.21.2 111 111

458204582045820 Topeka KSTopeka KSTopeka KSTopeka KS 50.650.650.6 ‐‐‐14.214.214.2 ‐‐‐1.81.81.8 302302302 ‐‐‐6.46.46.4 111 111

459404594045940 Trenton NJTrenton NJTrenton NJTrenton NJ 8.88.88.8 ‐‐‐13.713.713.7 ‐‐‐1.81.81.8 182182182 ‐‐‐7.07.07.0 111 111

460604606046060 Tucson AZTucson AZTucson AZTucson AZ 64.964.964.9 ‐‐‐33.833.833.8 ‐‐‐0.50.50.5 192192192 ‐‐‐5.75.75.7 111 111

461404614046140 Tulsa OKTulsa OKTulsa OKTulsa OK 20.120.120.1 ‐‐‐6.36.36.3 1.51.51.5 225225225 ‐‐‐4.14.14.1 000 111

462204622046220 Tuscaloosa ALTuscaloosa ALTuscaloosa ALTuscaloosa AL 41.041.041.0 ‐‐‐4.24.24.2 ‐‐‐0.20.20.2 202202202 ‐‐‐3.43.43.4 111 111

463404634046340 Tyler TXTyler TXTyler TXTyler TX 31.831.831.8 ‐‐‐6.16.16.1 0.90.90.9 293293293 ‐‐‐9.19.19.1 111 111

465404654046540 Utica NYUtica NYUtica NYUtica NY 6.56.56.5 ‐‐‐6.46.46.4 ‐‐‐0.20.20.2 268268268 ‐‐‐2.92.92.9 111 111



466604666046660 Valdosta GAValdosta GAValdosta GAValdosta GA 61.661.661.6 ‐‐‐4.84.84.8 ‐‐‐1.21.21.2 235235235 ‐‐‐3.33.33.3 111 111

467004670046700 Vallejo CAVallejo CAVallejo CAVallejo CA 27.127.127.1 ‐‐‐48.648.648.6 ‐‐‐2.02.02.0 204204204 ‐‐‐8.18.18.1 111 111

470204702047020 Victoria TXVictoria TXVictoria TXVictoria TX 4.24.24.2 ‐‐‐19.019.019.0 2.02.02.0 291291291 ‐‐‐8.48.48.4 000 111

472204722047220 Vineland NJVineland NJVineland NJVineland NJ 49.849.849.8 ‐‐‐7.47.47.4 ‐‐‐2.82.82.8 242242242 2.12.12.1 111 111

472604726047260 Virginia Beach VAVirginia Beach VAVirginia Beach VAVirginia Beach VA 76.476.476.4 ‐‐‐2.02.02.0 0.20.20.2 181181181 ‐‐‐4.94.94.9 111 111

473004730047300 Visalia CAVisalia CAVisalia CAVisalia CA 8.78.78.7 ‐‐‐64.664.664.6 0.60.60.6 199199199 ‐‐‐4.14.14.1 111 111

473804738047380 Waco TXWaco TXWaco TXWaco TX 33.233.233.2 ‐‐‐1.91.91.9 1.11.11.1 296296296 ‐‐‐6.66.66.6 000 000

475804758047580 Warner Robins GAWarner Robins GAWarner Robins GAWarner Robins GA 27.827.827.8 ‐‐‐10.910.910.9 0.70.70.7 330330330 ‐‐‐3.63.63.6 111 111

476444764447644 Warren MI [Metropolitan Division]Warren MI [Metropolitan Division]Warren MI [Metropolitan Division]Warren MI [Metropolitan Division] 62.962.962.9 ‐‐‐31.031.031.0 0.70.70.7 269269269 ‐‐‐6.76.76.7 111 111

478944789447894 Washington DC [Metropolitan Division]Washington DC [Metropolitan Division]Washington DC [Metropolitan Division]Washington DC [Metropolitan Division] 16.716.716.7 ‐‐‐8.48.48.4 0.20.20.2 152152152 ‐‐‐7.47.47.4 000 000

479404794047940 Waterloo IAWaterloo IAWaterloo IAWaterloo IA 29.529.529.5 3.73.73.7 1.01.01.0 269269269 ‐‐‐5.15.15.1 000 000

481404814048140 Wausau WIWausau WIWausau WIWausau WI 31.631.631.6 ‐‐‐5.65.65.6 0.20.20.2 286286286 ‐‐‐3.83.83.8 111 111

483004830048300 Wenatchee WAWenatchee WAWenatchee WAWenatchee WA 46.746.746.7 ‐‐‐16.416.416.4 2.22.22.2 177177177 ‐‐‐4.24.24.2 111 111

484244842448424 West Palm Beach FL [Metropolitan Division]West Palm Beach FL [Metropolitan Division]West Palm Beach FL [Metropolitan Division]West Palm Beach FL [Metropolitan Division] 21.721.721.7 ‐‐‐23.723.723.7 0.60.60.6 151151151 ‐‐‐8.18.18.1 000 111

485404854048540 Wheeling WVWheeling WVWheeling WVWheeling WV 20.820.820.8 ‐‐‐5.35.35.3 1.71.71.7 306306306 ‐‐‐10.110.110.1 000 111

486604866048660 Wichita Falls TXWichita Falls TXWichita Falls TXWichita Falls TX 10.410.410.4 ‐‐‐8.08.08.0 ‐‐‐0.90.90.9 337337337 ‐‐‐7.97.97.9 111 111

486204862048620 Wichita KSWichita KSWichita KSWichita KS 54.854.854.8 ‐‐‐11.211.211.2 0.70.70.7 266266266 ‐‐‐5.25.25.2 111 111

487004870048700 Williamsport PAWilliamsport PAWilliamsport PAWilliamsport PA 20.120.120.1 ‐‐‐3.63.63.6 0.70.70.7 232232232 ‐‐‐5.05.05.0 000 000

488644886448864 Wilmington DE [Metropolitan Division]Wilmington DE [Metropolitan Division]Wilmington DE [Metropolitan Division]Wilmington DE [Metropolitan Division] 50.750.750.7 ‐‐‐15.015.015.0 ‐‐‐1.01.01.0 197197197 ‐‐‐5.25.25.2 111 111

489004890048900 Wilmington NCWilmington NCWilmington NCWilmington NC 70.070.070.0 ‐‐‐10.010.010.0 ‐‐‐1.01.01.0 168168168 ‐‐‐1.01.01.0 111 111

490204902049020 Winchester VAWinchester VAWinchester VAWinchester VA 55.055.055.0 ‐‐‐19.919.919.9 3.33.33.3 201201201 ‐‐‐4.14.14.1 000 111

491804918049180 Winston NCWinston NCWinston NCWinston NC 59.859.859.8 1.71.71.7 0.50.50.5 230230230 ‐‐‐2.92.92.9 111 111

493404934049340 Worcester MAWorcester MAWorcester MAWorcester MA 7.17.17.1 ‐‐‐27.327.327.3 1.91.91.9 195195195 ‐‐‐5.05.05.0 111 111

494204942049420 Yakima WAYakima WAYakima WAYakima WA 48.548.548.5 ‐‐‐17.717.717.7 ‐‐‐0.70.70.7 162162162 ‐‐‐6.36.36.3 111 111

496204962049620 York PAYork PAYork PAYork PA 55.255.255.2 ‐‐‐1.41.41.4 1.21.21.2 240240240 ‐‐‐1.91.91.9 111 111

496604966049660 Youngstown OHYoungstown OHYoungstown OHYoungstown OH 10.110.110.1 ‐‐‐22.322.322.3 1.61.61.6 371371371 ‐‐‐5.75.75.7 111 111

497004970049700 Yuba City CAYuba City CAYuba City CAYuba City CA 72.272.272.2 ‐‐‐39.839.839.8 ‐‐‐1.11.11.1 296296296 ‐‐‐1.71.71.7 111 111

497404974049740 Yuma AZYuma AZYuma AZYuma AZ 54.954.954.9 ‐‐‐20.620.620.6 ‐‐‐2.02.02.0 257257257 ‐‐‐4.34.34.3 111 111



Housing Market Risk RankingHousing Market Risk Ranking Incorporating data through 2011Q2Incorporating data through 2011Q2Incorporating data through 2011Q2


FIP FIP FIP FIP Metro AreaMetro AreaMetro AreaMetro Area Leading House Price Indicator %Leading House Price Indicator %Leading House Price Indicator %Leading House Price Indicator % House Price BalanceHouse Price BalanceHouse Price BalanceHouse Price Balance Months of Excess SupplyMonths of Excess SupplyMonths of Excess SupplyMonths of Excess Supply

101801018010180 Abilene TXAbilene TXAbilene TXAbilene TX 49.449.449.4 0.00.00.0 ‐‐‐8.48.48.4

104201042010420 Akron OHAkron OHAkron OHAkron OH 11.411.411.4 ‐‐‐2.02.02.0 ‐‐‐5.05.05.0

105001050010500 Albany GAAlbany GAAlbany GAAlbany GA 60.060.060.0 0.00.00.0 ‐‐‐3.73.73.7

105801058010580 Albany NYAlbany NYAlbany NYAlbany NY 29.929.929.9 0.00.00.0 ‐‐‐2.22.22.2

107401074010740 Albuquerque NMAlbuquerque NMAlbuquerque NMAlbuquerque NM 61.061.061.0 0.00.00.0 ‐‐‐6.36.36.3

107801078010780 Alexandria LAAlexandria LAAlexandria LAAlexandria LA 40.640.640.6 0.00.00.0 ‐‐‐0.50.50.5

109001090010900 Allentown PAAllentown PAAllentown PAAllentown PA 40.440.440.4 ‐‐‐2.02.02.0 ‐‐‐2.62.62.6

110201102011020 Altoona PAAltoona PAAltoona PAAltoona PA 44.044.044.0 1.01.01.0 ‐‐‐5.95.95.9

111001110011100 Amarillo TXAmarillo TXAmarillo TXAmarillo TX 20.620.620.6 0.00.00.0 ‐‐‐6.56.56.5

111801118011180 Ames IAAmes IAAmes IAAmes IA 5.75.75.7 ‐‐‐2.02.02.0 ‐‐‐7.37.37.3

112601126011260 Anchorage AKAnchorage AKAnchorage AKAnchorage AK 32.932.932.9 ‐‐‐1.01.01.0 ‐‐‐10.310.310.3

113001130011300 Anderson INAnderson INAnderson INAnderson IN 61.361.361.3 ‐‐‐1.01.01.0 ‐‐‐7.67.67.6

113401134011340 Anderson SCAnderson SCAnderson SCAnderson SC 51.651.651.6 0.00.00.0 ‐‐‐4.44.44.4

114601146011460 Ann Arbor MIAnn Arbor MIAnn Arbor MIAnn Arbor MI 26.526.526.5 ‐‐‐1.01.01.0 ‐‐‐6.66.66.6

115001150011500 Anniston ALAnniston ALAnniston ALAnniston AL 43.243.243.2 0.00.00.0 ‐‐‐3.23.23.2

115401154011540 Appleton WIAppleton WIAppleton WIAppleton WI 21.721.721.7 ‐‐‐1.01.01.0 ‐‐‐5.35.35.3

117001170011700 Asheville NCAsheville NCAsheville NCAsheville NC 78.778.778.7 1.01.01.0 ‐‐‐4.64.64.6

120201202012020 Athens GAAthens GAAthens GAAthens GA 77.977.977.9 0.00.00.0 ‐‐‐3.33.33.3

120601206012060 Atlanta GAAtlanta GAAtlanta GAAtlanta GA 38.938.938.9 ‐‐‐1.01.01.0 ‐‐‐5.85.85.8

121001210012100 Atlantic City NJAtlantic City NJAtlantic City NJAtlantic City NJ 23.723.723.7 ‐‐‐1.01.01.0 1.71.71.7

122201222012220 Auburn ALAuburn ALAuburn ALAuburn AL 38.038.038.0 0.00.00.0 ‐‐‐0.70.70.7

122601226012260 Augusta GAAugusta GAAugusta GAAugusta GA 61.461.461.4 0.00.00.0 ‐‐‐4.14.14.1

124201242012420 Austin TXAustin TXAustin TXAustin TX 63.463.463.4 1.01.01.0 ‐‐‐4.94.94.9

125401254012540 Bakersfield CABakersfield CABakersfield CABakersfield CA 23.023.023.0 ‐‐‐2.02.02.0 ‐‐‐3.93.93.9

125801258012580 Baltimore MDBaltimore MDBaltimore MDBaltimore MD 8.28.28.2 ‐‐‐2.02.02.0 ‐‐‐6.46.46.4

126201262012620 Bangor MEBangor MEBangor MEBangor ME 22.922.922.9 ‐‐‐2.02.02.0 ‐‐‐1.61.61.6

127001270012700 Barnstable Town MABarnstable Town MABarnstable Town MABarnstable Town MA 45.845.845.8 ‐‐‐2.02.02.0 ‐‐‐6.96.96.9

129401294012940 Baton Rouge LABaton Rouge LABaton Rouge LABaton Rouge LA 49.949.949.9 0.00.00.0 ‐‐‐2.22.22.2

129801298012980 Battle Creek MIBattle Creek MIBattle Creek MIBattle Creek MI 70.770.770.7 ‐‐‐1.01.01.0 ‐‐‐2.52.52.5

130201302013020 Bay City MIBay City MIBay City MIBay City MI 43.043.043.0 ‐‐‐1.01.01.0 ‐‐‐4.34.34.3

131401314013140 Beaumont TXBeaumont TXBeaumont TXBeaumont TX 59.959.959.9 ‐‐‐1.01.01.0 ‐‐‐1.91.91.9

133801338013380 Bellingham WABellingham WABellingham WABellingham WA 54.354.354.3 ‐‐‐2.02.02.0 ‐‐‐5.85.85.8

134601346013460 Bend ORBend ORBend ORBend OR 88.788.788.7 ‐‐‐2.02.02.0 ‐‐‐3.43.43.4

136441364413644 Bethesda MD [Metropolitan Division]Bethesda MD [Metropolitan Division]Bethesda MD [Metropolitan Division]Bethesda MD [Metropolitan Division] 19.619.619.6 ‐‐‐1.01.01.0 ‐‐‐8.08.08.0

137401374013740 Billings MTBillings MTBillings MTBillings MT 27.527.527.5 0.00.00.0 ‐‐‐5.45.45.4

137801378013780 Binghamton NYBinghamton NYBinghamton NYBinghamton NY 50.050.050.0 0.00.00.0 ‐‐‐2.72.72.7

138201382013820 Birmingham ALBirmingham ALBirmingham ALBirmingham AL 75.175.175.1 0.00.00.0 ‐‐‐2.22.22.2

139001390013900 Bismarck NDBismarck NDBismarck NDBismarck ND 26.426.426.4 0.00.00.0 ‐‐‐3.53.53.5

139801398013980 Blacksburg VABlacksburg VABlacksburg VABlacksburg VA 67.167.167.1 1.01.01.0 ‐‐‐1.71.71.7

140601406014060 Bloomington ILBloomington ILBloomington ILBloomington IL 21.421.421.4 ‐‐‐1.01.01.0 ‐‐‐5.15.15.1

140201402014020 Bloomington INBloomington INBloomington INBloomington IN 6.76.76.7 0.00.00.0 ‐‐‐6.66.66.6

142601426014260 Boise City IDBoise City IDBoise City IDBoise City ID 63.763.763.7 0.00.00.0 ‐‐‐2.42.42.4

144841448414484 Boston MA [Metropolitan Division]Boston MA [Metropolitan Division]Boston MA [Metropolitan Division]Boston MA [Metropolitan Division] 17.617.617.6 ‐‐‐1.01.01.0 ‐‐‐8.58.58.5

145001450014500 Boulder COBoulder COBoulder COBoulder CO 28.728.728.7 0.00.00.0 ‐‐‐8.18.18.1

145401454014540 Bowling Green KYBowling Green KYBowling Green KYBowling Green KY 14.114.114.1 ‐‐‐1.01.01.0 ‐‐‐4.74.74.7

147401474014740 Bremerton WABremerton WABremerton WABremerton WA 49.049.049.0 ‐‐‐2.02.02.0 ‐‐‐5.55.55.5

148601486014860 Bridgeport CTBridgeport CTBridgeport CTBridgeport CT 33.133.133.1 ‐‐‐2.02.02.0 ‐‐‐7.97.97.9

151801518015180 Brownsville TXBrownsville TXBrownsville TXBrownsville TX 28.728.728.7 ‐‐‐1.01.01.0 ‐‐‐4.74.74.7

152601526015260 Brunswick GABrunswick GABrunswick GABrunswick GA 78.278.278.2 0.00.00.0 ‐‐‐3.83.83.8

153801538015380 Buffalo NYBuffalo NYBuffalo NYBuffalo NY 6.86.86.8 ‐‐‐2.02.02.0 ‐‐‐3.33.33.3

155001550015500 Burlington NCBurlington NCBurlington NCBurlington NC 28.228.228.2 ‐‐‐2.02.02.0 ‐‐‐3.43.43.4

155401554015540 Burlington VTBurlington VTBurlington VTBurlington VT 57.857.857.8 0.00.00.0 ‐‐‐4.94.94.9

157641576415764 Cambridge MA [Metropolitan Division]Cambridge MA [Metropolitan Division]Cambridge MA [Metropolitan Division]Cambridge MA [Metropolitan Division] 12.312.312.3 ‐‐‐2.02.02.0 ‐‐‐8.48.48.4



158041580415804 Camden NJ [Metropolitan Division]Camden NJ [Metropolitan Division]Camden NJ [Metropolitan Division]Camden NJ [Metropolitan Division] 22.022.022.0 ‐‐‐2.02.02.0 ‐‐‐3.33.33.3

159401594015940 Canton OHCanton OHCanton OHCanton OH 64.264.264.2 ‐‐‐2.02.02.0 ‐‐‐3.83.83.8

159801598015980 Cape Coral FLCape Coral FLCape Coral FLCape Coral FL 60.360.360.3 ‐‐‐2.02.02.0 ‐‐‐4.74.74.7

160201602016020 Cape Girardeau MOCape Girardeau MOCape Girardeau MOCape Girardeau MO 24.124.124.1 ‐‐‐2.02.02.0 ‐‐‐8.38.38.3

161801618016180 Carson City NVCarson City NVCarson City NVCarson City NV 80.680.680.6 0.00.00.0 ‐‐‐9.99.99.9

162201622016220 Casper WYCasper WYCasper WYCasper WY 43.643.643.6 ‐‐‐1.01.01.0 ‐‐‐2.32.32.3

163001630016300 Cedar Rapids IACedar Rapids IACedar Rapids IACedar Rapids IA 13.713.713.7 ‐‐‐2.02.02.0 ‐‐‐2.92.92.9

165801658016580 Champaign ILChampaign ILChampaign ILChampaign IL 28.628.628.6 0.00.00.0 ‐‐‐5.35.35.3

167001670016700 Charleston SCCharleston SCCharleston SCCharleston SC 76.976.976.9 0.00.00.0 ‐‐‐2.72.72.7

166201662016620 Charleston WVCharleston WVCharleston WVCharleston WV 36.136.136.1 ‐‐‐1.01.01.0 ‐‐‐7.27.27.2

167401674016740 Charlotte NCCharlotte NCCharlotte NCCharlotte NC 63.463.463.4 ‐‐‐2.02.02.0 ‐‐‐3.33.33.3

168201682016820 Charlottesville VACharlottesville VACharlottesville VACharlottesville VA 54.054.054.0 0.00.00.0 ‐‐‐3.73.73.7

168601686016860 Chattanooga TNChattanooga TNChattanooga TNChattanooga TN 78.278.278.2 1.01.01.0 ‐‐‐4.84.84.8

169401694016940 Cheyenne WYCheyenne WYCheyenne WYCheyenne WY 36.136.136.1 ‐‐‐2.02.02.0 ‐‐‐7.37.37.3

169741697416974 Chicago IL [Metropolitan Division]Chicago IL [Metropolitan Division]Chicago IL [Metropolitan Division]Chicago IL [Metropolitan Division] 67.567.567.5 ‐‐‐1.01.01.0 ‐‐‐8.08.08.0

170201702017020 Chico CAChico CAChico CAChico CA 27.927.927.9 ‐‐‐2.02.02.0 ‐‐‐4.04.04.0

171401714017140 Cincinnati OHCincinnati OHCincinnati OHCincinnati OH 21.821.821.8 ‐‐‐2.02.02.0 ‐‐‐3.63.63.6

173001730017300 Clarksville TNClarksville TNClarksville TNClarksville TN 18.618.618.6 0.00.00.0 ‐‐‐4.84.84.8

174601746017460 Cleveland OHCleveland OHCleveland OHCleveland OH 12.512.512.5 ‐‐‐2.02.02.0 ‐‐‐5.25.25.2

174201742017420 Cleveland TNCleveland TNCleveland TNCleveland TN 80.780.780.7 0.00.00.0 ‐‐‐2.12.12.1

176601766017660 Coeur d'Alene IDCoeur d'Alene IDCoeur d'Alene IDCoeur d'Alene ID 60.160.160.1 0.00.00.0 ‐‐‐1.81.81.8

177801778017780 College Station TXCollege Station TXCollege Station TXCollege Station TX 12.412.412.4 0.00.00.0 ‐‐‐4.44.44.4

178201782017820 Colorado Springs COColorado Springs COColorado Springs COColorado Springs CO 25.825.825.8 ‐‐‐2.02.02.0 ‐‐‐7.17.17.1

178601786017860 Columbia MOColumbia MOColumbia MOColumbia MO 27.427.427.4 ‐‐‐1.01.01.0 ‐‐‐3.83.83.8

179001790017900 Columbia SCColumbia SCColumbia SCColumbia SC 56.656.656.6 0.00.00.0 ‐‐‐3.03.03.0

179801798017980 Columbus GAColumbus GAColumbus GAColumbus GA 46.046.046.0 ‐‐‐1.01.01.0 ‐‐‐5.55.55.5

180201802018020 Columbus INColumbus INColumbus INColumbus IN 21.521.521.5 ‐‐‐1.01.01.0 ‐‐‐4.64.64.6

181401814018140 Columbus OHColumbus OHColumbus OHColumbus OH 12.512.512.5 ‐‐‐2.02.02.0 ‐‐‐6.46.46.4

185801858018580 Corpus Christi TXCorpus Christi TXCorpus Christi TXCorpus Christi TX 40.340.340.3 ‐‐‐1.01.01.0 ‐‐‐5.15.15.1

187001870018700 Corvallis ORCorvallis ORCorvallis ORCorvallis OR 40.740.740.7 ‐‐‐1.01.01.0 ‐‐‐8.78.78.7

188801888018880 Crestview FLCrestview FLCrestview FLCrestview FL 53.453.453.4 ‐‐‐1.01.01.0 ‐‐‐4.34.34.3

190601906019060 Cumberland MDCumberland MDCumberland MDCumberland MD 7.97.97.9 ‐‐‐2.02.02.0 ‐‐‐5.95.95.9

191241912419124 Dallas TX [Metropolitan Division]Dallas TX [Metropolitan Division]Dallas TX [Metropolitan Division]Dallas TX [Metropolitan Division] 15.715.715.7 0.00.00.0 ‐‐‐4.24.24.2

191401914019140 Dalton GADalton GADalton GADalton GA 81.581.581.5 0.00.00.0 ‐‐‐7.57.57.5

191801918019180 Danville ILDanville ILDanville ILDanville IL 45.245.245.2 0.00.00.0 ‐‐‐9.49.49.4

192601926019260 Danville VADanville VADanville VADanville VA 57.457.457.4 0.00.00.0 ‐‐‐5.85.85.8

193401934019340 Davenport ILDavenport ILDavenport ILDavenport IL 33.133.133.1 ‐‐‐1.01.01.0 ‐‐‐7.37.37.3

193801938019380 Dayton OHDayton OHDayton OHDayton OH 29.429.429.4 ‐‐‐2.02.02.0 ‐‐‐5.25.25.2

194601946019460 Decatur ALDecatur ALDecatur ALDecatur AL 42.542.542.5 0.00.00.0 ‐‐‐6.36.36.3

195001950019500 Decatur ILDecatur ILDecatur ILDecatur IL 22.922.922.9 ‐‐‐2.02.02.0 ‐‐‐5.55.55.5

196601966019660 Deltona FLDeltona FLDeltona FLDeltona FL 55.355.355.3 ‐‐‐2.02.02.0 ‐‐‐4.24.24.2

197401974019740 Denver CODenver CODenver CODenver CO 35.735.735.7 ‐‐‐1.01.01.0 ‐‐‐8.48.48.4

197801978019780 Des Moines IADes Moines IADes Moines IADes Moines IA 49.649.649.6 ‐‐‐1.01.01.0 ‐‐‐3.23.23.2

198041980419804 Detroit MI [Metropolitan Division]Detroit MI [Metropolitan Division]Detroit MI [Metropolitan Division]Detroit MI [Metropolitan Division] 52.752.752.7 ‐‐‐2.02.02.0 23.223.223.2

200202002020020 Dothan ALDothan ALDothan ALDothan AL 36.136.136.1 0.00.00.0 ‐‐‐5.25.25.2

201002010020100 Dover DEDover DEDover DEDover DE 43.443.443.4 ‐‐‐2.02.02.0 ‐‐‐2.42.42.4

202202022020220 Dubuque IADubuque IADubuque IADubuque IA 6.06.06.0 ‐‐‐1.01.01.0 ‐‐‐3.23.23.2

202602026020260 Duluth MNDuluth MNDuluth MNDuluth MN 32.732.732.7 ‐‐‐2.02.02.0 ‐‐‐6.06.06.0

205002050020500 Durham NCDurham NCDurham NCDurham NC 70.070.070.0 0.00.00.0 ‐‐‐4.04.04.0

207402074020740 Eau Claire WIEau Claire WIEau Claire WIEau Claire WI 27.027.027.0 0.00.00.0 ‐‐‐5.05.05.0

207642076420764 Edison NJ [Metropolitan Division]Edison NJ [Metropolitan Division]Edison NJ [Metropolitan Division]Edison NJ [Metropolitan Division] 48.248.248.2 ‐‐‐1.01.01.0 ‐‐‐5.25.25.2

209402094020940 El Centro CAEl Centro CAEl Centro CAEl Centro CA 14.214.214.2 ‐‐‐2.02.02.0 ‐‐‐6.96.96.9

213402134021340 El Paso TXEl Paso TXEl Paso TXEl Paso TX 31.831.831.8 0.00.00.0 ‐‐‐4.74.74.7

210602106021060 Elizabethtown KYElizabethtown KYElizabethtown KYElizabethtown KY 11.711.711.7 0.00.00.0 ‐‐‐5.15.15.1

211402114021140 Elkhart INElkhart INElkhart INElkhart IN 29.629.629.6 ‐‐‐1.01.01.0 ‐‐‐0.90.90.9

213002130021300 Elmira NYElmira NYElmira NYElmira NY 17.417.417.4 0.00.00.0 ‐‐‐7.97.97.9

215002150021500 Erie PAErie PAErie PAErie PA 20.520.520.5 ‐‐‐2.02.02.0 ‐‐‐6.06.06.0

216602166021660 Eugene OREugene OREugene OREugene OR 59.159.159.1 ‐‐‐1.01.01.0 ‐‐‐7.57.57.5

217802178021780 Evansville INEvansville INEvansville INEvansville IN 16.316.316.3 ‐‐‐2.02.02.0 ‐‐‐5.35.35.3

218202182021820 Fairbanks AKFairbanks AKFairbanks AKFairbanks AK 3.53.53.5 ‐‐‐2.02.02.0 ‐‐‐10.210.210.2

220202202022020 Fargo NDFargo NDFargo NDFargo ND 28.828.828.8 0.00.00.0 ‐‐‐3.93.93.9



221402214022140 Farmington NMFarmington NMFarmington NMFarmington NM 45.245.245.2 0.00.00.0 ‐‐‐7.07.07.0

222202222022220 Fayetteville ARFayetteville ARFayetteville ARFayetteville AR 91.591.591.5 0.00.00.0 ‐‐‐5.25.25.2

221802218022180 Fayetteville NCFayetteville NCFayetteville NCFayetteville NC 8.88.88.8 ‐‐‐2.02.02.0 ‐‐‐4.44.44.4

223802238022380 Flagstaff AZFlagstaff AZFlagstaff AZFlagstaff AZ 56.756.756.7 ‐‐‐2.02.02.0 ‐‐‐8.28.28.2

224202242022420 Flint MIFlint MIFlint MIFlint MI 78.578.578.5 ‐‐‐2.02.02.0 9.49.49.4

225202252022520 Florence ALFlorence ALFlorence ALFlorence AL 25.925.925.9 0.00.00.0 ‐‐‐4.34.34.3

225002250022500 Florence SCFlorence SCFlorence SCFlorence SC 33.933.933.9 ‐‐‐1.01.01.0 ‐‐‐5.15.15.1

225402254022540 Fond du Lac WIFond du Lac WIFond du Lac WIFond du Lac WI 26.026.026.0 ‐‐‐1.01.01.0 ‐‐‐6.06.06.0

226602266022660 Fort Collins COFort Collins COFort Collins COFort Collins CO 10.410.410.4 ‐‐‐2.02.02.0 ‐‐‐8.18.18.1

227442274422744 Fort Lauderdale FL [Metropolitan Division]Fort Lauderdale FL [Metropolitan Division]Fort Lauderdale FL [Metropolitan Division]Fort Lauderdale FL [Metropolitan Division] 70.370.370.3 0.00.00.0 ‐‐‐8.88.88.8

229002290022900 Fort Smith ARFort Smith ARFort Smith ARFort Smith AR 49.949.949.9 0.00.00.0 ‐‐‐4.74.74.7

230602306023060 Fort Wayne INFort Wayne INFort Wayne INFort Wayne IN 22.522.522.5 ‐‐‐1.01.01.0 ‐‐‐4.74.74.7

231042310423104 Fort Worth TX [Metropolitan Division]Fort Worth TX [Metropolitan Division]Fort Worth TX [Metropolitan Division]Fort Worth TX [Metropolitan Division] 39.739.739.7 0.00.00.0 ‐‐‐5.15.15.1

234202342023420 Fresno CAFresno CAFresno CAFresno CA 18.418.418.4 ‐‐‐2.02.02.0 ‐‐‐3.73.73.7

234602346023460 Gadsden ALGadsden ALGadsden ALGadsden AL 46.646.646.6 0.00.00.0 ‐‐‐3.13.13.1

235402354023540 Gainesville FLGainesville FLGainesville FLGainesville FL 55.155.155.1 0.00.00.0 ‐‐‐4.94.94.9

235802358023580 Gainesville GAGainesville GAGainesville GAGainesville GA 72.572.572.5 ‐‐‐1.01.01.0 ‐‐‐4.24.24.2

238442384423844 Gary IN [Metropolitan Division]Gary IN [Metropolitan Division]Gary IN [Metropolitan Division]Gary IN [Metropolitan Division] 47.947.947.9 ‐‐‐2.02.02.0 ‐‐‐4.04.04.0

240202402024020 Glens Falls NYGlens Falls NYGlens Falls NYGlens Falls NY 2.02.02.0 ‐‐‐2.02.02.0 ‐‐‐2.42.42.4

241402414024140 Goldsboro NCGoldsboro NCGoldsboro NCGoldsboro NC 67.867.867.8 0.00.00.0 ‐‐‐6.76.76.7

242202422024220 Grand Forks NDGrand Forks NDGrand Forks NDGrand Forks ND 26.926.926.9 ‐‐‐1.01.01.0 ‐‐‐5.55.55.5

243002430024300 Grand Junction COGrand Junction COGrand Junction COGrand Junction CO 68.568.568.5 0.00.00.0 ‐‐‐3.43.43.4

243402434024340 Grand Rapids MIGrand Rapids MIGrand Rapids MIGrand Rapids MI 66.666.666.6 ‐‐‐2.02.02.0 ‐‐‐2.92.92.9

245002450024500 Great Falls MTGreat Falls MTGreat Falls MTGreat Falls MT 24.624.624.6 ‐‐‐1.01.01.0 ‐‐‐4.44.44.4

245402454024540 Greeley COGreeley COGreeley COGreeley CO 45.945.945.9 ‐‐‐1.01.01.0 ‐‐‐4.74.74.7

245802458024580 Green Bay WIGreen Bay WIGreen Bay WIGreen Bay WI 23.123.123.1 ‐‐‐2.02.02.0 ‐‐‐4.24.24.2

246602466024660 Greensboro NCGreensboro NCGreensboro NCGreensboro NC 56.756.756.7 0.00.00.0 ‐‐‐5.05.05.0

247802478024780 Greenville NCGreenville NCGreenville NCGreenville NC 26.826.826.8 ‐‐‐1.01.01.0 ‐‐‐4.94.94.9

248602486024860 Greenville SCGreenville SCGreenville SCGreenville SC 65.765.765.7 0.00.00.0 ‐‐‐2.22.22.2

250602506025060 Gulfport MSGulfport MSGulfport MSGulfport MS 63.863.863.8 0.00.00.0 1.91.91.9

251802518025180 Hagerstown MDHagerstown MDHagerstown MDHagerstown MD 38.038.038.0 ‐‐‐2.02.02.0 ‐‐‐0.30.30.3

252602526025260 Hanford CAHanford CAHanford CAHanford CA 90.890.890.8 ‐‐‐1.01.01.0 ‐‐‐3.43.43.4

254202542025420 Harrisburg PAHarrisburg PAHarrisburg PAHarrisburg PA 50.150.150.1 0.00.00.0 ‐‐‐3.83.83.8

255002550025500 Harrisonburg VAHarrisonburg VAHarrisonburg VAHarrisonburg VA 72.272.272.2 1.01.01.0 ‐‐‐1.21.21.2

255402554025540 Hartford CTHartford CTHartford CTHartford CT 26.126.126.1 ‐‐‐2.02.02.0 ‐‐‐5.45.45.4

256202562025620 Hattiesburg MSHattiesburg MSHattiesburg MSHattiesburg MS 35.635.635.6 0.00.00.0 ‐‐‐8.68.68.6

258602586025860 Hickory NCHickory NCHickory NCHickory NC 69.769.769.7 0.00.00.0 ‐‐‐5.05.05.0

259802598025980 Hinesville GAHinesville GAHinesville GAHinesville GA 75.875.875.8 0.00.00.0 ‐‐‐5.05.05.0

261002610026100 Holland MIHolland MIHolland MIHolland MI 56.156.156.1 ‐‐‐1.01.01.0 ‐‐‐4.54.54.5

261802618026180 Honolulu HIHonolulu HIHonolulu HIHonolulu HI 54.454.454.4 0.00.00.0 ‐‐‐6.36.36.3

263002630026300 Hot Springs ARHot Springs ARHot Springs ARHot Springs AR 77.377.377.3 0.00.00.0 ‐‐‐7.47.47.4

263802638026380 Houma LAHouma LAHouma LAHouma LA 7.57.57.5 0.00.00.0 ‐‐‐0.70.70.7

264202642026420 Houston TXHouston TXHouston TXHouston TX 19.219.219.2 0.00.00.0 ‐‐‐3.43.43.4

265802658026580 Huntington WVHuntington WVHuntington WVHuntington WV 9.09.09.0 0.00.00.0 ‐‐‐8.28.28.2

266202662026620 Huntsville ALHuntsville ALHuntsville ALHuntsville AL 64.064.064.0 0.00.00.0 ‐‐‐1.71.71.7

268202682026820 Idaho Falls IDIdaho Falls IDIdaho Falls IDIdaho Falls ID 18.118.118.1 ‐‐‐2.02.02.0 ‐‐‐4.54.54.5

269002690026900 Indianapolis INIndianapolis INIndianapolis INIndianapolis IN 41.141.141.1 ‐‐‐2.02.02.0 ‐‐‐4.74.74.7

269802698026980 Iowa City IAIowa City IAIowa City IAIowa City IA 40.940.940.9 0.00.00.0 ‐‐‐1.91.91.9

270602706027060 Ithaca NYIthaca NYIthaca NYIthaca NY 30.730.730.7 1.01.01.0 ‐‐‐5.25.25.2

271002710027100 Jackson MIJackson MIJackson MIJackson MI 26.326.326.3 ‐‐‐2.02.02.0 ‐‐‐7.37.37.3

271402714027140 Jackson MSJackson MSJackson MSJackson MS 54.854.854.8 0.00.00.0 ‐‐‐2.42.42.4

271802718027180 Jackson TNJackson TNJackson TNJackson TN 54.254.254.2 ‐‐‐2.02.02.0 ‐‐‐3.63.63.6

272602726027260 Jacksonville FLJacksonville FLJacksonville FLJacksonville FL 57.757.757.7 ‐‐‐2.02.02.0 ‐‐‐3.63.63.6

273402734027340 Jacksonville NCJacksonville NCJacksonville NCJacksonville NC 32.632.632.6 ‐‐‐2.02.02.0 ‐‐‐1.91.91.9

275002750027500 Janesville WIJanesville WIJanesville WIJanesville WI 46.746.746.7 0.00.00.0 ‐‐‐0.70.70.7

276202762027620 Jefferson City MOJefferson City MOJefferson City MOJefferson City MO 4.44.44.4 ‐‐‐2.02.02.0 ‐‐‐7.37.37.3

277402774027740 Johnson City TNJohnson City TNJohnson City TNJohnson City TN 45.545.545.5 0.00.00.0 ‐‐‐3.83.83.8

277802778027780 Johnstown PAJohnstown PAJohnstown PAJohnstown PA 15.015.015.0 ‐‐‐1.01.01.0 ‐‐‐4.64.64.6

278602786027860 Jonesboro ARJonesboro ARJonesboro ARJonesboro AR 4.74.74.7 ‐‐‐1.01.01.0 ‐‐‐1.31.31.3

279002790027900 Joplin MOJoplin MOJoplin MOJoplin MO 32.532.532.5 ‐‐‐1.01.01.0 ‐‐‐7.67.67.6

280202802028020 Kalamazoo MIKalamazoo MIKalamazoo MIKalamazoo MI 72.672.672.6 ‐‐‐2.02.02.0 ‐‐‐6.06.06.0



281002810028100 Kankakee ILKankakee ILKankakee ILKankakee IL 68.268.268.2 0.00.00.0 ‐‐‐3.53.53.5

281402814028140 Kansas City MOKansas City MOKansas City MOKansas City MO 65.765.765.7 ‐‐‐1.01.01.0 ‐‐‐7.37.37.3

284202842028420 Kennewick WAKennewick WAKennewick WAKennewick WA 2.42.42.4 ‐‐‐2.02.02.0 ‐‐‐4.34.34.3

286602866028660 Killeen TXKilleen TXKilleen TXKilleen TX 26.426.426.4 ‐‐‐1.01.01.0 ‐‐‐3.63.63.6

287002870028700 Kingsport TNKingsport TNKingsport TNKingsport TN 51.451.451.4 1.01.01.0 ‐‐‐4.84.84.8

287402874028740 Kingston NYKingston NYKingston NYKingston NY 18.918.918.9 0.00.00.0 ‐‐‐0.30.30.3

289402894028940 Knoxville TNKnoxville TNKnoxville TNKnoxville TN 76.576.576.5 1.01.01.0 ‐‐‐2.62.62.6

290202902029020 Kokomo INKokomo INKokomo INKokomo IN 22.822.822.8 ‐‐‐2.02.02.0 ‐‐‐6.76.76.7

291002910029100 La Crosse WILa Crosse WILa Crosse WILa Crosse WI 26.426.426.4 0.00.00.0 ‐‐‐4.34.34.3

291402914029140 Lafayette INLafayette INLafayette INLafayette IN 31.031.031.0 ‐‐‐2.02.02.0 ‐‐‐4.74.74.7

291802918029180 Lafayette LALafayette LALafayette LALafayette LA 35.235.235.2 0.00.00.0 ‐‐‐3.93.93.9

293402934029340 Lake Charles LALake Charles LALake Charles LALake Charles LA 22.422.422.4 ‐‐‐2.02.02.0 ‐‐‐0.40.40.4

294042940429404 Lake County IL [Metropolitan Division]Lake County IL [Metropolitan Division]Lake County IL [Metropolitan Division]Lake County IL [Metropolitan Division] 81.681.681.6 0.00.00.0 ‐‐‐7.27.27.2

294202942029420 Lake Havasu AZLake Havasu AZLake Havasu AZLake Havasu AZ 91.891.891.8 ‐‐‐1.01.01.0 ‐‐‐7.07.07.0

294602946029460 Lakeland FLLakeland FLLakeland FLLakeland FL 30.430.430.4 ‐‐‐2.02.02.0 0.10.10.1

295402954029540 Lancaster PALancaster PALancaster PALancaster PA 55.355.355.3 0.00.00.0 ‐‐‐4.74.74.7

296202962029620 Lansing MILansing MILansing MILansing MI 18.118.118.1 ‐‐‐2.02.02.0 ‐‐‐7.17.17.1

297002970029700 Laredo TXLaredo TXLaredo TXLaredo TX 44.444.444.4 0.00.00.0 ‐‐‐5.25.25.2

297402974029740 Las Cruces NMLas Cruces NMLas Cruces NMLas Cruces NM 30.130.130.1 ‐‐‐2.02.02.0 ‐‐‐4.24.24.2

298202982029820 Las Vegas NVLas Vegas NVLas Vegas NVLas Vegas NV 91.391.391.3 ‐‐‐2.02.02.0 ‐‐‐0.80.80.8

299402994029940 Lawrence KSLawrence KSLawrence KSLawrence KS 40.040.040.0 0.00.00.0 ‐‐‐5.15.15.1

300203002030020 Lawton OKLawton OKLawton OKLawton OK 5.85.85.8 ‐‐‐1.01.01.0 ‐‐‐8.28.28.2

301403014030140 Lebanon PALebanon PALebanon PALebanon PA 27.327.327.3 0.00.00.0 ‐‐‐3.03.03.0

303003030030300 Lewiston IDLewiston IDLewiston IDLewiston ID 36.136.136.1 0.00.00.0 ‐‐‐7.27.27.2

303403034030340 Lewiston MELewiston MELewiston MELewiston ME 18.918.918.9 ‐‐‐2.02.02.0 6.06.06.0

304603046030460 Lexington KYLexington KYLexington KYLexington KY 51.651.651.6 1.01.01.0 ‐‐‐2.52.52.5

306203062030620 Lima OHLima OHLima OHLima OH 46.846.846.8 ‐‐‐1.01.01.0 ‐‐‐4.24.24.2

307003070030700 Lincoln NELincoln NELincoln NELincoln NE 25.425.425.4 ‐‐‐1.01.01.0 ‐‐‐4.84.84.8

307803078030780 Little Rock ARLittle Rock ARLittle Rock ARLittle Rock AR 16.916.916.9 0.00.00.0 ‐‐‐4.24.24.2

308603086030860 Logan UTLogan UTLogan UTLogan UT 46.546.546.5 0.00.00.0 ‐‐‐4.24.24.2

309803098030980 Longview TXLongview TXLongview TXLongview TX 37.337.337.3 0.00.00.0 ‐‐‐8.18.18.1

310203102031020 Longview WALongview WALongview WALongview WA 44.244.244.2 ‐‐‐2.02.02.0 ‐‐‐4.04.04.0

310843108431084 Los Angeles CA [Metropolitan Division]Los Angeles CA [Metropolitan Division]Los Angeles CA [Metropolitan Division]Los Angeles CA [Metropolitan Division] 31.031.031.0 ‐‐‐1.01.01.0 ‐‐‐9.79.79.7

311403114031140 Louisville KYLouisville KYLouisville KYLouisville KY 62.862.862.8 0.00.00.0 ‐‐‐5.15.15.1

311803118031180 Lubbock TXLubbock TXLubbock TXLubbock TX 23.823.823.8 0.00.00.0 ‐‐‐6.06.06.0

313403134031340 Lynchburg VALynchburg VALynchburg VALynchburg VA 62.862.862.8 1.01.01.0 ‐‐‐3.03.03.0

314203142031420 Macon GAMacon GAMacon GAMacon GA 73.373.373.3 ‐‐‐1.01.01.0 ‐‐‐2.82.82.8

314603146031460 Madera CAMadera CAMadera CAMadera CA 95.595.595.5 ‐‐‐1.01.01.0 ‐‐‐6.66.66.6

315403154031540 Madison WIMadison WIMadison WIMadison WI 56.556.556.5 0.00.00.0 ‐‐‐6.36.36.3

317003170031700 Manchester NHManchester NHManchester NHManchester NH 59.659.659.6 ‐‐‐1.01.01.0 ‐‐‐5.75.75.7

317403174031740 Manhattan KSManhattan KSManhattan KSManhattan KS 22.722.722.7 ‐‐‐2.02.02.0 ‐‐‐3.93.93.9

318603186031860 Mankato MNMankato MNMankato MNMankato MN 26.426.426.4 0.00.00.0 ‐‐‐5.55.55.5

319003190031900 Mansfield OHMansfield OHMansfield OHMansfield OH 75.575.575.5 ‐‐‐2.02.02.0 0.80.80.8

325803258032580 McAllen TXMcAllen TXMcAllen TXMcAllen TX 3.63.63.6 ‐‐‐1.01.01.0 ‐‐‐4.04.04.0

327803278032780 Medford ORMedford ORMedford ORMedford OR 74.974.974.9 ‐‐‐1.01.01.0 ‐‐‐7.17.17.1

328203282032820 Memphis TNMemphis TNMemphis TNMemphis TN 9.59.59.5 ‐‐‐2.02.02.0 ‐‐‐5.45.45.4

329003290032900 Merced CAMerced CAMerced CAMerced CA 37.537.537.5 ‐‐‐2.02.02.0 ‐‐‐7.97.97.9

331243312433124 Miami FL [Metropolitan Division]Miami FL [Metropolitan Division]Miami FL [Metropolitan Division]Miami FL [Metropolitan Division] 77.677.677.6 0.00.00.0 ‐‐‐10.010.010.0

331403314033140 Michigan City INMichigan City INMichigan City INMichigan City IN 47.347.347.3 ‐‐‐1.01.01.0 ‐‐‐4.84.84.8

332603326033260 Midland TXMidland TXMidland TXMidland TX 11.111.111.1 0.00.00.0 ‐‐‐4.94.94.9

333403334033340 Milwaukee WIMilwaukee WIMilwaukee WIMilwaukee WI 42.142.142.1 0.00.00.0 ‐‐‐7.57.57.5

334603346033460 Minneapolis MNMinneapolis MNMinneapolis MNMinneapolis MN 41.841.841.8 ‐‐‐1.01.01.0 ‐‐‐8.28.28.2

335403354033540 Missoula MTMissoula MTMissoula MTMissoula MT 60.560.560.5 1.01.01.0 ‐‐‐5.75.75.7

336603366033660 Mobile ALMobile ALMobile ALMobile AL 77.277.277.2 ‐‐‐2.02.02.0 0.70.70.7

337003370033700 Modesto CAModesto CAModesto CAModesto CA 60.860.860.8 ‐‐‐1.01.01.0 ‐‐‐8.08.08.0

337403374033740 Monroe LAMonroe LAMonroe LAMonroe LA 24.524.524.5 0.00.00.0 ‐‐‐5.55.55.5

337803378033780 Monroe MIMonroe MIMonroe MIMonroe MI 71.171.171.1 ‐‐‐2.02.02.0 ‐‐‐5.05.05.0

338603386033860 Montgomery ALMontgomery ALMontgomery ALMontgomery AL 49.449.449.4 ‐‐‐1.01.01.0 ‐‐‐5.65.65.6

340603406034060 Morgantown WVMorgantown WVMorgantown WVMorgantown WV 18.818.818.8 0.00.00.0 ‐‐‐10.510.510.5

341003410034100 Morristown TNMorristown TNMorristown TNMorristown TN 71.371.371.3 0.00.00.0 ‐‐‐3.53.53.5

345803458034580 Mount Vernon WAMount Vernon WAMount Vernon WAMount Vernon WA 59.959.959.9 ‐‐‐2.02.02.0 ‐‐‐4.04.04.0



346203462034620 Muncie INMuncie INMuncie INMuncie IN 15.015.015.0 ‐‐‐2.02.02.0 ‐‐‐9.39.39.3

347403474034740 Muskegon MIMuskegon MIMuskegon MIMuskegon MI 91.791.791.7 ‐‐‐2.02.02.0 3.43.43.4

348203482034820 Myrtle Beach SCMyrtle Beach SCMyrtle Beach SCMyrtle Beach SC 52.252.252.2 ‐‐‐1.01.01.0 ‐‐‐1.21.21.2

349003490034900 Napa CANapa CANapa CANapa CA 20.420.420.4 ‐‐‐2.02.02.0 ‐‐‐7.77.77.7

349403494034940 Naples FLNaples FLNaples FLNaples FL 54.854.854.8 0.00.00.0 ‐‐‐4.54.54.5

349803498034980 Nashville TNNashville TNNashville TNNashville TN 62.562.562.5 0.00.00.0 ‐‐‐3.53.53.5

350043500435004 Nassau NY [Metropolitan Division]Nassau NY [Metropolitan Division]Nassau NY [Metropolitan Division]Nassau NY [Metropolitan Division] 37.537.537.5 0.00.00.0 ‐‐‐7.77.77.7

353003530035300 New Haven CTNew Haven CTNew Haven CTNew Haven CT 41.141.141.1 ‐‐‐2.02.02.0 ‐‐‐7.17.17.1

353803538035380 New Orleans LANew Orleans LANew Orleans LANew Orleans LA 61.261.261.2 ‐‐‐2.02.02.0 ‐‐‐6.26.26.2

356443564435644 New York NY [Metropolitan Division]New York NY [Metropolitan Division]New York NY [Metropolitan Division]New York NY [Metropolitan Division] 12.612.612.6 0.00.00.0 ‐‐‐7.97.97.9

350843508435084 Newark NJ [Metropolitan Division]Newark NJ [Metropolitan Division]Newark NJ [Metropolitan Division]Newark NJ [Metropolitan Division] 19.119.119.1 ‐‐‐1.01.01.0 ‐‐‐6.46.46.4

356603566035660 Niles MINiles MINiles MINiles MI 69.569.569.5 ‐‐‐2.02.02.0 ‐‐‐2.52.52.5

358403584035840 North Port FLNorth Port FLNorth Port FLNorth Port FL 59.159.159.1 ‐‐‐2.02.02.0 ‐‐‐4.54.54.5

359803598035980 Norwich CTNorwich CTNorwich CTNorwich CT 14.014.014.0 ‐‐‐2.02.02.0 ‐‐‐5.15.15.1

360843608436084 Oakland CA [Metropolitan Division]Oakland CA [Metropolitan Division]Oakland CA [Metropolitan Division]Oakland CA [Metropolitan Division] 25.425.425.4 ‐‐‐2.02.02.0 ‐‐‐9.09.09.0

361003610036100 Ocala FLOcala FLOcala FLOcala FL 51.551.551.5 ‐‐‐2.02.02.0 ‐‐‐1.81.81.8

361403614036140 Ocean City NJOcean City NJOcean City NJOcean City NJ 24.524.524.5 ‐‐‐2.02.02.0 ‐‐‐3.73.73.7

362203622036220 Odessa TXOdessa TXOdessa TXOdessa TX 47.947.947.9 0.00.00.0 ‐‐‐6.06.06.0

362603626036260 Ogden UTOgden UTOgden UTOgden UT 58.158.158.1 ‐‐‐1.01.01.0 ‐‐‐5.25.25.2

364203642036420 Oklahoma City OKOklahoma City OKOklahoma City OKOklahoma City OK 45.045.045.0 0.00.00.0 ‐‐‐5.65.65.6

365003650036500 Olympia WAOlympia WAOlympia WAOlympia WA 44.544.544.5 ‐‐‐2.02.02.0 ‐‐‐2.82.82.8

365403654036540 Omaha NEOmaha NEOmaha NEOmaha NE 21.421.421.4 ‐‐‐2.02.02.0 ‐‐‐3.53.53.5

367403674036740 Orlando FLOrlando FLOrlando FLOrlando FL 51.551.551.5 ‐‐‐1.01.01.0 ‐‐‐5.15.15.1

367803678036780 Oshkosh WIOshkosh WIOshkosh WIOshkosh WI 22.522.522.5 ‐‐‐2.02.02.0 ‐‐‐4.94.94.9

369803698036980 Owensboro KYOwensboro KYOwensboro KYOwensboro KY 13.713.713.7 ‐‐‐1.01.01.0 ‐‐‐2.52.52.5

371003710037100 Oxnard CAOxnard CAOxnard CAOxnard CA 38.938.938.9 ‐‐‐1.01.01.0 ‐‐‐10.510.510.5

373403734037340 Palm Bay FLPalm Bay FLPalm Bay FLPalm Bay FL 39.039.039.0 ‐‐‐1.01.01.0 ‐‐‐3.93.93.9

373803738037380 Palm Coast FLPalm Coast FLPalm Coast FLPalm Coast FL 38.838.838.8 ‐‐‐1.01.01.0 ‐‐‐5.85.85.8

374603746037460 Panama City FLPanama City FLPanama City FLPanama City FL 12.712.712.7 ‐‐‐2.02.02.0 ‐‐‐8.08.08.0

376203762037620 Parkersburg WVParkersburg WVParkersburg WVParkersburg WV 38.038.038.0 ‐‐‐1.01.01.0 ‐‐‐7.67.67.6

377003770037700 Pascagoula MSPascagoula MSPascagoula MSPascagoula MS 35.235.235.2 ‐‐‐1.01.01.0 ‐‐‐2.02.02.0

377643776437764 Peabody MAPeabody MAPeabody MAPeabody MA 14.114.114.1 ‐‐‐2.02.02.0 ‐‐‐9.19.19.1

378603786037860 Pensacola FLPensacola FLPensacola FLPensacola FL 40.240.240.2 ‐‐‐1.01.01.0 ‐‐‐5.15.15.1

379003790037900 Peoria ILPeoria ILPeoria ILPeoria IL 8.88.88.8 ‐‐‐1.01.01.0 ‐‐‐5.05.05.0

379643796437964 Philadelphia PA [Metropolitan Division]Philadelphia PA [Metropolitan Division]Philadelphia PA [Metropolitan Division]Philadelphia PA [Metropolitan Division] 50.550.550.5 ‐‐‐1.01.01.0 ‐‐‐7.37.37.3

380603806038060 Phoenix AZPhoenix AZPhoenix AZPhoenix AZ 52.052.052.0 ‐‐‐2.02.02.0 ‐‐‐5.85.85.8

382203822038220 Pine Bluff ARPine Bluff ARPine Bluff ARPine Bluff AR 34.734.734.7 ‐‐‐1.01.01.0 0.40.40.4

383003830038300 Pittsburgh PAPittsburgh PAPittsburgh PAPittsburgh PA 14.214.214.2 ‐‐‐2.02.02.0 ‐‐‐5.65.65.6

383403834038340 Pittsfield MAPittsfield MAPittsfield MAPittsfield MA 11.611.611.6 ‐‐‐2.02.02.0 ‐‐‐6.26.26.2

385403854038540 Pocatello IDPocatello IDPocatello IDPocatello ID 50.450.450.4 0.00.00.0 ‐‐‐6.26.26.2

389403894038940 Port St. Lucie FLPort St. Lucie FLPort St. Lucie FLPort St. Lucie FL 30.930.930.9 ‐‐‐2.02.02.0 ‐‐‐6.06.06.0

388603886038860 Portland MEPortland MEPortland MEPortland ME 41.841.841.8 ‐‐‐1.01.01.0 ‐‐‐0.60.60.6

389003890038900 Portland ORPortland ORPortland ORPortland OR 21.121.121.1 ‐‐‐1.01.01.0 ‐‐‐7.27.27.2

391003910039100 Poughkeepsie NYPoughkeepsie NYPoughkeepsie NYPoughkeepsie NY 21.821.821.8 ‐‐‐1.01.01.0 ‐‐‐3.13.13.1

391403914039140 Prescott AZPrescott AZPrescott AZPrescott AZ 88.588.588.5 ‐‐‐1.01.01.0 ‐‐‐6.36.36.3

393003930039300 Providence RIProvidence RIProvidence RIProvidence RI 41.441.441.4 ‐‐‐2.02.02.0 ‐‐‐6.36.36.3

393403934039340 Provo UTProvo UTProvo UTProvo UT 80.280.280.2 0.00.00.0 ‐‐‐3.93.93.9

393803938039380 Pueblo COPueblo COPueblo COPueblo CO 48.448.448.4 ‐‐‐2.02.02.0 ‐‐‐7.17.17.1

394603946039460 Punta Gorda FLPunta Gorda FLPunta Gorda FLPunta Gorda FL 24.124.124.1 ‐‐‐2.02.02.0 ‐‐‐6.36.36.3

395403954039540 Racine WIRacine WIRacine WIRacine WI 63.963.963.9 ‐‐‐1.01.01.0 ‐‐‐3.13.13.1

395803958039580 Raleigh NCRaleigh NCRaleigh NCRaleigh NC 71.471.471.4 1.01.01.0 ‐‐‐2.72.72.7

396603966039660 Rapid City SDRapid City SDRapid City SDRapid City SD 30.030.030.0 0.00.00.0 ‐‐‐5.25.25.2

397403974039740 Reading PAReading PAReading PAReading PA 36.236.236.2 0.00.00.0 ‐‐‐4.94.94.9

398203982039820 Redding CARedding CARedding CARedding CA 28.728.728.7 ‐‐‐2.02.02.0 ‐‐‐4.84.84.8

399003990039900 Reno NVReno NVReno NVReno NV 81.581.581.5 ‐‐‐1.01.01.0 ‐‐‐4.74.74.7

400604006040060 Richmond VARichmond VARichmond VARichmond VA 76.176.176.1 0.00.00.0 ‐‐‐4.54.54.5

401404014040140 Riverside CARiverside CARiverside CARiverside CA 45.245.245.2 ‐‐‐1.01.01.0 ‐‐‐6.26.26.2

402204022040220 Roanoke VARoanoke VARoanoke VARoanoke VA 62.862.862.8 1.01.01.0 ‐‐‐5.45.45.4

403404034040340 Rochester MNRochester MNRochester MNRochester MN 28.228.228.2 ‐‐‐2.02.02.0 ‐‐‐6.06.06.0

403804038040380 Rochester NYRochester NYRochester NYRochester NY 3.83.83.8 ‐‐‐1.01.01.0 ‐‐‐5.55.55.5

404204042040420 Rockford ILRockford ILRockford ILRockford IL 68.168.168.1 ‐‐‐1.01.01.0 ‐‐‐1.31.31.3



404844048440484 Rockingham County NH [Metropolitan Division]Rockingham County NH [Metropolitan Division]Rockingham County NH [Metropolitan Division]Rockingham County NH [Metropolitan Division] 47.047.047.0 ‐‐‐2.02.02.0 ‐‐‐3.73.73.7

405804058040580 Rocky Mount NCRocky Mount NCRocky Mount NCRocky Mount NC 38.538.538.5 ‐‐‐2.02.02.0 ‐‐‐5.65.65.6

406604066040660 Rome GARome GARome GARome GA 66.066.066.0 0.00.00.0 ‐‐‐6.16.16.1

409004090040900 Sacramento CASacramento CASacramento CASacramento CA 22.322.322.3 ‐‐‐2.02.02.0 ‐‐‐6.86.86.8

409804098040980 Saginaw MISaginaw MISaginaw MISaginaw MI 37.937.937.9 ‐‐‐2.02.02.0 ‐‐‐0.80.80.8

414204142041420 Salem ORSalem ORSalem ORSalem OR 62.362.362.3 ‐‐‐2.02.02.0 ‐‐‐7.17.17.1

415004150041500 Salinas CASalinas CASalinas CASalinas CA 6.06.06.0 ‐‐‐2.02.02.0 ‐‐‐9.79.79.7

415404154041540 Salisbury MDSalisbury MDSalisbury MDSalisbury MD 28.828.828.8 ‐‐‐2.02.02.0 ‐‐‐4.94.94.9

416204162041620 Salt Lake City UTSalt Lake City UTSalt Lake City UTSalt Lake City UT 76.776.776.7 0.00.00.0 ‐‐‐6.66.66.6

416604166041660 San Angelo TXSan Angelo TXSan Angelo TXSan Angelo TX 41.141.141.1 0.00.00.0 ‐‐‐6.76.76.7

417004170041700 San Antonio TXSan Antonio TXSan Antonio TXSan Antonio TX 58.158.158.1 0.00.00.0 ‐‐‐6.66.66.6

417404174041740 San Diego CASan Diego CASan Diego CASan Diego CA 15.415.415.4 ‐‐‐2.02.02.0 ‐‐‐9.09.09.0

418844188441884 San Francisco CA [Metropolitan Division]San Francisco CA [Metropolitan Division]San Francisco CA [Metropolitan Division]San Francisco CA [Metropolitan Division] 10.710.710.7 ‐‐‐2.02.02.0 ‐‐‐10.410.410.4

419404194041940 San Jose CASan Jose CASan Jose CASan Jose CA 13.013.013.0 ‐‐‐2.02.02.0 ‐‐‐10.010.010.0

420204202042020 San Luis Obispo CASan Luis Obispo CASan Luis Obispo CASan Luis Obispo CA 48.648.648.6 ‐‐‐2.02.02.0 ‐‐‐6.06.06.0

417804178041780 Sandusky OHSandusky OHSandusky OHSandusky OH 43.843.843.8 ‐‐‐2.02.02.0 ‐‐‐7.57.57.5

420444204442044 Santa Ana CA [Metropolitan Division]Santa Ana CA [Metropolitan Division]Santa Ana CA [Metropolitan Division]Santa Ana CA [Metropolitan Division] 21.921.921.9 ‐‐‐1.01.01.0 ‐‐‐9.69.69.6

420604206042060 Santa Barbara CASanta Barbara CASanta Barbara CASanta Barbara CA 23.323.323.3 ‐‐‐1.01.01.0 ‐‐‐9.39.39.3

421004210042100 Santa Cruz CASanta Cruz CASanta Cruz CASanta Cruz CA 19.719.719.7 ‐‐‐2.02.02.0 ‐‐‐9.79.79.7

421404214042140 Santa Fe NMSanta Fe NMSanta Fe NMSanta Fe NM 55.755.755.7 ‐‐‐1.01.01.0 ‐‐‐9.99.99.9

422204222042220 Santa Rosa CASanta Rosa CASanta Rosa CASanta Rosa CA 11.011.011.0 ‐‐‐2.02.02.0 ‐‐‐9.69.69.6

423404234042340 Savannah GASavannah GASavannah GASavannah GA 70.770.770.7 0.00.00.0 ‐‐‐4.14.14.1

425404254042540 Scranton PAScranton PAScranton PAScranton PA 55.055.055.0 0.00.00.0 ‐‐‐4.34.34.3

426444264442644 Seattle WA [Metropolitan Division]Seattle WA [Metropolitan Division]Seattle WA [Metropolitan Division]Seattle WA [Metropolitan Division] 61.161.161.1 ‐‐‐2.02.02.0 ‐‐‐6.46.46.4

426804268042680 Sebastian FLSebastian FLSebastian FLSebastian FL 37.937.937.9 ‐‐‐2.02.02.0 ‐‐‐2.82.82.8

431004310043100 Sheboygan WISheboygan WISheboygan WISheboygan WI 46.546.546.5 ‐‐‐1.01.01.0 ‐‐‐5.65.65.6

433004330043300 Sherman TXSherman TXSherman TXSherman TX 30.930.930.9 ‐‐‐1.01.01.0 ‐‐‐8.48.48.4

433404334043340 Shreveport LAShreveport LAShreveport LAShreveport LA 10.410.410.4 0.00.00.0 ‐‐‐4.44.44.4

435804358043580 Sioux City IASioux City IASioux City IASioux City IA 18.118.118.1 ‐‐‐1.01.01.0 ‐‐‐7.27.27.2

436204362043620 Sioux Falls SDSioux Falls SDSioux Falls SDSioux Falls SD 44.744.744.7 0.00.00.0 ‐‐‐2.12.12.1

437804378043780 South Bend INSouth Bend INSouth Bend INSouth Bend IN 40.240.240.2 ‐‐‐2.02.02.0 ‐‐‐4.64.64.6

439004390043900 Spartanburg SCSpartanburg SCSpartanburg SCSpartanburg SC 24.624.624.6 0.00.00.0 ‐‐‐2.92.92.9

440604406044060 Spokane WASpokane WASpokane WASpokane WA 39.439.439.4 ‐‐‐2.02.02.0 ‐‐‐5.25.25.2

441004410044100 Springfield ILSpringfield ILSpringfield ILSpringfield IL 4.44.44.4 ‐‐‐1.01.01.0 ‐‐‐5.95.95.9

441404414044140 Springfield MASpringfield MASpringfield MASpringfield MA 7.77.77.7 ‐‐‐1.01.01.0 ‐‐‐5.85.85.8

441804418044180 Springfield MOSpringfield MOSpringfield MOSpringfield MO 51.051.051.0 ‐‐‐1.01.01.0 ‐‐‐5.15.15.1

442204422044220 Springfield OHSpringfield OHSpringfield OHSpringfield OH 21.121.121.1 ‐‐‐2.02.02.0 ‐‐‐3.43.43.4

410604106041060 St. Cloud MNSt. Cloud MNSt. Cloud MNSt. Cloud MN 26.226.226.2 ‐‐‐1.01.01.0 ‐‐‐5.85.85.8

411004110041100 St. George UTSt. George UTSt. George UTSt. George UT 95.895.895.8 ‐‐‐1.01.01.0 ‐‐‐1.11.11.1

411404114041140 St. Joseph MOSt. Joseph MOSt. Joseph MOSt. Joseph MO 47.447.447.4 0.00.00.0 ‐‐‐7.47.47.4

411804118041180 St. Louis MOSt. Louis MOSt. Louis MOSt. Louis MO 41.541.541.5 0.00.00.0 ‐‐‐4.94.94.9

443004430044300 State College PAState College PAState College PAState College PA 12.012.012.0 1.01.01.0 ‐‐‐4.34.34.3

446004460044600 Steubenville OHSteubenville OHSteubenville OHSteubenville OH 43.243.243.2 ‐‐‐1.01.01.0 ‐‐‐9.39.39.3

447004470044700 Stockton CAStockton CAStockton CAStockton CA 32.132.132.1 ‐‐‐2.02.02.0 ‐‐‐6.46.46.4

449404494044940 Sumter SCSumter SCSumter SCSumter SC 64.164.164.1 1.01.01.0 ‐‐‐3.33.33.3

450604506045060 Syracuse NYSyracuse NYSyracuse NYSyracuse NY 7.87.87.8 ‐‐‐2.02.02.0 ‐‐‐3.13.13.1

451044510445104 Tacoma WA [Metropolitan Division]Tacoma WA [Metropolitan Division]Tacoma WA [Metropolitan Division]Tacoma WA [Metropolitan Division] 57.757.757.7 ‐‐‐2.02.02.0 ‐‐‐3.33.33.3

452204522045220 Tallahassee FLTallahassee FLTallahassee FLTallahassee FL 31.631.631.6 ‐‐‐1.01.01.0 ‐‐‐5.35.35.3

453004530045300 Tampa FLTampa FLTampa FLTampa FL 40.940.940.9 ‐‐‐2.02.02.0 ‐‐‐5.65.65.6

454604546045460 Terre Haute INTerre Haute INTerre Haute INTerre Haute IN 6.76.76.7 ‐‐‐2.02.02.0 ‐‐‐6.36.36.3

455004550045500 Texarkana TXTexarkana TXTexarkana TXTexarkana TX 22.522.522.5 0.00.00.0 ‐‐‐7.27.27.2

457804578045780 Toledo OHToledo OHToledo OHToledo OH 46.546.546.5 ‐‐‐2.02.02.0 ‐‐‐1.21.21.2

458204582045820 Topeka KSTopeka KSTopeka KSTopeka KS 50.650.650.6 ‐‐‐2.02.02.0 ‐‐‐6.46.46.4

459404594045940 Trenton NJTrenton NJTrenton NJTrenton NJ 8.88.88.8 ‐‐‐1.01.01.0 ‐‐‐7.07.07.0

460604606046060 Tucson AZTucson AZTucson AZTucson AZ 64.964.964.9 ‐‐‐2.02.02.0 ‐‐‐5.75.75.7

461404614046140 Tulsa OKTulsa OKTulsa OKTulsa OK 20.120.120.1 0.00.00.0 ‐‐‐4.14.14.1

462204622046220 Tuscaloosa ALTuscaloosa ALTuscaloosa ALTuscaloosa AL 41.041.041.0 0.00.00.0 ‐‐‐3.43.43.4

463404634046340 Tyler TXTyler TXTyler TXTyler TX 31.831.831.8 0.00.00.0 ‐‐‐9.19.19.1

465404654046540 Utica NYUtica NYUtica NYUtica NY 6.56.56.5 0.00.00.0 ‐‐‐2.92.92.9

466604666046660 Valdosta GAValdosta GAValdosta GAValdosta GA 61.661.661.6 0.00.00.0 ‐‐‐3.33.33.3

467004670046700 Vallejo CAVallejo CAVallejo CAVallejo CA 27.127.127.1 ‐‐‐2.02.02.0 ‐‐‐8.18.18.1



470204702047020 Victoria TXVictoria TXVictoria TXVictoria TX 4.24.24.2 ‐‐‐1.01.01.0 ‐‐‐8.48.48.4

472204722047220 Vineland NJVineland NJVineland NJVineland NJ 49.849.849.8 0.00.00.0 2.12.12.1

472604726047260 Virginia Beach VAVirginia Beach VAVirginia Beach VAVirginia Beach VA 76.476.476.4 0.00.00.0 ‐‐‐4.94.94.9

473004730047300 Visalia CAVisalia CAVisalia CAVisalia CA 8.78.78.7 ‐‐‐2.02.02.0 ‐‐‐4.14.14.1

473804738047380 Waco TXWaco TXWaco TXWaco TX 33.233.233.2 0.00.00.0 ‐‐‐6.66.66.6

475804758047580 Warner Robins GAWarner Robins GAWarner Robins GAWarner Robins GA 27.827.827.8 ‐‐‐1.01.01.0 ‐‐‐3.63.63.6

476444764447644 Warren MI [Metropolitan Division]Warren MI [Metropolitan Division]Warren MI [Metropolitan Division]Warren MI [Metropolitan Division] 62.962.962.9 ‐‐‐2.02.02.0 ‐‐‐6.76.76.7

478944789447894 Washington DC [Metropolitan Division]Washington DC [Metropolitan Division]Washington DC [Metropolitan Division]Washington DC [Metropolitan Division] 16.716.716.7 0.00.00.0 ‐‐‐7.47.47.4

479404794047940 Waterloo IAWaterloo IAWaterloo IAWaterloo IA 29.529.529.5 0.00.00.0 ‐‐‐5.15.15.1

481404814048140 Wausau WIWausau WIWausau WIWausau WI 31.631.631.6 ‐‐‐1.01.01.0 ‐‐‐3.83.83.8

483004830048300 Wenatchee WAWenatchee WAWenatchee WAWenatchee WA 46.746.746.7 ‐‐‐2.02.02.0 ‐‐‐4.24.24.2

484244842448424 West Palm Beach FL [Metropolitan Division]West Palm Beach FL [Metropolitan Division]West Palm Beach FL [Metropolitan Division]West Palm Beach FL [Metropolitan Division] 21.721.721.7 ‐‐‐1.01.01.0 ‐‐‐8.18.18.1

485404854048540 Wheeling WVWheeling WVWheeling WVWheeling WV 20.820.820.8 0.00.00.0 ‐‐‐10.110.110.1

486604866048660 Wichita Falls TXWichita Falls TXWichita Falls TXWichita Falls TX 10.410.410.4 0.00.00.0 ‐‐‐7.97.97.9

486204862048620 Wichita KSWichita KSWichita KSWichita KS 54.854.854.8 ‐‐‐1.01.01.0 ‐‐‐5.25.25.2

487004870048700 Williamsport PAWilliamsport PAWilliamsport PAWilliamsport PA 20.120.120.1 ‐‐‐1.01.01.0 ‐‐‐5.05.05.0

488644886448864 Wilmington DE [Metropolitan Division]Wilmington DE [Metropolitan Division]Wilmington DE [Metropolitan Division]Wilmington DE [Metropolitan Division] 50.750.750.7 ‐‐‐2.02.02.0 ‐‐‐5.25.25.2

489004890048900 Wilmington NCWilmington NCWilmington NCWilmington NC 70.070.070.0 0.00.00.0 ‐‐‐1.01.01.0

490204902049020 Winchester VAWinchester VAWinchester VAWinchester VA 55.055.055.0 ‐‐‐2.02.02.0 ‐‐‐4.14.14.1

491804918049180 Winston NCWinston NCWinston NCWinston NC 59.859.859.8 0.00.00.0 ‐‐‐2.92.92.9

493404934049340 Worcester MAWorcester MAWorcester MAWorcester MA 7.17.17.1 ‐‐‐2.02.02.0 ‐‐‐5.05.05.0

494204942049420 Yakima WAYakima WAYakima WAYakima WA 48.548.548.5 ‐‐‐2.02.02.0 ‐‐‐6.36.36.3

496204962049620 York PAYork PAYork PAYork PA 55.255.255.2 0.00.00.0 ‐‐‐1.91.91.9

496604966049660 Youngstown OHYoungstown OHYoungstown OHYoungstown OH 10.110.110.1 ‐‐‐2.02.02.0 ‐‐‐5.75.75.7

497004970049700 Yuba City CAYuba City CAYuba City CAYuba City CA 72.272.272.2 ‐‐‐2.02.02.0 ‐‐‐1.71.71.7

497404974049740 Yuma AZYuma AZYuma AZYuma AZ 54.954.954.9 ‐‐‐1.01.01.0 ‐‐‐4.34.34.3



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