metro unemployment and the financial markets

U.S. Financial Markets and the Metropolitan Unemployment Rate

David Kim

April 19, 2015

Introduction

The natural rate of unemployment in the United States has always been around

5-6%. During times of recessions and depressions the same unemployment rate will

increase to highs of 15%. Similar to the unemployment rate, during recessions the

financial markets will often fall by 15% and historically will increase at about 8-

10%. If the Federal Reserve Bank and Congress could see a clear relationship

between unemployment rates and the financial markets, then they could effectively

allocate resources to areas with the highest sensitivity measured in this paper

through the variable beta (β).

Literature Review

In a recent paper at the St. Louis Federal Reserve Bank titled Metro Business Cycles,

economists Maria A. Arias, Charles S. Gascon, and David E. Rapah constructed an index

for 51 metropolitan areas to measure their business cycles relative to the aggregate

United States economy. More specifically, the economist chose to measure the effect of

two past recessions on the housing market. Rather than construct an index for the 50

states the economist felt that the metropolitan indices would “provide a rich source of

variation in economic activity that can be exploited to analyze important economic

relationships with greater precision.” Arias et al. (2015). The metropolitan indices

provided a richer comparison in terms of business cycles than state data as economists

could see greater variation relative to the state business cycles as well as the entire United

States. These business cycles can range from a variety of labor-market variables such as,

“payroll employment, the unemployment rate, average hours worked in manufacturing,

and real wage and salary disbursements” Arias et al. (2015). Similar to the model

constructed in working paper Metro Business Cycles this paper will seek to understand

the effect of the financial markets on both the metropolitan unemployment and state

unemployment rate during times of financial crises.

Economic Model

The economic model used in this paper is based off of these assumptions:

GDP is measured by Y=C(Y(-Unemployment)-T)+I+NE+G with:o Y=GDP(output)o C(Y(Unemployment)-T)=Consumption as a function of income minus

taxes o I=Investments held constanto NE=Net exports held constanto G=Government spendingo Y(income) is a function of unemployment; as unemployment decreases

the Aggregate income will rise. MV=PY Short-Run

o M=Money Supplyo V=Velocity of Money held constant o P=Price level held constanto Y=income

Planned Expenditure (PE)=Y, PE=C(Y(-unemployment)-T)+I+NE+Go Hold all other variables constant except for G and PE.

For an increase in G, PE will increase, which will cause a positive shift in the Investment Savings Curve (IS)

The unemployment during the recession is structural unemployment The Government Purchases Multiplier and the Tax Multiplier exists.

This paper will seek to better understand the relationship between the financial markets

represented by the IS curve and the output (Y) holding all other variables except for C

and G constant. Since the only variables affecting output are government spending and

consumption as a function of unemployment; for a positive increase in government

spending or an increase in consumption, the output (Y) should increase. Consumption in

this model is a function of income minus taxes; the aggregate income in the consumption

function is also a function of –unemployment. This is built off of the assumption that if as

a whole, individuals were working then the aggregate income will increase causing an

increase in the overall disposable income, which will then increase consumption, then

finally output (Y). Since investments is represented through the IS curve a negative shift

in the IS curve will cause a decrease in output (Y). Therefore, if the IS curve shifts

negatively, this will cause a decrease in PE and in turn output (Y). Because output

decreased, the unemployment should increase, which will cause consumption to fall;

balancing the equation: Y=C(Y(-Unemployment) -T)+I(R)(constant)+NE(constant)+G.

The assumption is that if the financial markets decreased, which caused a decrease in the

output (Y), then Congress can offset the low output by increasing government spending

(G) or the Federal Reserve can increase the money supply which will increase output (Y)

in turn decreasing unemployment.

The variables that will measure unemployment are the unemployment rates for all 50

states as well as the 51 metropolitan areas. The financial markets will be represented by

United States 30 Year Treasury rates and the -S&P 500 index. The beta will measure the

sensitivity of the dependent variable; unemployment, to the independent variables; the 30

Year Treasury rates and the -S&P 500 index. The economic model will seek to see the

relationship between the dependent and independent variables four months prior to times

of recessions, during the recession, and four month after the recession. The four months

prior to the recession will give a clear indicator of how quickly metropolitan areas and

states fell into the recession. The four months before will also provide some insight into

how sensitive the State’s and Metropolitan area’s unemployment rates are to the financial

markets. The model will measure how the unemployment rate changed during the

recession. Finally, by measuring four months after a recession the model will provide

understanding of how well the area recovered as well as how quickly the area stabilized.

The model will measure the relationship between the unemployment rate, the 30 Year

Treasury Rate, the S&P 500 index.

Empirical Methodology

This data set is the unemployment rate for the US for both the 2000 and 2007

Recessions. Below is the descriptive statistics for the data:

2000 recession

Descriptive Statistics

N Minimum Maximum Mean Std. Deviation

US civilian unemployment rate 2000 recession

17 3.9 5.7 4.812 .6688

Valid N (listwise) 17

2007 recession



US civilian unemployment 2007 recession

27 4.6 10.0 6.848 1.9618

Valid N (listwise)27

The unemployment rates are measured in a time series monthly. For the Recession of

2000 the monthly data begins on November 2000 and ends on March 2002. For the

Recession of 2007 the data is a time series measured monthly starting from August 2007

to October 2009. The mean of the 2000 Recession is relatively small compared with that

of the 2007 Recession. The standard deviations of both recessions show how much

unemployment fluctuated and is an adequate measure of the strength of the recessions.

The mean unemployment rate for the US in 2000 was actually lower than the natural rate

of unemployment and the standard deviation of the recession seems relatively normal.

Purely based on the descriptive statistics it is safe to say that the 2000 recession had little

to no impact on the entire US. The 2007 Recession however was slightly higher than the

natural rate of unemployment but from the high standard deviation relative to the

unemployment rate it is safe to conclude that is was a period of economic uncertainty.

This data set is the unemployment rate for the 51 US Metropolitan Areas during

the 2000-2001 recession. Below is the descriptive statistics for the data:



Birmingham AL 17 2.4 4.1 3.318 .5028Pheonix AZ 17 2.4 5.5 3.894 1.1116Little Rock AR 17 2.4 4.5 3.635 .6344Los Angeles CA 17 4.6 6.6 5.600 .6991Riverside CA 17 4.0 5.4 4.882 .4202San Diego CA 17 2.3 3.9 3.147 .5014San Francisco CA

17 1.5 5.4 3.659 1.2733

San Jose CA 17 1.3 7.5 4.535 2.2997Sacramento CA 17 3.2 5.2 4.065 .5384Denver CO 17 1.8 6.0 3.494 1.3236Hartford CT 17 1.6 4.2 2.941 .8024Washington DC 17 2.1 3.9 2.912 .6632Jacksonville FL 17 2.9 5.2 3.924 .6713Miami FL 17 4.9 8.1 6.429 1.0079Orlando FL 17 2.3 5.9 3.794 1.2168Tampa FL 17 2.4 4.6 3.447 .6587Atlanta GA 17 2.3 4.7 3.488 .7449

Chicago IL 17 3.9 6.6 5.400 .7391Indianpolis IN 17 1.8 4.6 3.094 .9052Louisville KY 17 2.9 5.4 3.929 .9339Baltimore MD 17 3.7 5.6 4.506 .5618Boston MA 17 1.7 4.3 3.171 .7904Detroit MI 15 2.9 6.1 4.680 .8817Minneapolis MN 17 2.1 4.3 3.212 .6604Kansas City MO 17 2.9 5.0 3.871 .6091St Louis MO 17 3.1 5.3 4.376 .6088Las Vegas NV 17 4.1 6.9 5.265 1.0204Buffalo NY 17 4.8 7.1 5.459 .7349New York NY 17 4.5 7.1 5.647 .8589Charlotte NC 17 3.3 6.5 4.741 .9657Raleigh NC 17 1.6 4.7 3.165 1.0618Columbus OH 17 2.2 4.3 2.953 .6578Cincinnati OH 17 3.0 4.9 3.829 .5903Clevland OH 17 3.7 6.8 4.829 1.0061Oklahoma City OK

17 2.1 4.5 3.400 .7722

Portland OR 17 3.2 8.9 5.729 1.8203Philadelphia PA 17 3.4 5.5 4.406 .5618Pittsburg PA 17 3.8 5.8 4.553 .6681Providence RI 17 3.1 6.0 4.500 .7689Memphis TN 17 3.3 5.6 4.206 .7049Nashville TN 17 2.7 4.2 3.300 .4514Austin TX 17 1.6 5.4 3.735 1.3138Dallas TX 17 2.5 6.8 4.688 1.4348Houston TX 17 3.0 5.3 4.218 .7002San Antonio TX 17 2.7 4.9 3.894 .6666Salt Lake City UT 17 2.6 5.9 4.065 .8725Norfolk VA 17 2.3 4.5 3.253 .7107Richmond VA 17 1.7 4.1 2.994 .8771Seattle WA 17 3.2 7.1 5.000 1.2145Milwaukee WI 17 2.8 6.3 4.535 .9539Valid N (listwise) 15

The unemployment rate for the 51 US Metropolitan Areas is measured as a percentage

and is a time series of monthly data during the 2000-2001 recession starting from

November 2000, which is four month prior to the recession, and ending four months after

the recession on March 2002.

This data set is the unemployment rate for the 51 US Metropolitan Areas during

the 2007-2009 recession. Below is the descriptive statistics for the data:



Birmingham AL 27 2.7 10.2 5.893 2.6460Pheonix AZ 27 2.9 8.7 5.515 2.0407Little Rock AR 27 3.9 6.7 4.974 .8098Los Angeles CA 27 4.8 11.9 8.019 2.6498Riverside CA 27 6.0 14.6 9.833 3.1660San Diego CA 27 4.8 10.6 7.196 2.1622San Francisco CA 27 4.6 10.7 7.067 2.3483San Jose CA 27 4.9 12.1 7.841 2.7984Sacramento CA 27 5.4 12.3 8.426 2.5165Denver CO 27 3.5 8.2 5.822 1.4825Hartford CT 27 4.3 8.4 6.437 1.4017Washington DC 27 3.0 6.2 4.485 1.2712Jacksonville FL 27 3.9 10.7 6.989 2.5311Miami FL 27 4.0 11.0 6.804 2.5481Orlando FL 27 4.0 11.5 7.193 2.8119Tampa FL 27 4.3 11.7 7.637 2.7752Atlanta GA 27 4.0 10.6 7.089 2.3026Chicago IL 27 4.7 10.6 7.348 2.0498Indianpolis IN 27 3.7 8.7 6.037 1.8541Louisville KY 27 4.3 10.3 7.393 2.1814New Orleans LA 27 3.1 7.7 4.974 1.4456Baltimore MD 27 3.5 7.9 5.507 1.6701Boston MA 27 3.5 8.8 5.693 1.7974Detroit MI 27 6.9 17.7 11.044 3.7024Minneapolis MN

27 3.9 8.4 5.981 1.5153

Kansas City MO27 4.6 8.9 6.663 1.5242

St Louis MO 27 5.1 9.9 7.422 1.7241Las Vegas NV 27 5.0 13.9 8.337 3.0565Buffalo NY 27 4.3 9.6 6.741 1.6458New York NY 27 4.3 9.3 6.333 1.8506Charlotte NC 27 4.6 12.4 8.074 2.9843Raleigh NC 27 3.5 9.1 6.056 2.1516Columbus OH 27 4.5 11.5 6.730 1.9245Cincinnati OH 27 4.6 10.3 6.956 1.9914Clevland OH 27 5.4 10.0 7.374 1.3415Oklahoma City OK

27 2.9 6.5 4.607 1.0118

Portland OR 27 4.6 11.8 7.644 2.8593Philadelphia PA 27 3.9 8.9 6.267 1.7563Pittsburg PA 27 3.9 7.9 5.907 1.3981Providence RI 27 4.5 12.7 8.752 2.8372Memphis TN 27 4.6 10.4 7.474 1.8975Nashville TN 27 3.5 9.8 6.478 2.1793Austin TX 27 3.3 7.3 4.974 1.4659Dallas TX 27 3.8 8.3 5.748 1.6106Houston TX 27 3.8 8.5 5.641 1.6312San Antonio TX 27 3.6 7.1 5.159 1.1833Salt Lake City UT

27 2.5 6.3 4.019 1.3112

Norfolk VA 27 3.0 7.1 5.044 1.4508Richmond VA 27 3.0 8.1 5.393 1.8772Seattle WA 27 3.6 9.1 6.033 2.0923Milwaukee WI 27 4.30 9.50 6.4585 1.82950Valid N (listwise)

27

The data set is the unemployment rate for the 51 US Metropolitan Areas during the 2007-

2009 recession starting from August 2007, which is four month prior to the recession, and

ending four months after the recession on October 2009. Similar to the descriptive

statistic of the US unemployment during the 2007 Recession, the standard deviation and

the mean in the descriptive above is higher during the 2007 Recession than the 2000

Recession.

This data set is the S&P 500 index and the 30-Year Treasury rates during both the

2000 and 2007 Recessions. Below is the descriptive statistics for the data:

2000 Recession


N Minimum Maximum MeanStd.

Deviation

S&P 500 17 1040.94 1366.01 1191.0935 91.9985030 year Treasury rates

17 6.62 7.75 7.0412 .25828

Valid N (listwise)

17

2007 RecessionDescriptive Statistics

N Minimum Maximum MeanStd.

Deviation

S&P 500 27 735.09 1549.38 1157.5467 256.0624230 year treasury rates

27 4.81 6.57 5.7330 .58339

Valid N (listwise)

27

The descriptive statistics above is a time series of monthly data taken during both the

2000 and 2007 Recessions. Similar to the US unemployment rate and the 51 metropolitan

area unemployment rate the standard deviation for both the S&P 500 index and the US

30-Year Treasury is larger during the 2007 Recession.

The core regression used in this paper will be:

Unemploymenti =β1+β2*-S&P500+β3*30-Year Treasury Rates+ei

With this regression built off of the previous assumptions, it is expected that for an

increase in the S&P 500 the unemployment will decrease. For a decrease in the 30-Year

Treasury rates the unemployment rate will also decrease. A summarized table is below:

Variable Relationship with unemployment

S&P 500 Index + then -

30-Year Treasury Rates - then -

Results

This is the regression result for the 2000 Recession US unemployment rate as well as five

metropolitan areas; New York City, Los Angeles, San Jose, Austin, and Chicago:

Year: 2000 R^2 Std. ErrorSum of Squares df F sig beta

US unemployment 0.608 0.4477 7.158 16 10.852 0.001negative S&P500 0.68130-Year Treasury Rates

-0.128

New York 0.398 0.7122 11.802 16 4.635 0.029negative S&P500 0.330-Year Treasury Rates 0.973

Los Angles 0.431 0.35 7.82 16 5.311 0.019negative S&P500 0.62330-Year Treasury Rates

-0.156

San Jose 0.681 1.3885 84.619 16 14.945 0negative S&P500 0.83730-Year Treasury

0.016

RatesAustin 0.65 0.831 27.619 16 13 0.001

negative S&P500 0.79230-Year Treasury Rates -0.02

Chicago 0.441 0.5906 5.528 16 5.528 0.017negative S&P500 0.48630-Year Treasury Rates

-0.221

The hypothesis being tested in the 2000 Recession regression is:

H0: The financial markets do affect the unemployment ratesH1: The financial markets do not affect the unemployment rates

Listed below are the F-values for the regression model as well as the F-Critical Value:

Area/Year F F-CritUS 2000 1.356 10.852New York 2000 0.0579 4.635Los Angeles 200 0.66402 5.311San Jose 2000 1.868 14.945Austin 2000 1.625 13Chicago 2000 0.691 5.528

For all six of the areas tested in the regression the F-Value<F-Critical Value. Therefore,

there is enough evidence to support the H0: The financial markets do affect the

unemployment rates.

This is regression result for the 2007 Recession US unemployment rate as well as

five metropolitan areas; New York City, Los Angeles, San Jose, Austin, and Chicago:

Year: 2007 R^2 Std. Error Sum of df F sig beta

SquaresUS unemployment 0.813 0.8838 100.067 26 52.062 0

negative S&P500 0.38130-Year Treasury Rates -0.573

New York 0.771 0.9221 89.04 26 40.359 0negative S&P500 0.31630-Year Treasury Rates -0.61

Los Angles 0.795 1.2488 182.561 26 46.536 0negative S&P500 0.5130-Year Treasury Rates -0.436

San Jose 0.806 1.2835 203.605 26 49.797 0negative S&P500 0.33930-Year Treasury Rates -0.609

Austin 0.77 0.7314 55.872 26 40.225 0negative S&P500 0.42530-Year Treasury Rates -0.506

Chicago 0.762 1.0412 109.247 26 38.384 0negative S&P500 0.38230-Year Treasury Rates -0.543

The hypothesis being tested in the 2007 Recession regression is:

H0: The financial markets do affect the unemployment ratesH1: The financial markets do not affect the unemployment rates

Listed below are the F-values for the regression model as well as the F-Critical Value:

Area/Year F F-Crit

US 2007 4.017 52.062New York 2007 3.114 40.359Los Angles 2007 3.591 46.536San Jose 2007 3.842 49.797Austin 2007 3.104 40.225Chicago 2007 2.962 38.384

For all six of the areas tested in the regression the F-Value<F-Critical Value. Therefore,

there is enough evidence to support the H0: The financial markets do affect the

unemployment rates.

Furthermore, the β in the individual metropolitan areas for both the 2000 and

2007 Recessions are higher showing increased sensitivity for the unemployment rates to

the financial markets. Therefore, theoretically if the Federal Reserve Bank and Congress

wished to stimulate the economy it would be more effective to increase the money supply

or offer tax cuts to individuals in specific metropolitan areas rather than the entire US.

Conclusion

Building off of the assumptions in the introduction of the paper, that regression

results showed that there is a relationship between unemployment and the financial

markets. The regression results also showed increased sensitivity in the individual

metropolitan areas compared to the entire US. Because each metropolitan area’s

beta differs from the beta of the entire US, it would be inefficient to implement

broad monetary and fiscal policies. Rather specific policies aimed at areas with a

higher beta than the national average would be a more efficient use of the United

State’s limited resources.

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