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7

C H A P T E R 2

THE YEAR IN REVIEW ANDTHE YEARS AHEAD

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Figure 2-1Real GDP Growth by Quarter, 2007 2011

2011:Q4

Note: Shaded area represents recession.Source: Bureau of Economic Analysis, National Income and Product Accounts.



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Figure 2-2Real GDP During Recoveries

Source: Bureau of Economic Analysis, National Income and Product Accounts; NationalBureau of Economic Research; CEA calculations.



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South Korea (1997:Q3)

Colombia (1998:Q2)

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Norway (1988:Q1)Japan (1993:Q1)

Philippines (1998:Q1)

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Figure 2-3Real GDP in Recessions Associated with Financial Crises

Percent decline peak-to-trough

Note: Financial crisis dates are from Reinhart and Rogoff (2009). U.S. business cycles are defined by the National Bureau of Economic Research, and the business cycles of other countries refer to the peaks and troughs of real GDP. "Average 14"excludes current U.S. cycle.Source: Reinhart and Rogoff (2009); National Bureau of Economic Research; International Monetary Fund, World EconomicOutlook (2010) and data from authors; Gordon and Krenn (2010); national sources; CEA calculations.

0 10 20

Duration of downturn(quarters)

Percent decline Duration in quarters

0

1

2

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Figure 2-4Unemployment Rate Increases in Recessions

Associated with Financial CrisesPercentage point change from business-cycle peak

Quarters after business-cycle peak

Average 14

United States(2007:Q4-2012:Q1)

Note: "Average 14" shows the average rise in the unemployment rate in each quarter after the business-cycle peaks identified by Reinhartand Rogoff (2009) as being associated with major, systemic financial crises. Financial crises are shown in Figure 2-3. U.S. business-cycle

peaks are defined by the National Bureau of Economic Research, and the business-cycle peaks of other countries refer to the peaks of realGDP. Quarterly unemployment rates for Argentina, Colombia, Indonesia, Malaysia, and Thailand are based on annual data. The 2012:Q1value for the United States is through January 2012.Source: Reinhart and Rogoff (2009); National Bureau of Economic Research; International Monetary Fund, International FinancialStatistics, World Economic Outlook (2010), and data from authors; Moore (1961); national sources; CEA calculations.



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Total-wealth-to-DPIratio (right axis)

Consumption/DPI ratio Years of disposable income

2011:Q4Consumption-to-DPI ratio (left axis)

Figure 2-5Consumption and Wealth Relative to

Disposable Personal Income (DPI), 1952 2011

Source: Bureau of Economic Analysis, National Income and Product Accounts; FederalReserve Board, Z.1; CEA calculations.

Net housingwealth-to-DPI ratio

(right axis)

Stock marketwealth-to-DPI

ratio (right axis)

2011:Q3

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D W - : T D I T S -B E

In 947, services represented less th n 40 percent of U.S. gross

domestic product (GDP). Tod y, service industries ccount for lmost70 percent of tot l U.S. domestic output. For m ny ye rs, however, theme surement of service ctivity l gged the sectors growing import nce.

A fund ment l ch llenge in me suring the v lue of services isthe disp r te r nge of ctivities encomp ssed within the service sector.The Bure u of Economic An lysis (BEA) defines services s productsth t c nnot e stored nd re consumed t the pl ce nd time of theirpurch se. This includes, for inst nce, medic l consult tions, dmissionto movie the ters, Internet su scriptions, h ircuts, nd p rtment rents,

ut lso some less pp rent things such s me ls t rest ur nts, check cle ring y nks, nd the rent l v lue of homeownership. (Althoughthe purch se of newly constructed home is c tegorized under residen-ti l investment, the BEA estim tes the mount homeowners would h veh d to p y to rent simil r houses nd cl ssifies this imputed rent underhousing services.)

A m jor re kthrough in the me surement of service output c mewith the introduction of the North Americ n Industry Cl ssific tion

System (NAICS) eginning in 997 to repl ce the St nd rd Industri lCl ssific tion (SIC) system. Origin lly developed during the 930s ndreflecting the economy of its time, the SIC provided f r more det il forgoods-producing industries such s m nuf cturing nd mining th n forservice-producing industries. The 997 NAICS dded more th n 49new services industries. Just s import nt, process w s put in pl ceto dd new industries to NAICS s they develop. A p r llel effort c r-ried out over the p st dec de, the development of the North Americ nProduct Cl ssific tion System, simil rly will provide consistent sisfor c tegorizing the rich rr y of outputs produced in the growingservice sector.

The qu lity of the source d t on the volume of service tr ns ctionslso h s improved over time. Since the 980s, the BEA h s collected

d t on intern tion l tr de in services. In 004, the Census Bure uintroduced the Qu rterly Services Survey (QSS) to provide more timely d t on domestic consumption of services. The QSS, norm lly pu lished

out months fter the end of e ch qu rter, llows the BEA to incor-

por te ctu l survey d t on m ny services into its qu rterly estim tesof GDP, r ther th n relying on judgment l trends. Furthermore, theCensus Bure u h s exp nded the scope of its nnu l surveys of theservice sector. In f ct, the Services Annu l Survey nd the Qu rterly Services Survey oth now c pture 55 percent of U.S. GDPequ ling the



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cover ge of services in the Economic Census nd m rking su st nti limprovement rel tive to even just few ye rs go.

Me surement of re l ctivity in the service sector requires ppro-pri te price defl tors for service outputs. In 990, the Producer PriceIndex (PPI) covered less th n 5 percent of U.S. service output. Tod y,th nks to concerted effort y the Bure u of L or St tistics, PPI defl -tors re v il le for more th n three-qu rters of domestic lly providedservices. This h s tr nsl ted directly into more ccur te estim tes of re lGDP.

Nevertheless, s the U.S. economy continues to evolve, the work of ccur tely me suring service ctivity grows ccordingly. Despite recent

innov tions in the collection of prim ry source d t , there re still

conceptu l issues pert ining to the ppr is l nd definition of servicesth t rem in unresolved. As n ex mple, improvements in he lth c reh ve contri uted to longer life sp ns nd etter qu lity of life, ut thereis not consensus out how to v lue nd incorpor te these enefitsin n tion l income ccounting fr mework. Simil rly, industries such

s fin nce l rgely produce int ngi le outputs th t re difficult evento identify, much less qu ntify. Furthermore, lthough estim tes of intern tion l tr de in services re now more det iled th n w s the c se

efore the 980s, the st tistics still could nd should e improved. D ton the prices of tr ded services re extremely limited, nd even the mostdis ggreg ted d t collected y the BEA on services extend to only 36c tegories, in contr st to thous nds of c tegories for m nuf cturedgoods. Continued rese rch nd investment in the development of d ton services re needed to ensure timely nd ccur te me surement of the U.S. economy.



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T Y R Y A | 55

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Liquid assets held bynonfinancial corporations

Nonresidential fixedinvestment

Cash flow

Note: Potential GDP is a CBO estimate. Cash flow, from the National Income and Product Accounts,and nonfinancial liquid assets are plotted using three-quarter moving averages.Source: Bureau of Economic Analysis, National Income and Product Accounts; Federal Reserve Board(Flow of Funds L.102); Congressional Budget Office.

Percent of potential GDP

Figure 2-6Business Fixed Investment and Cash Flow, 1990 2011

2011:Q3

2011:Q4



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Investment c n e defined s devoting resources to produce dur le sset th t will yield future flow of services. Until recently,

me sures of investment in the N tion l Income nd Product Accounts(NIPAs) were restricted to investments in physic l c pit l such suildings, m chinery, nd equipment; new residenti l construction; nd

net dditions to inventories. In tod ys knowledge economy, however,int ngi le ssets such s computer softw re nd scientific innov tionsm ke incre singly import nt contri utions to economic growth.

The Bure u of Economic An lysis (BEA) h s egun to incorpor teinvestments in int ngi le c pit l into the NIPAs. The first step in thisdirection, t ken in 999, w s to tre t spending on computer softw re

s n investment outl y, which enters GDP directly, r ther th n s usiness expense, which is considered n intermedi te input r ther

th n p rt of fin l dem nd; the tre tment of government spending oncomputer softw re w s ch nged t the s me time. Bec use usiness ndgovernment spending on computer softw re h d een growing r pidly comp red to other types of spending, these ch nges r ised the me suredgrowth r te of GDP slightly. In 0 3, BEA pl ns to egin tre ting spend-ing on scientific rese rch nd development s n investment r ther th n

n expense; h d this tre tment een in effect historic lly, it too wouldh ve r ised the ver ge me sured r te of growth of GDP in recentdec des.

Some rese rchers h ve rgued th t investment in int ngi lesshould e defined even more ro dly (Corr do, Hulten, nd Sichel

009; Corr do nd Hulten 0 0). In ddition to rese rch nd develop-ment th t uilds on scientific se of knowledge, for ex mple, thereis n rgument for tre ting s investment the money firms spend onother sorts of new product development, such s the development of new motion pictures or new fin nci l services products. Businesses lsospend money on str tegic pl nning, the implement tion of new usinessprocesses, nd employee tr ining, ll of which m y dd signific ntly tofuture productivity nd thus rgu ly should e tre ted s investment

s well. T king n even ro der perspective, time nd money devoted toform l educ tion dd to the hum n c pit l of the Americ n workforce

nd thus to its future productivity. While ccounting ccur tely for the v lue of these investments poses some difficult me surement ch llenges

(A r h m 0 0), their import nce to future economic growth shouldnot e overlooked. According to some rese rch (Krueger 999), returnson hum n c pit l gener te the lions sh re of n tion l income.



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T Y R Y A | 57

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T Y R Y A | 59

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T Y R Y A | 6

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GDP .Labor Market Trends

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2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012200

300

400

500

600

700

Figure 2-7Weekly Initial Unemployment Insurance Claims, 2004 2012

Thousands, seasonally adjusted

Note: Four-week moving average. Shading denotes recession.Source: Department of Labor, Employment and Training Administration.

Week ended1/28/2012



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Indexed to 100 at NBER-defined trough

Figure 2-8Private Nonfarm Employment During Recoveries

2001

Current (June

2009 trough)

Months from troughSource: Bureau of Labor Statistics, Current Employment Statistics; National Bureau of Economic Research; CEA calculations.

1991



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1979 1983 1987 1991 1995 1999 2003 2007 2011

Figure 2-9Unemployment Rate, 1979 2012

Percent

Note: Shaded areas represent recessions.Source: Bureau of Labor Statistics, Current Population Survey.

Jan-12



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T Y R Y A | 65

-3

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2004 2005 2006 2007 2008 2009 2010 2011 2012

Figure 2-10Consumer Price Inflation, 2004 2011

12-month percent change

Dec-11

Source: Bureau of Labor Statistics, Consumer Price Index.

Core

Headline

1.25

1.50

1.75

2.00

1947:Q1 1957:Q1 1967:Q1 1977:Q1 1987:Q1 1997:Q1 2007:Q1

Markup over unit labor costs

2011:Q4

Average markup1947:Q1-2011:Q4: 1.57

Figure 2-11Price Markup over Unit Labor Costs, Nonfarm Business, 1947 2011

Note: Shading denotes recession.Source: Bureau of Economic Analysis, National Income and Product Accounts; Bureau of Labor Statistics, Productivity and Costs; CEA calculations.

Ratio of prices to unit labor costs



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Nominal

Figure 2-1210-Year Treasury Yields, 2004 2012

Percent

Source: Federal Reserve Board, H.15.

Feb.2

1.86%

-0.30%



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T Y R Y A | 67

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q 7:Q :Q , F R S L O O S

( ) , , .

S k

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74/453

68 | C

k .E k (B k 98 ; H

997; P k R ). C ,

, , (FH , P 988; K L 99 ; K , LS 99 ; L Z 998; R j Z 998; GS z , Z ). G G ( 99 )

, K z , L , K ( 7) k k

k .T x . U , ,

B , L k , M G ( ) CP S , C , N S S

11 S . T , F R NS B F 988 989, ,

.

88

90

92

94

96

98

100

102

2007:Q1 2008:Q1 2009:Q1 2010:Q1 2011:Q1

Indexed to 100 at 2007:Q4

Note: Small firms have fewer than 500 employees. Shaded area denotes recession.Source: Bureau of Labor Statistics, Business Employment Dynamics.

Figure 2-13Private Sector Job Recovery by Firm Size, 2007 2011

Large firms

Small firms

2011:Q2



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T Y R Y A | 69

F . k , 7 9, k

x . F , k , k

( ).T

x

P , k $5

(C B k ). S 9, , k

S , k , ,

. B JD , B z C ,

k 5 k .

.6 k , 8.5

12 T q .

0

5

10

15

20

25

30

35

40

0

50

100

150

200

250

300

350

400

2007 2008 2009 2010 2011

Figure 2-14Small Business Commercial and Industrial Loans, 2007 2011

2011:Q3

Note: Loans with original amounts of less than $1 million.Source: Federal Deposit Insurance Corporation, Statistics on Banking.

Billions of dollars Millions of loans

Value of loans(left axis)

Number of loans

(right axis)



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B x - : SBA R F S F D R

The Sm ll Business Administr tion (SBA) w s cre ted y Congressin 953 to id nd provide technic l support for sm ll usinesses.1 M ny

SBA progr ms seek to minimize the riskiness of sm ll- usiness lo nsfor lenders y gu r nteeing portion of these lo ns g inst def ult. SBAcoll or tes with feder l gencies nd the White House to ensure th t

t le st 3 percent of Feder l Government contr ct opportunities, worthne rly $ 00 illion, re v il le to sm ll usinesses.

Tr dition l SBA progr ms, the 7( ) nd 504 lo ns, t rget sm llfirms. These progr ms h ve een found to h ve positive imp ct onloc l economic perform nce (Cr ig, J ckson, nd Thomson 005). Inresponse to ongoing tight credit conditions f cing sm ll firms during therecovery, the Sm ll Business Jo s Act of 0 0 incre sed the lo n limitsfor SBA lo n gu r ntees. The limits for equipment nd re l est te lo nswere incre sed perm nently nd the limits for working c pit l lo nsthrough the SBA Express progr m were incre sed tempor rily. BetweenFY 0 0 nd FY 0 , the num er of SBA lo ns pproved incre sed .5percent, while the v lue of SBA lo ns pproved incre sed 45.4 percent(see ox figure). SBA incre sed over ll lending supported to $30.5 il-lion in FY 0 , the highest ever lending ye r in its 60-ye r history.2

Recent economic rese rch shows th t new nd young firms con-tri ute disproportion tely to jo growth in the U.S. (see Ch pter 6). TheO m Administr tion h s cre ted the St rtup Americ initi tive tosupport the role th t st rtups pl y in economic growth nd jo cre tion.The initi tive ims to cceler te high-growth entrepreneurship throughpolicies th t unlock ccess to c pit l for high-growth comp nies, cre tementoring progr ms, cceler te l -to-m rket innov tion, nd m kegovernment work etter for entrepreneurs.

As p rt of the St rtup Americ initi tive, SBA is improving ccessto c pit l for high-growth sm ll usinesses. The SBA h s l unched twonew Sm ll Business Investment Comp ny (SBIC) progr ms, e ch seek-ing to gu r ntee n ddition l $ illion in priv te investment withinfive ye rs: the E rly-St ge Innov tion Fund for seed- nd e rly-st gecomp nies nd the Imp ct Investment Fund for comp nies in re sof n tion l priority, including underserved m rkets nd emerging

1T S B A

, , , , :// . . / / / /S z _ST . .2 L SBA 7( ) 5

5k . T x 7( ) 5 ,

.



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T Y R Y A | 7

sectors, such s energy nd educ tion. SBA licensed the first SBICImp ct Investment Fund in Michig n in July 0 . The InvestMichig n!Mezz nine Fund, with resources of $ 30 million, is pu lic-priv tep rtnership etween SBA, Dow Chemic l Comp ny, nd Michig nGrowth C pit l P rtners th t will e m n ged priv tely nd will focuson funding new nd sm ll firms with pl ns to exp nd their oper tions

nd cre te jo s. SBA lso deepened its commitment to underservedm rkets in 0 with the implement tion of the Underserved M rketsIniti tive, which will dissemin te SBA resources to youth, rur l, veter n,low-income, nd other communities.

40

50

60

70

80

90

100

110

120

10

12

14

16

18

20

22

24

26

28

30

2006 2007 2008 2009 2010 2011

Value of Loans

Number of Loans

Billions of dollars

Source: Small Business Administration, Agency Financial Report, 2011.

SBA Loans Approved, 2006-2011Thousands of loans

SBA ugmented its role s coordin tor of feder l gencies insupporting sm ll usinesses in 0 . As is common fter fin nci l crises,sm ll firms re experiencing difficulties m n ging c sh flow due to

dverse credit conditions. To improve ccess to working c pit l forthous nds of sm ll firms, in Septem er, President O m issued nexecutive order to institute the QuickP y progr m, which requires n

gency to p y its contr ctors within 5 d ys nd, t m ximum, within30 d ys. As with the QuickP y progr m, SBA pl ys coordin ting rolefor the Sm ll Business Innov tion Rese rch (SBIR) progr m, whichfocuses on sm ll high-technology firms nd includes gr nting gen-cies. Evidence suggests th t SBA nd SBIR involvement m ke differ-ence to young firms. Between 983 nd 997 w rdees of the SBIR pro-gr m su sequently h d su st nti lly higher employment nd s les

growth comp red to m tched s mple of simil r firms (Lerner 999). InDecem er, Congress p ssed long-term re uthoriz tion of the SBIR progr m th t will incre se its funding.



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7 | C

, .9 CDFI , , .

I 9, O A

. T : x

. I , A $

, k , C D F I

. T

S S B C I x $ 5 x ,

S B A (SBA), D A Ex I B k. O A

. F x , S 9

k ,

, . G

, ,

, .B FY , k

T S B L F (SBLF)

SSBCI . A J ,

SBLF $ , , F Y , SBA

. (B x A SBA

k S AT x

j

13 S B z C 5 . L ,

B z C J D 14 I

. j (W H ).



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T Y R Y A | 7

, . S W F G

J 9 , , x , J 8. T

x .5 M ,

J 8, F I , x

x ( ) x (8 x

j x j 8.

The Long-Term Outlook

L k , A j 9 (T

, FY B

1 T W F G 6 x D & B $

. S J ( ).

0

5

10

15

20

25

30

35

2003-Q3 2005-Q3 2007-Q3 2009-Q3 2011-Q3

Percent of respondents

Note: Small firms have less than $20 million in annual revenue. Shaded area denotesrecession.Source: Wells Fargo/Gallup Small Business Survey cited in Jacobe (2012).

Figure 2-15Employment Outlook for Small Businesses, 2003 2012

Employment expected toincrease over next

12 months

2012:Q1

Employment expected todecrease over next

12 months



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7 | C

, , . T A j GDP

.6 .

T A x : T A N ,

9. O , T . T B

j k z . , 8.

8.9

. T : , . T , , T

k

T A E F

NominalGDP

RealGDP

(chain-type)

GDPpriceindex

(chain-type)

Con-sumerpriceindex

(CPI-U)

Interestrate,91-day

Treasury bills

(percent)

Interestrate,10-yearTreasury

notes(percent)

Percent change, Q4-to-Q4 Level, calendar year

( ) 4.7 3.1 1.6 1.2 0.1 3.2

4.0 1.7 2.2 3.6 0.1 2.8

4.6 3.0 1.6 1.9 0.1 2.84.7 3.0 1.6 1.9 0.2 3.5

5.8 4.0 1.7 2.0 1.4 3.9

5 6.1 4.2 1.8 2.0 2.7 4.46 5.8 3.9 1.8 2.1 3.8 4.77 5.7 3.8 1.8 2.1 4.1 5.08 4.6 2.8 1.8 2.1 4.1 5.1

9 4.4 2.6 1.8 2.1 4.1 5.14.3 2.5 1.8 2.1 4.1 5.1

4.3 2.5 1.8 2.1 4.1 5.3

4.3 2.5 1.8 2.1 4.1 5.3

Note: 2011-2022 orecasts were based on data available as o November 15, 2011, and were used or the FY 2013Budget. e interest rate on 91-day T-bills is measured on a secondary-market discount basis.

Source: e orecast was done jointly by the Council o Economic Advisers, the Department o Commerce(Bureau o Economic Analysis), the Department o the Treasury, and the Ofce o Management and Budget.



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T Y R Y A | 75

I F ,

B C 8. 7. j 8.6 8.

S , F R O M k j 8. 8.5

q 7. 8. . A CBO FOMC

J k .

T C E A z F ,

57, , , , , ND , J , . L k ,

j 6,

T A L M k F , F

Unemployment rate (percent) Non arm payrollemploymente

(averagemonthly change,

Q4-to-Q4,thousands)Feb-2012

Annual average Fourthquarter

FY 2013Budget

Nov-2011

CBODec-2011

Blue Chipc

low-highFeb-2012

FOMCd

low-highJan-2012

9.0 9.0 146

8.9 8.8 8.0 8.6 8.2 8.5 167

8.6 9.1 7.4 8.4 7.4 8.1 220

8.1 8.7 6.7 7.6 264

5 7.3 7.4 284

6 6.5 6.3 2597 5.8 5.7 2518 5.5 5.5 1319 5.4 5.5 101

5.4 5.4 92

5.4 5.4 97

5.4 5.3 89

a e Administration Budget orecast (done jointly by the Council o Economic Advisers, the Ofce o Manage-ment and Budget, the Department o the Treasury, and the Department o Commerce) was based on data available

as o November 15, 2011.b e Congressional Budget Ofce orecast was completed in early December.c e Blue Chip Economic Indicators or February 2012 was based on a survey o more than 50 pro essional ore-

casters conducted on February 6-7, 2012. e high-10 and low-10 orecasts are the average o the ten highest andten lowest orecasts.

d e high and low end o the central tendency o the Federal Open Market Committee announced on January 25, 2012.

e Based on data available on February 5, 2012.Source: Aspen Publishers, Blue Chip Economic Indicators; Federal Reserve, Federal Open Market Committee.



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67, . A , j , .8 .D k , A

x . W

z , .

Growth in GDP over the Long TermT

, . T

U.S. GDP GDP

A , . B

:Q j FY B GDP j .5 .

T A GDP.

, , ,

, k k, , GDP . E T

: T

k 95 k k

. T 7:Q :Q ,

7 9 . T A j

:Q , j 7:Q :Q , .

T k j . , j ( , ),

j C B . O j . , ),

j . T

x



83/453

T Y R Y A | 77

, j k . T

. T 6 J 8 D

(F 6). A

, x T k ,

j . T q

x . x ( , ) ,

7 ( , ).

1 B ,

1 T , GDP 7:Q :Q ,

7:Q ( .8 ) , 5. 7 j

T C A P R GDP G , 95

Component

Growth ratea

History,peak-to-

peak

Recent his-tory, since

peak Forecast

History andorecast,

since peak

1953:Q2 to2007:Q4b

2007:Q4 to2011:Q3

2011:Q3 to2022:Q4

2007:Q4 to2022:Q4

1 C 6+1.4 1.1 1.0 1.02 L 0.2 0.8 0.1 0.33 E 0.0 1.2 0.4 0.04 R

0.0 1.0 0.1 0.2

5 A k ( )0.3 0.1 0.0 0.0

6 O ( , )

2.1 1.9 2.3 2.2

7 R GDP 0.2 0.2 0.5 0.38 S : A GDP 3.2 0.1 3.1 2.49 M : P GDP 3.2 2.5 2.5 2.5a All contributions are in percentage points at an annual rate.b 1953:Q2 and 2007:Q4 are business-cycle peaks.Note: Population, labor orce, and household employment have been adjusted or discontinuities in the population

series. Non arm business employment, workweek, and productivity come rom the Labor Productivity and Costsdatabase maintained by the Bureau o Labor Statistics.

Source: Bureau o Labor Statistics, Current Population Survey, Labor Productivity and Costs; Bureau o EconomicAnalysis, National Income and Product Accounts; Department o the Treasury; Ofce o Management and Budget;CEA calculations.



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, j j .

T k k j j ( 5, )

, , ( 5, ). T kx k

.L j .

z ( 6, ), 95 7 ( 6, ). T

k j k . O

, ,

T GDP x GDP j ( 7,

. T , , ,

, z .

40

50

60

70

80

90

100

2002:Q1 2004:Q1 2006:Q1 2008:Q1 2010:Q1 2012:Q1

Educational enrollment rate

Labor force participationand enrollment rate

Labor force participation rate

Note: Enrollment rate is defined as the number of those enrolled in school but not in the labor forceas a share of the population. Shading denotes recession.Source: Bureau of Labor Statistics; CEA calculations.

Percent, seasonally adjusted

Figure 2-16Labor Force Participation and Educational Enrollment,

Ages 16 24, 2002 2011

2011:Q4



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T Y R Y A | 79

S , GDP j . j ( 8 .5

( 9, ). A GDP x

GDP j , ) k j . S

x . , , 57 , j GD

7 R GDP j .5

( 8, ),

. ( 8, ). T j GDP j

7 9 , x

j , x

A q k,

q k GDP . I A B , U.S.

. T . T GDP

D U.S. .

Conclusion

T U.S.

GDP 99 ,

. T k

, k .A , k

, q ,



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8 | C

. E q x

A , k

U.S. . O x j . T

j k 99 ,



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8

C H A P T E R 3

RESTORING FISCALRESPONSIBILITY

W P O k , A $ . j $8 .1 T A

N .

x

. I ,

. I , , ,

, k

.

R z k , O A I F , P S P A Y

x

. I M , P C A , x

k ,

, P C $ k B C A , $ .

1 I , , x .



88/453

8 | C

. A ,

C A k $ ,

. T

x k M ,

I q A .

T

j k , A , z z

k A

P k

k

.T

R . A A C A B C

F k . B j

, C k A N k.

Determinants of Current Deficits

U , j O M B

$ . (8.7 GDP) $66

GDP). D j , x

. T G R . I ,



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R F R |

, x . W

, , j

x , j .

A , . A ,

, $ . S D . T M P D

, , M $ 5 . I .T x ,

, x . I ,

, $ . (R H

, F x j . GDP 7.7 . P

x , ,

x x

x .B , z

z ,

A R R A ( R A ) $8 , T A R(TARP) j $68 . O

x ,

. F x , T P T x C C , x x ,

2 T j z I , , C B

$5.6 (CBO ). N z , $6.5

.



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8 | C

, x M , F

, I q A

, x , z . W k G R . T

, C B O (CBO)

k O A q . I

9 ,

, x .T

. F D , J L D ,

, ,

(A G ). A

0

200

400

600

800

1,000

1,200

1,400

1,600

2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

War costsBush-era tax cutsRecovery measuresTARP, Fannie, and FreddieEconomic downturn

Deficit without these factors

Billions of dollars

Figure 3-1Selected Components of Deficit Projections: 2009 2019

Note: Based on CBO budget projections. CBO employs different economicassumptions and methodology than OMB. As a result, the projections presented inthis figure may differ from those presented by OMB.Source: Ruffing and Horney (2011).



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R F R |

U.S. , q k .

W ,

F .Falling Effective Tax Rates on Upper-Income Taxpayers

E x , k x , x . I ,

x ,

, x

A , x

. S P x A O T x C , x

x , x A .

I x , x k x

. U , x A

97 , 98 O P . E x

, k 98 k 98 . I x x

F x ., x q

96 .A x

, x . W E G T x R R

A x , x,

5. . T , , x

k .T x . F x , F



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86 | C

, 8, x .

q . A x .7 . , .7 .

T , P F Y B

x $ 5 , ,

q x , k x k $ 5 , .

Heterogeneity in Effective Tax Rates among High-IncomeTaxpayers

T x x . E x x

x x ,

. F x , x x

x , x

) x .

0

10

20

30

40

50

60

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Average tax rate

Note: Average Federal (income plus Federal Insurance Contributions Act) tax rates for asample of 2005 taxpayers after adjusting for growth in the National Average Wage Index.Source: Internal Revenue System Statistics of Income 2005 Public Use File, NationalBureau of Economic Research TAXSIM, and CEA calculations.

Figure 3-2Average Tax Rates for Selected Income GroupsUnder a Fixed Income Distribution, 1960 2010

Top 0.1%

Top 1%

Middle20%



93/453

R F R |

I , x q , ( , , x ) x

. ( ) 9. 9 . T

x x . F x x

9. ( 8 ). F x ,

k . A , x 8.7 x ,

x .6 ( T T

. I 8, x (7.5 )

F x , 59 ( .8 ) .

Addressing the Role Of Exclusions and Deductions in EffectiveTax Burdens

A , x x , x . M ,

x x . B , ,

-10

-5

0

5

10

15

20

25

30

1stquintile

2ndquintile

Middlequintile

4thquintile

Highestquintile

Top 10 percent

Top 5 percent

Top 1 percent

Top 0.1 percent

Average tax rate, 2000

Average tax rate, 2008

Average tax rate

Note: Quintiles are based on adjusted gross income.Source: Department of Treasury.

Figure 3-3Average Individual Income Tax Rates by Income

Quintile, 2000 and 2008



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x x . D ,

M T x (AMT) x ,

x (B 7). I , x x

x x .A x

, P x

P B A $ ,

x . I , P x ,

x x . (F x

E A B x ).

The Fiscal Outlook

W , . M ,

A F Y B

T D A F T x R

Family cash income groupAverage rate at each breakpoint in the rate distribution

10th 25th Median 75th 90th

L q 13.7 0.0 5.4 13.1 15.5S q 8.7 0.5 7.2 17.0 20.9M q 1.7 5.4 13.3 20.4 23.5F q 7.2 12.1 17.2 22.3 26.2H q 12.1 17.4 21.9 26.0 29.3

Total 0.0 5.0 14.5 20.7 25.0

T 8.7 21.2 29.6 32.3 34.6

Note: Calculations assume 2012 tax law with an AMT patch and 2012 income levels, and includes individualincome tax, corporate income tax, and payroll tax. For the lowest income quintile, the calculation o average rates

and the distribution o average rates do not include amilies with negative income. ese amilies are included inthe total.Source: Department o Treasury.



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R F R |

j j j

O A .

Medium-Term Budget ProjectionsU OMB j , GDP j

GDP .7 GDP , F j

. T x AMT , x

x x

O C M .

T k A k

A C A B C A . N ,

. T P

0

12

3

4

5

6

7

8

9

10

2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Percent of GDP

Note: See text for policies incorporated in OMB's adjusted baseline.Source: Office of Management and Budget (2012a).

Figure 3-4Projected Medium-Term Budget Deficits, 2011 2022

Adjusted baseline



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9 | C

E A B x 3- :M P T x C

T x ch nges re typic lly ev lu ted sed on sever l key criteri ,

including efficiency, simplicity, e se of compli nce nd dministr tion,imp ct on economic ctivity, nd progressivity. Progressivity is the me -sure of how p rticul r policy ffects households with differing levelsof income or resources. F irness is the essence of progressivity; m ny t xesp rticul rly income t xes re designed to ensure lighter t x

urden for households with less income nd lower ility to p y.Economists typic lly define progressive t x s one th t h s ver-

ge t x r tes th t incre se with income; under progressive t x code,higher-income t xp yers devote higher sh re of their income to t xesth n other t xp yers. A progressive t x ch nge is one th t lowers ver get x r tes more for low- nd middle-income households rel tive to othersor r ises ver ge t x r tes more for high-income households rel tive toothers. For ex mple, the recent percent ge point cut in the p yroll t xis considered progressive ec use it reduces ver ge t x r tes more forlow- nd middle-income f milies comp red to high-income f milies.

Other me sures of progressivity, such s me sures th t referstrictly to doll r ch nges in t xes p id or to the percent ge ch nge in

t xes p id, c n e misle ding. For ex mple, t x cut might reducet xes p id y low-income households from $ 00 to $50 ( ch nge of 50 percent), nd reduce t xes p id y high-income households from$500,000 to $400,000 ( ch nge of just 0 percent). Some might rgueth t this ch nge is progressive ec use it reduces t xes p id y low-income households y proportion tely more th n it reduces t xes p id

y high-income households, ut this me sure is ctu lly inconclusiveec use it tells us nothing out the ch nge in ver ge t x r tes. Along

these s me lines, metrics th t focus on the sh re of t xes p id re notuseful ec use they do not incorpor te inform tion on ver ge t x r tes

y income group.The definition of income or well- eing c n lso e import nt

when me suring progressivity. Some forms of compens tionsuch semployer contri utions to retirement ccount or he lth insur ncepremiums p id y n employerm y not e considered income for t xpurposes ut might in principle e considered s income for me suringt xp yer resources. Simil rly, income tr nsfers such s unemployment

compens tion or Soci l Security enefits could e included in incomewhen me suring progressivity.The extent to which the t x code equ lizes income is expressed

gr phic lly y the Lorenz curve in the ox, which shows the cumul tive



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R F R |

The Vital Role of Economic Growth in Future Fiscal OutcomesB

. B . D

j

, $ .9 x 9 ( F ). OMB ( ) j GDP ,

GDP , $7 . S , CBO ( ) j .

distri ution of income efore nd fter t xes. The 45 degree linerepresents perfectly equ l distri ution of income; the closer theLorenz curve to th t line of equ lity, the more equ l the distri ution of income. A progressive t x code is one th t shifts the income distri utioncloser to the 45 degree line. In 007, the t x code helped to improve theprogressivity of the income distri ution, s illustr ted y the gr ph, y m king fter-t x income more equ l th n efore-t x income. However,even the fter-t x Lorenz curve w s well elow the 45 degree line,me ning th t the distri ution of fter-t x income w s highly skewedtow rds the highest-income t xp yers.

0

10

20

30

40

50

60

70

80

90

100

0 20 40 60 80 100Cumulative share of population

Before-taxincome

After-taxincome

Line of equality

Source: Congressional Budget Office (2011a).

Cumulative share of incomeIncome Concentration, 2007



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GDP j .

T k k

A J A . A ,3

, . E k.

Improvement in Long-Run Budget ProjectionsA

A . A , B C A $ x k , $ .

3 T P A J A ; .

D W 3- : D IRS S I D

The St tistics of Income (SOI) Division of the Tre sury Dep rt-ments Intern l Revenue Service produces inform tive nnu l st tistics.

The resulting inform tion is n import nt input to the N tion l Incomend Product Accounts nd h s een inv lu le for the ev lu tion of economic nd t x policies, s well s for usiness decisions.

One dv nt ge of SOI st tistics is th t they re v il le for longperiod of time: historic l d t series cover the period from 9 6 to thepresent. Of p rticul r interest re t ul tions of selected items y county

nd ZIP Code, such s migr tion p tterns. Extensive d t lso rev il le on usinesses, including corpor tions, p rtnerships, nd sole

proprietorships. In response to incre sed glo liz tion, for ex mple,SOI produces regul r reports on oth foreign-owned U.S. corpor tions

nd U.S.-owned corpor tions oper ting in other counties.More th n 4,000 det iled t les nd regul r reports re v il le

to the pu lic online through the T x St ts p ges loc ted t www.irs.gov.Periodic speci l reports h ve ex mined topics such s pensions, foreigne rned income, nd nonc sh ch rit le contri utions. Users m y cre tecustom t les using t le wiz rd pplic tion. Import ntly, SOI p ins-t kingly s fegu rds the confidenti lity nd nonymity of the underlying

inform tion it dr ws on. St tistics derived from the SOI provide richsource of inform tion for policym kers, usiness people, rese rchers,nd pu lic interest groups, mong others.



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R F R |

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k , ,

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A C A .) T A M

I C M M I q I P A B ,

M , . T j

A C A M . TT ,

M j GDP . T

M T j A C A . T ,

.

The Importance of RestoringFiscal Sustainability

R . L

. B 9

8, A

A k, . A GDP ,

q N

. T



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GDP 6 O z ). H

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Differences in government ccounting pr ctices nd in the typesof ssets held y centr l governments complic te the comp rison of

government de t cross countries. These complic tions c n le d toconfusion over the most ppropri te me sure of government de t ndthe rel tive levels of de t for different countries.

One source of misunderst nding is the distinction etween pu licde t nd tot l government de t. Pu lic de t refers to government de theld y priv te investors, including individu ls, pension funds, mutu lfunds, nd corpor tions. Tot l government de t is the sum of pu licde t nd intr government l de tgovernment de t held in government

ccounts, such s government securities held in the U.S. Soci l Security nd Medic re trust funds. Economists widely recognize pu lic de t s

the more relev nt me sure since it is government orrowing from thepriv te sector th t c n e expected to inter ct with credit m rkets.

In most Org nis tion for Economic Co-oper tion nd Develop-ment (OECD) countries, there is little intr government l de t. In theUnited St tes nd C n d , however, udget ry conventions give rise tol rge ccumul tions of such de t. At the end of Decem er 0 , U.S.de t tot led $ 5. trillion, of which $ 0.5 trillion w s held y the pu lic

nd $4.8 trillion w s intr government l de t. Intr government l de t issimil rly import nt in C n d . Including intr government l de t whenm king intern tion l comp risons le ds to n ex gger ted impressionof government inde tedness in the United St tes nd C n d rel tive toother OECD n tions.

A second source of confusion is the distinction etween grossde t nd net de t. The OECD me sures gross de t s tot l li ilitiesoutst nding, including securities issued on eh lf of the government(such s Tre sury securities), currency, nd li ilities to governmentemployee pension funds. Net de t is me sured s gross de t minusgovernment-owned fin nci l ssets. The import nce of this distinction v ries cross countries. In J p n, for ex mple, the difference is st rk:gross government de t equ led 0 percent of GDP in 0 0, while netgovernment de t w s just 7 percent of GDP.

A fin l source of misunderst nding concerns the p rticul r govern-ment sector eing me sured. The OECD presents me sures of gener lgovernment de t, which encomp sses de t t ll levels of government,

including St te nd loc l governments in the United St tes, nd centr lgovernment de t. Both of these me sures c rry economic signific nce,

ut the distinction m tters insof r s centr l governments gener lly renot li le for de t incurred y other levels of government.



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Great Depression (national)

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Boston 1989

Real price level compared to peak

Source: S&P/Case-Shiller Home Price Index; the Great Depression time series fromShiller (2005).

Figure 4-1Housing Busts in U.S. History



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Mortgage value per home-owninghousehold ($2010)

(left axis)

Price-to-rent ratio(right axis)

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Source: CoreLogic; Department of Labor; Bureau of Labor Statistics, Consumer PriceIndex.

Figure 4-2Price-to-Rent Ratio and Mortgage Debt

Price-to-rent ratio



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Figure 4-3S&P/Case-Shiller: January 2009 Expectations of Future House Prices and

Actual Price Index

Housing pricesimplied by futurescontracts traded in

January 2009

Actual



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Mortg ge r tes in the United St tes re ched historic lows in 0 ,

presenting n opportunity for m ny homeowners to s ve money y refin ncing their fixed-r te mortg ges. However, refin ncing typic lly involves num er of costs th t push the effective interest r te ove ther tes reported in news medi . These costs include those ssoci ted witho t ining new lo n, such s title insur nce nd v rious dministr tivefees; risk-m n gement ch rges rel ted to lo n origin tion (for ex mplepoints); underwriting ch rges for ppr is l of the house; nd the moremund ne costs of g thering document tion.

How does homeowner decide whether it is worth p ying theddition l costs to re p the enefit of the lower r te? The first step in

ev lu ting refin ncing is to get cle r nd comprehensive summ ry of costs ssoci ted with new lo n; these should e provided y your lo nofficer or mortg ge roker on HUD- form. While m ny of these costsc n e rolled into the lo n, some h ve to e p id in c sh up front.

The second step is to l y out the stre m of ll p yments requiredunder the origin l lo n nd the new lo n used for refin ncing. Althoughthis process m y seem involved, it will llow you to t ke into ccount

refin ncing costs s well s the f ct th t you will e m king p yments on refin nced mortg ge over longer period th n you will h ve rem in-ing on the existing mortg ge.

Third, those p yment stre ms need to e converted into onenum erthe mount of spending tod y th t this stre m of p yments isworth. This is known s the net present v lue or NPV. The net present v lue discounts costs p id in the future to reflect the time v lue of money

nd the uncert inty ssoci ted with future returns. In the simplest pos-si le form, it is etter to h ve doll r tod y th n doll r tomorrow,

s this doll r c n e invested nd grow in v lue y the time tomorrow rrives. Hence, ll future p yments re discounted rel tive to tod ys

outl ys. The choice of the discount r te merits sep r te discussion th tis eyond the scope of this ex mple. However, some common choicesinclude discounting t the risk-free r te (commonly pproxim ted y the 0-ye r Tre sury r te) or the expected r te of return for the stock m rket ( pproxim ted, s y, y the long-term ver ge return on the S&P500 index). The NPV c lcul tion c n e c rried out with spre dsheet

progr m such s Microsoft Excel or on num er of we sites. Once NPV v lues re computed for oth p yment stre ms, the one with the lower v lue is the etter choice.



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The comput tion nd comp rison of net present v lues is them in ide ehind ro d r nge of online c lcul tors designed to

nswer the question of whether refin ncing m kes sense. An ex mplec n e found on J ck Guttent gs Mortg ge Professors We site thttp://www.mtgprofessor.com/c lcul tors/C lcul tor3 .html. Somemortg ge rokers re fond of m king use of simple rules of thum s

shortcut for using the NPV ppro ch. For ex mple, they m y suggestth t the new mortg ge r te h s to e percent ge point lower to justify refin ncing with typic l closing costs. Recent estim tes of such rule-of-thum threshold differences in interest r tes h ve v ried etween nd

.5 percent ge points.One often overlooked cost of refin ncing h s not yet een men-

tioned. By refin ncing tod y, one gener lly forgoes the opportunity torefin nce in the future if interest r tes were to drop it further. Supposeyou determine th t refin ncing 5.75 percent lo n into 4.5 percentlo n is dv nt geous from n NPV st ndpoint. Then refin ncing theorigin l lo n into 4. 5 percent lo n would e even more enefici l, utrefin ncing from 4.5 percent lo n would not. This difference etweenp yments t 4.5 percent nd 4. 5 percent is essenti lly the v lue of theforgone option to del y refin ncing. The v lue of preserving this optionh s fluctu ted over time, ec use it cle rly depends on the vol tility of interest r tes, the economic outlook, nd the ility to m int in ccessto credit m rkets- nontrivi l concern for tod ys orrowers.

In recent work, Sumit Ag rw l, John Driscoll nd D vid L i son( 007) c lcul ted the optim l interest r te differenti l t which to refi-n nce th t explicitly t kes into ccount the forementioned option v lue(these c lcul tions c n e found t http://zwicke.n er.org/refin nce/).T ke, for ex mple, f mily th t pl ns to st y in their house for 0 ye rs,h s $ 50,000 mortg ge t 6 percent interest r te nd h s m rgin l t x

r te of 8 percent. For this f mily, ssuming n upfront fee of percent-ge point of mortg ge v lue ( point) nd c sh closing costs of $ ,000,

refin ncing is optim l if the interest r te on the new mortg ge is 4.6percent or less. Unlike the simple rule of thum , this c lcul tion t kesinto ccount f mily expect tions of the future infl tion r te, interest r te vol tility, nd how long they pl n to st y in the housethe option v luedetermin ntswhich ffect the ultim te recommend tion.



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D W 4- : N C S D M D P

There re currently four sic sources of lo n-level d t on mort-

g ge de t: the Home Mortg ge Disclosure Act (HMDA) d t se, d treported y mortg ge servicers, credit ure u d t , nd pu lic recordsd t . E ch of these sources provides insight out mortg ge holdings,

ut the existing system is in dequ te for me suring the extent nd own-ership o

president's 2012 economic report to congress

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