Optimal Welfare-to-Work Programs

U

NEQUAL

W

E

S

TAND

An empirical analysis of economic inequality in the

United States, 1967-2006

Jonathan Heathcote

Federal Reserve Bank of Minneapolis, and CEPR

Fabrizio Perri

University of Minnesota, Federal Reserve Bank of Minneapolis, CEPR and NBER

Gianluca Violante

New York University, CEPR and NBER

RED special issue

• _{Macroeconomics is expanding its focus from aggregate dynamics}

to dynamics of entire equilibrium distributions across agents

• _{Representative-agent business-cycle literature built on well}

defined set of facts about aggregate variables

• _{Heterogeneous-agents incomplete-markets literature lacks}

systematic set of “uncontroversial" facts about cross-sections

• _{RED special issue: consistently document facts about key} dimensions of cross-sectional inequality in several countries

I USA, UK, Canada - Italy, Germany, Spain, Sweden - Russia,

RED special issue

• _{Macroeconomics is expanding its focus from aggregate dynamics}

to dynamics of entire equilibrium distributions across agents

• _{Representative-agent business-cycle literature built on well}

defined set of facts about aggregate variables

• _{Heterogeneous-agents incomplete-markets literature lacks}

systematic set of “uncontroversial" facts about cross-sections • _{RED special issue: consistently document facts about key}

dimensions of cross-sectional inequality in several countries

I USA, UK, Canada - Italy, Germany, Spain, Sweden - Russia,

RED special issue

• _{Macroeconomics is expanding its focus from aggregate dynamics}

to dynamics of entire equilibrium distributions across agents

• _{Representative-agent business-cycle literature built on well}

defined set of facts about aggregate variables

• _{Heterogeneous-agents incomplete-markets literature lacks}

systematic set of “uncontroversial" facts about cross-sections

• _{RED special issue: consistently document facts about key} dimensions of cross-sectional inequality in several countries

I USA, UK, Canada - Italy, Germany, Spain, Sweden - Russia,

Economic inequality in the United States

1970 1975 1980 1985 1990 1995 2000 2005 0.25

0.3 0.35 0.4 0.45

Year

Variance of Log

Wage and Consumption Inequality

Men Hourly Wages(CPS)

Economic inequality in the United States

1970 1975 1980 1985 1990 1995 2000 2005 0.25

0.3 0.35 0.4 0.45

Year

Variance of Log

Wage and Consumption Inequality

Men Hourly Wages (CPS) Household Consumption (CEX)

From “endowments” to “welfare”

• _{Several intervening choices and institutions in between individual}

wages and household consumption

1. individual labor supply

2. income pooling within family

3. government taxes and transfers

4. borrowing/saving through financial markets

• _{Some mechanisms acts as dampening forces, others as}

amplifying forces • _{Aim of this paper: descriptive empirical study to shed light on the}

From “endowments” to “welfare”

• _{Several intervening choices and institutions in between individual}

wages and household consumption

1. individual labor supply

2. income pooling within family

3. government taxes and transfers

4. borrowing/saving through financial markets

• _{Some mechanisms acts as dampening forces, others as}

amplifying forces

• _{Aim of this paper: descriptive empirical study to shed light on the}

Organizing device: household budget constraint

c + _a0 _{= a +}

N

X

i₌₁

w_ih_i + _bP + _d + _bG _{− τ}

• _{wi: individual hourly wage}

• _{hi: individual hours worked}

• _{N: number of workers in the household}

• _bP: net private transfers

• _{d: household net asset income}

• _bG: government transfers

• _{τ: taxes}

Intervening choices and institutions

c + _a0 = _a +

N

X

i=1

w_ih_i + _bP + _d + _bG _{− τ}

• _{wi individual wage}

• _{wihi individual labor supply}

• PN

i₌₁wihi family labor supply

• PN

i₌₁ wihi + b

P _{+ d} family/social networks + financial markets

• PN

i₌₁ wihi + b

P _{+ d + b}G _{− τ} public transfers and tax system

Three micro data sets representative of US population

1. Current Population Survey (CPS), 1968-2007

• _{repeated cross-section: ASEC supplement (March) covering}

60,000+ households

• _{key strength: its size}

2. Consumer Expenditure Survey (CEX), 1980-2007

• _{repeated cross-section: Interview Survey covering 15,000+}

households

• _{key strength: consumption data}

3. Panel Study of Income Dynamics (PSID), 1968-97, 99, 2001, 03

• _{longitudinal study: SRC sample following 3,000 families}

Three micro data sets representative of US population

1. Current Population Survey (CPS), 1968-2007

• _{repeated cross-section: ASEC supplement (March) covering}

60,000+ households

• _{key strength: its size}

2. Consumer Expenditure Survey (CEX), 1980-2007

• _{repeated cross-section: Interview Survey covering 15,000+}

households

• _{key strength: consumption data}

3. Panel Study of Income Dynamics (PSID), 1968-97, 99, 2001, 03

• _{longitudinal study: SRC sample following 3,000 families}

Three micro data sets representative of US population

1. Current Population Survey (CPS), 1968-2007

• _{repeated cross-section: ASEC supplement (March) covering}

60,000+ households

• _{key strength: its size}

2. Consumer Expenditure Survey (CEX), 1980-2007

• _{repeated cross-section: Interview Survey covering 15,000+}

households

• _{key strength: consumption data}

3. Panel Study of Income Dynamics (PSID), 1968-97, 99, 2001, 03

• _{longitudinal study: SRC sample following 3,000 families}

Sample selection

1. Sample A

• _{“Clean” version of raw data: drop record only if seriously}

incomplete or implausible

• _{used for population-level statistics (like NIPA)}

2. Sample B

• _{restrict to households where at least one member is of}

working age 25-60

• _{used for household-level (earnings, income, consumption)}

statistics

3. Sample C

• _{restricted to those who work at least 260 hours per year}

Macro facts in micro data

1970 1975 1980 1985 1990 1995 2000 2005 9.1 9.2 9.3 9.4 9.5 9.6 9.7 9.8 9.9

10 Labor Income Per−capita

Year

Log − 2003 $

1970 1980 1990 2000

9.5 9.6 9.7 9.8 9.9 10 10.1 10.2 10.3 10.4

Personal Income Per−capita (NIPA) vs

Money Income Per−capita (CPS)

Year

Log − 2003 $

CPS NIPA CPS

NIPA

• _{Labor income p.c. in CPS aligns well with NIPA}

Individual wage inequality

1970 1980 1990 2000 0.2 0.25 0.3 0.35 0.4 0.45 Year

Variance of Log Hourly Wages

1970 1980 1990 2000 0.26 0.28 0.3 0.32 0.34 0.36 0.38

Gini Coefficient of Hourly Wages

Year

1970 1980 1990 2000 1.8

2 2.2

2.4 P50−P10 Ratio of Hourly Wages

Year 1970 1980 1990 2000

1.8 2 2.2 2.4

Year

P90−P50 Ratio of Hourly Wages

Decomposing (male) wage inequality

1970 1975 1980 1985 1990 1995 2000 2005 0.25

0.3 0.35 0.4 0.45

Variance of Log Male Wage

Year

Raw Residual

Recap: individual wage inequality

1. Continuous increase since late 1960s

• _{1970s: concentrated at the bottom}

• _{1980s: throughout the distribution}

• _{1990s: concentrated at the top}

2. Striking similarity between men’s and women’s trends...

• _{... except for 1970s}

3. Two-thirds of the increase is residual

• _{virtually 100% residual in the 1970s}

Recap: individual wage inequality

1. Continuous increase since late 1960s

• _{1970s: concentrated at the bottom}

• _{1980s: throughout the distribution}

• _{1990s: concentrated at the top}

2. Striking similarity between men’s and women’s trends...

• _{... except for 1970s}

3. Two-thirds of the increase is residual

• _{virtually 100% residual in the 1970s}

Recap: individual wage inequality

1. Continuous increase since late 1960s

• _{1970s: concentrated at the bottom}

• _{1980s: throughout the distribution}

• _{1990s: concentrated at the top}

2. Striking similarity between men’s and women’s trends...

• _{... except for 1970s}

3. Two-thirds of the increase is residual

• _{virtually 100% residual in the 1970s}

Role of individual labor supply: men

1970 1980 1990 2000 0.2

0.3 0.4 0.5

Variance of Male Log Wages

Year 1970 1980 1990 2000

0 0.1 0.2 0.3

Variance of Male Log Annual Hours

Year

1970 1980 1990 2000 −0.1

0 0.1 0.2

Correl. btw Log Hours and Log Wages

Year 1970 1980 1990 2000

0.4 0.5 0.6 0.7

Variance of Male Log Annual Earnings

Understanding individual earnings inequality

1970 1980 1990 2000 −0.5

0 0.5

Earnings Ranked by Earnings Decile

Year

Log Change

1970 1980 1990 2000 −0.4 −0.2 0 0.2 0.4 0.6

Wage Ranked by Earnings Decile

Year

Log Change

1970 1980 1990 2000 −0.8 −0.6 −0.4 −0.2 0 0.2

Hours Ranked by Earnings Decile

Year

Log Change

1970 1980 1990 2000 4

6 8

10 Unemployment Rate

Recap: men’s earnings inequality

1. Steady increase, until early 1990s

• _{During 1970s-1980s, rise is twice as big as for wages}

2. It reflects rising correlation between wages and hours worked

Recap: men’s earnings inequality

1. Steady increase, until early 1990s

• _{During 1970s-1980s, rise is twice as big as for wages}

2. It reflects rising correlation between wages and hours worked

Var. of log vs. Gini for household earnings

1970 1980 1990 2000 0.5

0.6 0.7 0.8

Variance of Log Equiv. Household Earnings

Year 1970 1980 1990 2000

0.32 0.34 0.36 0.38 0.4

0.42Gini Coefficient of Equiv. Household Earnings

Year

1970 1980 1990 2000 2.5

2.75 3 3.25 3.5

P50−P10 Ratio of Equiv. Household Earnings

Year 1970 1980 1990 2000

1.8 2 2.2 2.4 2.6 2.8

P90−P50 Ratio of Equiv. Household Earnings

Year

Var. of log vs. Gini for household earnings

1970 1980 1990 2000 0.5

0.6 0.7 0.8

Variance of Log Equiv. Household Earnings

Year 1970 1980 1990 2000

0.32 0.34 0.36 0.38 0.4

0.42Gini Coefficient of Equiv. Household Earnings

Year

1970 1980 1990 2000 2.5

2.75 3 3.25 3.5

P50−P10 Ratio of Equiv. Household Earnings

Year 1970 1980 1990 2000

1.8 2 2.2 2.4 2.6 2.8

P90−P50 Ratio of Equiv. Household Earnings

Year

Var. of log vs. Gini for household earnings

1970 1980 1990 2000 0.5

0.6 0.7 0.8

Variance of Log Equiv. Household Earnings

Year 1970 1980 1990 2000

0.32 0.34 0.36 0.38 0.4

0.42Gini Coefficient of Equiv. Household Earnings

Year

1970 1980 1990 2000 2.5

2.75 3 3.25 3.5

P50−P10 Ratio of Equiv. Household Earnings

Year 1970 1980 1990 2000

1.8 2 2.2 2.4 2.6 2.8

P90−P50 Ratio of Equiv. Household Earnings

Year

Cyclicality of household earnings inequality

1970 1975 1980 1985 1990 1995 2000 2005 −0.3

−0.2 −0.1 0 0.1 0.2 0.3 0.4 0.5 0.6

Equivalized Household Earnings

Year

Log (normalized to 0 in 1967)

CPS Percentiles

P5 P10 P25 P50 P95

P90 P75

Long-run impact of recessions on inequality

1970 1975 1980 1985 1990 1995 2000 2005 0

0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45

Household Earnings

Year

Log (normalized to 0 in 1967) 90−10 Log Differential

Role of household labor supply

1970 1980 1990 2000 0.45

0.5 0.55 0.6 0.65 0.7 0.75 0.8

Variance of Log Earnings

Year 1970 1980 1990 2000

0.32 0.34 0.36 0.38 0.4 0.42 0.44 0.46

Gini of Household Earnings

Year

Main Earner Household Main Earner

Household

Forces impacting scope for within-household insurance

1970 1980 1990 2000 0.4

0.5 0.6 0.7 0.8

0.9 Var. of Log Household Earnings

Year

Singles Married

1970 1980 1990 2000 0.55

0.6 0.65 0.7 0.75

0.8 Fraction of Married Households

Year

1970 1980 1990 2000 0.55 0.6 0.65 0.7 0.75 0.8

Fraction of Two−Earner Married Households

Year

1970 1980 1990 2000 0.1

0.2 0.3 0.4

Within Married Household Correlation of Log Earnings

Recap: income pooling within the household

• _{Married households do significant income pooling}

I but... increasingly assortative matching

• _{Women’s labor force participation increases potential role of}

within-family insurance

I but... increasing fraction of single households

Recap: income pooling within the household

• _{Married households do significant income pooling}

I but... increasingly assortative matching

• _{Women’s labor force participation increases potential role of}

within-family insurance

I but... increasing fraction of single households

Recap: income pooling within the household

• _{Married households do significant income pooling}

I but... increasingly assortative matching

• _{Women’s labor force participation increases potential role of}

within-family insurance

I but... increasing fraction of single households

Role of private transfers

1970 1980 1990 2000 0.5

0.55 0.6 0.65 0.7 0.75 0.8 0.85

Year Variance of Log

1970 1980 1990 2000 0.33

0.34 0.35 0.36 0.37 0.38 0.39 0.4 0.41 0.42 0.43

Year Gini

Household Earnings + Private Transfers

Role of private transfers

1970 1980 1990 2000 0.5

0.55 0.6 0.65 0.7 0.75 0.8 0.85

Year Variance of Log

1970 1980 1990 2000 0.33

0.34 0.35 0.36 0.37 0.38 0.39 0.4 0.41 0.42 0.43

Year Gini

Household Earnings + Private Transfers

Role of asset income

1970 1980 1990 2000

0.45 0.5 0.55 0.6 0.65 0.7 0.75 0.8

Year

Variance of Log

1970 1980 1990 2000

0.34 0.36 0.38 0.4 0.42 0.44

Year Gini

HH Earn. + Priv. Transf. + Asset Income

Role of asset income

1970 1980 1990 2000

0.45 0.5 0.55 0.6 0.65 0.7 0.75 0.8

Year

Variance of Log

1970 1980 1990 2000

0.34 0.36 0.38 0.4 0.42 0.44

Year Gini

HH Earn. + Priv. Transf. + Asset Income

Role of public transfers

1970 1975 1980 1985 1990 1995 2000 2005 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0.75 Year Variance of Log

Pre−Govt. Income + Govt. Benefits

1970 1975 1980 1985 1990 1995 2000 2005 0.33 0.34 0.35 0.36 0.37 0.38 0.39 0.4 0.41 0.42 0.43 Year Gini

• _{Public transfers greatly reduce level of inequality at the bottom}

• _{Expansion in 1970s, tightening after 1994}

Role of public transfers

1970 1975 1980 1985 1990 1995 2000 2005 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0.75 Year Variance of Log

Pre−Govt. Income + Govt. Benefits

1970 1975 1980 1985 1990 1995 2000 2005 0.33 0.34 0.35 0.36 0.37 0.38 0.39 0.4 0.41 0.42 0.43 Year Gini

• _{Public transfers greatly reduce level of inequality at the bottom}

• _{Expansion in 1970s, tightening after 1994}

Role of public transfers

1970 1975 1980 1985 1990 1995 2000 2005 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0.75 Year Variance of Log

Pre−Govt. Income + Govt. Benefits

1970 1975 1980 1985 1990 1995 2000 2005 0.33 0.34 0.35 0.36 0.37 0.38 0.39 0.4 0.41 0.42 0.43 Year Gini

• _{Public transfers greatly reduce level of inequality at the bottom}

• _{Expansion in 1970s, tightening after 1994}

Role of public transfers

1970 1975 1980 1985 1990 1995 2000 2005 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0.75 Year Variance of Log

Pre−Govt. Income + Govt. Benefits

1970 1975 1980 1985 1990 1995 2000 2005 0.33 0.34 0.35 0.36 0.37 0.38 0.39 0.4 0.41 0.42 0.43 Year Gini

• _{Public transfers greatly reduce level of inequality at the bottom}

• _{Expansion in 1970s, tightening after 1994}

Role of tax system

19701975198019851990199520002005 0.3

0.35 0.4 0.45 0.5 0.55 0.6

Year Variance of Log

1970 1975 1980 1985 1990 1995 2000 2005 0.31

0.32 0.33 0.34 0.35 0.36 0.37 0.38 0.39 0.4 0.41

Year Gini

Pre−Tax. Income Disp. Income

REP DEM REP REP DEM REP

• _{Taxes greatly reduce level of inequality throughout the distribution}

Role of tax system

19701975198019851990199520002005 0.3

0.35 0.4 0.45 0.5 0.55 0.6

Year Variance of Log

1970 1975 1980 1985 1990 1995 2000 2005 0.31

0.32 0.33 0.34 0.35 0.36 0.37 0.38 0.39 0.4 0.41

Year Gini

Pre−Tax. Income Disp. Income

REP DEM REP REP DEM REP

• _{Taxes greatly reduce level of inequality throughout the distribution}

Recap: household income dispersion

• _{Private transfers somewhat reduce inequality at bottom (small)}

• _{Asset income increases inequality at the top, but it is} underestimated

• _{Public transfers play a significant role for redistribution and} stabilization – less since 1994

Macro facts in micro data: CEX

1980 1985 1990 1995 2000 2005 9.6 9.7 9.8 9.9 10 10.1 10.2 10.3 Income Per−capita Year

Log scale (2003 $)

NIPA CEX

1980 1985 1990 1995 2000 2005 7.5 7.6 7.7 7.8 7.9 8 8.1 8.2

8.3 Food Consumption Per−capita

Year

Log scale (2003 $)

NIPA CEX PSID

Macro facts in micro data: CEX

1980 1985 1990 1995 2000 2005 9.6 9.7 9.8 9.9 10 10.1 10.2 10.3 Income Per−capita Year

Log scale (2003 $)

NIPA CEX

1980 1985 1990 1995 2000 2005 7.5 7.6 7.7 7.8 7.9 8 8.1 8.2

8.3 Food Consumption Per−capita

Year

Log scale (2003 $)

NIPA CEX PSID

Comparison CPS-CEX: household earnings

1970 1980 1990 2000

−0.2 −0.15 −0.1 −0.05 0 0.05 0.1

Variance of Log

Year

Series demeaned

CPS CEX

1970 1980 1990 2000

−0.04 −0.03 −0.02 −0.01 0 0.01 0.02 0.03 0.04

Gini

Year

Series demeaned

CPS CEX

Comparison CPS-CEX: disposable income

1970 1980 1990 2000 −0.1

−0.05 0 0.05

Variance of Log

Year

Series demeaned

CPS CEX

1970 1980 1990 2000 −0.04

−0.03 −0.02 −0.01 0 0.01 0.02 0.03

Gini

Year

Series demeaned

CPS CEX

From disposable income to consumption

1980 1990 2000

0.25 0.3 0.35 0.4 0.45 0.5 0.55

Variance

Year 1980 1990 2000

0.28 0.3 0.32 0.34 0.36 0.38

0.4 Gini Coefficient

Year Disp. Income

Nond. Cons.

Contrasting income smoothing at top and bottom

19801 1985 1990 1995 2000 2005 1.5

2 2.5 3 3.5 4 4.5 5 5.5 6

P50−P10 (ranked by earnings)

19801 1985 1990 1995 2000 2005 1.5

2 2.5 3 3.5 4 4.5 5 5.5 6

P90−P50 (ranked by earnings)

Saving and borrowing

• _{Difference between income and consumption inequality: saving}

and borrowing

• _{Scope for self-insurance via saving/borrowing depends on}

persistence of shocks

• _{Estimating persistence requires panel data: PSID}

I Permanent-transitory model with non-stationarity in

Estimation of wage dynamics from PSID

• _{Focus on log male wages because closest definition to}

“exogenous endowments”

• _{Permanent-transitory model for (residual) wage dynamics}

w_i,a,t = _zi,a,t + _εi,a,t

z_i,a,t = _{zi,a−1,t−1} + _ηi,a,t

• _{Time-varying variances of the three components: structural} parameters are {σ_εt, σ_ηt, σ_z0,t}

T t₌₁

• _{Minimum distance estimation:}

1. moments in first-differences

Comparison CPS-CEX-PSID: male wages

1970 1980 1990 2000 −0.1

−0.05 0 0.05 0.1 0.15

Var. of Log

Year

Series demeaned

1970 1980 1990 2000 −0.04

−0.02 0 0.02 0.04 0.06 0.08

Gini

Year

Series demeaned

CPS PSID CEX

CPS PSID CEX

Results

1970 1975 1980 1985 1990 1995 0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04 0.045 0.05

Variance of Permanent Innovation

Year 1970 1975 1980 1985 1990 1995

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

Wage Variance Decomposition

Year Levels

Diff.

Total Var

Transitory Var: Levels Transitory Var: Diff.

Fit of moments in first differences

1970 1975 1980 1985 1990 1995 0.1

0.15 0.2 0.25 0.3

Variance of Wage Growth

Year Data & Diff. Levels

1970 1975 1980 1985 1990 1995 −0.15

−0.1 −0.05 0 0.05

Covariance of Wage Growth at Lag 1

Year Data & Diff. Levels

Fit of moments in levels

1970 1975 1980 1985 1990 1995 0.2 0.4 0.6 0.8 1 1.2

Variance of Wages (1969 Cohort)

Year Data

Levels Diff.

1970 1975 1980 1985 1990 1995 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Wage Correlation between age 25 and age t (1969 Cohort)

Year

Data Levels Diff.

• _{Estimation in differences spectacularly fails to match these}

Recap: wage dynamics

• _{Misspecification of the permanent-transitory model}

• _{Estimates in levels more reliable (misspecification error less}

dramatic)

• _{What is the right stochastic process for log wages?}

Autocovariance function of log wages

1970 1975 1980 1985 1990 1995 0.02

0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18

0.2 Autocovariance of Log Wages

Year

1969

1976

Net worth-income ratios by income deciles (SCF)

1990 1995 2000 2005 1.6 1.8 2 2.2 2.4 2.6 2.8 3 3.2 3.4

Bottom Income Deciles

Year D1 D2 D3 D4 D5

1990 1995 2000 2005 1.6 1.8 2 2.2 2.4 2.6 2.8 3 3.2 3.4

Top Income Deciles

Year D6 D7 D8 D9 D10

Conclusions

• _{Difficult to generalize about inequality without asking: Inequality in}

what? Inequality measured how?

• _{Difficult to understand evolution of inequality or its implications for}

welfare without modeling explicitly choices/institutions that

mediate between wages and consumption / leisure

• _{Inequality increases permanently in recessions ⇒ unified theory}

of business cycles and long-run trends for inequality

• _{Permanent-transitory model misspecified, and bias enormous}

when estimated in first-differences

• _{Rise in consumption inequality smaller than rise in income}

Conclusions

• _{Difficult to generalize about inequality without asking: Inequality in}

what? Inequality measured how?

• _{Difficult to understand evolution of inequality or its implications for}

welfare without modeling explicitly choices/institutions that

mediate between wages and consumption / leisure

• _{Inequality increases permanently in recessions ⇒ unified theory}

of business cycles and long-run trends for inequality

• _{Permanent-transitory model misspecified, and bias enormous}

when estimated in first-differences

• _{Rise in consumption inequality smaller than rise in income}

Conclusions

• _{Difficult to generalize about inequality without asking: Inequality in}

what? Inequality measured how?

• _{Difficult to understand evolution of inequality or its implications for}

welfare without modeling explicitly choices/institutions that

mediate between wages and consumption / leisure

• _{Inequality increases permanently in recessions ⇒ unified theory}

of business cycles and long-run trends for inequality

• _{Permanent-transitory model misspecified, and bias enormous}

when estimated in first-differences

• _{Rise in consumption inequality smaller than rise in income}

Conclusions

• _{Difficult to generalize about inequality without asking: Inequality in}

what? Inequality measured how?

• _{Difficult to understand evolution of inequality or its implications for}

welfare without modeling explicitly choices/institutions that

mediate between wages and consumption / leisure

• _{Inequality increases permanently in recessions ⇒ unified theory}

of business cycles and long-run trends for inequality

• _{Permanent-transitory model misspecified, and bias enormous}

when estimated in first-differences

• _{Rise in consumption inequality smaller than rise in income}