Data to Examine Consumption Poverty and I Inequality in the U.S.: - - PowerPoint PPT Presentation

Data to Examine Consumption Poverty and I lit i th U S 1960 2008 Inequality in the U.S.: 1960-2008 CE Survey Data Users’ Needs Forum y June 22, 2010

Bruce D. Meyer University of Chicago and NBER Based on work with J X S lli James X. Sullivan University of Notre Dame

• I. Introduction

 Question: How have poverty and inequality

changed over the past five decades? changed over the past five decades?

 We look at both income and consumption based

measures of well-being measures of well being

 We emphasize the importance of measurement

issues for understanding poverty and inequality patterns

 We refine the methods to convert expenditure

d t i t ti d t data into consumption data

• I. Income v. Consumption: Conceptual

 Meyer and Sullivan (2003, 2007)

C t l i f ti

 Conceptual issues favor consumption.

 Permanent income (Cutler and Katz 1991;

Poterba 1991) Poterba 1991)

 Public and private insurance  Access to credit  Access to credit

• II. Income v. Consumption: Data Quality

 Reporting issues are split between income and

consumption consumption

 Ease of reporting v. sensitive topics  Nonresponse  Nonresponse  Under-reporting

 Low percentiles of expenditures greatly exceed  Low percentiles of expenditures greatly exceed

low percentiles of income

Nonresponse Rates

T bl 5

Survey Nonresponse Imputation Rates

Table 5 Survey Nonresponse and Imputations Rates, CPS and CE Interview Survey, 1993-2007

CPS- ASEC/ADF CE Survey CPS-ASEC/ADF CE Survey Pre-tax Money Income After-tax Incomea After-tax Incomeb Total E pendit res Income Incomea Incomeb Expenditures (1) (2) (3) (4) (5) (6) 1993 0.154 0.156 0.153 0.252 0.444 0.104 1994 0.154 0.167 0.156 0.259 0.456 0.104 1995 0 154 0 194 0 180 0 295 0 496 0 104 1995 0.154 0.194 0.180 0.295 0.496 0.104 1996 0.157 0.211 0.190 0.316 0.518 0.125 1997 0.144 0.199 0.204 0.344 0.548 0.128 1998 0.161 0.201 0.219 0.375 0.574 0.129 1999 0.144 0.202 0.217 0.382 0.589 0.149 1999 0.144 0.202 0.217 0.382 0.589 0.149 2000 0.159 0.200 0.248 0.428 0.626 0.154 2001 0.162 0.220 0.255 0.434 0.628 0.163 2002 0.150 0.220 0.262 0.422 0.604 0.179 2003 0.160 0.214 0.254 0.389 0.565 0.184 2004 0.174 0.240 0.256 0.401 0.583 0.167 2005 0.167 0.255 0.239 0.373 0.557 0.194 2006 0.171 0.234 0.252 0.403 0.592 0.228 2007 0.156 0.262 0.251 0.398 0.591 0.130

Share of Dollars Imputed, CPS

0 4 0.4 0.3 0.2 0.1 AFDC/TANF Food Stamps OASDI SSI

1 2 3 4 5 6 7 8 9 1 2 3 4 5 6 7 8

UI WC

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Meyer, Mok, and Sullivan (2009)

Reporting Rates for Dollar Amounts of Transfer Programs, CPS

1 0 6 0.8 0 4 0.6 0.2 0.4 AFDC/TANF Food Stamps SSI

1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005

Ratios of CE Expenditure Measures to National Aggregates 1980-2008

1.1 1.2

Food at home Food away from home Rent plus Utilities Gasoline and motor oil Alcoholic beverages Transportation Tobacco Clothing

Ratios of CE Expenditure Measures to National Aggregates, 1980 2008

0.8 0.9 1

• 0.6

0.7 CE/NIPA Rati 0 3 0.4 0.5 C 0.1 0.2 0.3 1980 1984 1987 1992 1994 1997 2002 2004 2007 2008 1980 1984 1987 1992 1994 1997 2002 2004 2007 2008

• II. Income v. Consumption: Data Quality

 Refinement to income tend to move it toward

consumption (alternative poverty housing consumption (alternative poverty, housing, MOOP, etc.)

 CE provides much info to approximate  CE provides much info to approximate

consumption that is missing in CPS (housing and vehicle characteristics MOOP) and vehicle characteristics, MOOP).

 Consumption is more strongly associated with

• ther measures of well-being
• ther measures of well-being

• II. CPS Income Data

 Current Population Survey – ASEC/ADF

1963 2008

 1963-2008  Taxes calculated using TAXSIM  Census has imputed noncash benefits since 1980  Census has imputed noncash benefits since 1980.  These imputed benefits have some drawbacks

• III. CE Consumption and Income Data

 Consumer Expenditure (CE) Interview

Component Component

 1960/61, 1972/73, 1980-1981, 1984-2008  1982-1983 only urban consumers; also because  1982 1983 only urban consumers; also because

summary measures of aggregated expenditures are not provided it makes it difficult to use

 Recent improved timeliness of data releases is

welcome; talk of speeding up releases further?

• III. CE Consumption and Income Data

 Consumer Expenditure (CE) Interview

Component raw data Component raw data

 Mostly use family files: summary expenditures  Also use detailed expenditure files: vehicles debt  Also use detailed expenditure files: vehicles, debt,

Medicaid enrollment, HI coverage

 And member files: exact age composition of CU  And member files: exact age composition of CU

• III. CE Consumption Data

 We modify expenditures to approach consumption

 We make many improvements in the measurement of  We make many improvements in the measurement of

consumption at the bottom

 Rental equivalent for owner-occupied housing

W h k d th t it l t ibl t t d h l



We checked that it relates sensibly to reported home values



Others have related reported home values to sales prices in

• ther datasets.

 Impute value of public/subsidized housing using detailed

housing characteristics



Make adjustment based on PSID info on rental equivalent j q



Adding rental equivalent to survey would be helpful

• III. CE Consumption Data

 Flow value of vehicles (based on more than

350,000 purchase prices) 350,000 purchase prices)

 Use equations to predict purchase price for those

without it

 Complicated set of regressions to determine implicit

prices of vehicle characteristics depending on what information is missing. information is missing.

 Use data to determine depreciation that goes into

flow value

 Validated using NADA data  Unfortunate that make but not model available

beginning in 2006 beginning in 2006.

• III. CE Consumption Data

 Medical care, health insurance

Subtract out MOOP Imputed in CPS in proposed

 Subtract out MOOP. Imputed in CPS in proposed

Supplemental Poverty Measure.

 Use information on Medicaid Medicare and Private  Use information on Medicaid, Medicare, and Private

HI coverage.

• III. General Issues in CE

 We use annualized quarterly data

W h d t t f d

 We have compared one quarter to four, and

there is some understatement of dispersion inherent in relying on one quarter inherent in relying on one quarter.

 This problem is likely to be much more severe

if one relies on two weeks of expenditures to if one relies on two weeks of expenditures to infer consumption in the diary data. C i f k f di d t t t

 Comparisons of one week of diary data to two

weeks shows differences in the distribution of expenditures expenditures.

• III. CE Income Data

 We use TAXSIM as reported income tax

payments are very different from estimated payments are very different from estimated taxes.

 NBER willing to supply code to implement in CE  NBER willing to supply code to implement in CE

 State IDs missing for 16 percent of the sample

we used from the 1990s in our AER paper we used from the 1990s in our AER paper.

 Imputation of income began in 2005.

C ld ili ti f i d

 Could reconciliation of income and

consumption be brought back?

Figure 1: Real After-tax Income Plus Food Stamps at Various Percentiles, 1980-2008, CPS & CE Survey

16000 5th Percentile CPS 10th Percentile CPS 25th Percentile CPS 5th Percentile CE Survey 10th Percentile CE Survey 25th Percentile CE Survey 12000 14000 25th Percentile CE Survey 8000 10000

2005 $

4000 6000 2000

80 82 84 86 88 90 92 94 96 98 00 02 04 06 08 198 198 198 198 198 199 199 199 199 199 200 200 200 200 200

Figrue 2: Real After-tax Income Plus Food Stamps at Various Percentiles, 1980-2008, CPS & CE Survey

70000 50th Percentile CPS 75th Percentile CPS 90th Percentile CPS 50th P til CE S 50000 60000 50th Percentile CE Survey 75th Percentile CE Survey 90th Percentile CE Survey 30000 40000

2005 $

20000 30000 10000

80 82 84 86 88 90 92 94 96 98 00 02 04 06 08 198 198 198 198 198 199 199 199 199 199 200 200 200 200 200

• VI. Core Consumption

 We look at a subset of total consumption that

includes important spending categories that tend to p p g g be well reported:

 Housing  Food at home  Food at home  Transportation

 For those near the poverty line, Core is 80% of non-

di l i i l 1980 medical consumption in early 1980s

 Information is needed to compare CE totals to NIPA

aggregates Knowing which categories of

• aggregates. Knowing which categories of

expenditures line up well with NIPA would be

• helpful. An earlier Garner et al. paper did this, but

NIPA categories have changed NIPA categories have changed.

• VII. Predicted Consumption

 We regress total consumption measures on a

cubic in core consumption, a cubic in the age p g

• f the head, education of the head dummies,

family type dummies, and race dummies.

 We use data from 1980 81 because total  We use data from 1980-81, because total

expenditures in the CE Survey compare more favorably to NIPA in the early 1980s than in recent years.

 Coefficients from this regression are then

used to predict a value of the consumption used to predict a value of the consumption measures for each consumer unit in all years.

 R-squared = 0.72

• VIII. Results

 Do income and consumption poverty and

inequality differ? inequality differ?

Summary of Changes in Income and Consumption Inequality

0.3 0.25 Log After-Tax Income 0.15 0.2 Ratio Log Consumption Excluding HI 0.1 0.15 e in 90/10 R 0.05 Change

• 0.05

1963-1972 1972-1980 1980-1990 1990-2000 2000-2008

• 0.1

Figure 4: Consumption Inequality 1961-2008

6 5 6.0 6.5 5.0 5.5 4.0 4.5

90/10 Ratio

3 0 3.5

9

After-tax Money Income (90/10) 2.5 3.0 After-tax Money Income (90/10) Expenditures (90/10) Consumption (90/10) Consumption Excluding HI (90/10) Core Consumption (90/10) 2.0

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47

• XI. Conclusions

 Consumption data extremely useful to look at

measures of well being measures of well-being.

 Consumption poverty and inequality are quite

different from their income cousins different from their income cousins.

• XI. Conclusions: Data Suggestions

 Recent improvements helpful

 Imputation of income  Improved timeliness of data release

 Opportunities for improvement

 Information on categories compatible with NIPA or

more regular comparisons to NIPA totals

 Suppression of vehicle model starting in 2006  Suppression of vehicle model starting in 2006  High fraction of units with suppressed or recoded

state id

 Make data available at RDC?  Use TAXSIM?  Reconcile Y and Expenditures?

• IX. Comparisons Across Data Sets

 How does consumption inequality in the CE

Survey compare to that in the PSID? Survey compare to that in the PSID?

 Food and housing

How does income inequality in the CPS

 How does income inequality in the CPS

compare to that in the PSID?

 Pre tax money income  Pre-tax money income

Consumption Inequality, CPS and PSID 1980-2007

0 14 0 10 0.12 0.14 0.06 0.08 0.10

1980

0.02 0.04 0.06

n 90-10 Since

• 0.02

0.00

1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 Change in

• 0.06
• 0.04

Food at home & housing consumption (CE Survey) Food at home & housing consumption (PSID)

• 0.08

Pre-Tax Money Income Inequality, CPS and PSID 1967-2006

0 4 0.3 0.4 Pre-tax Money Income (CPS) Pre-tax Money Income (PSID) 0.2

1980

y ( ) 0.1

n 90-10 Since

0.0

967 969 971 973 975 977 979 981 983 985 987 989 991 993 995 997 999 001 003 005 007 Change in

• 0.1

19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 20 20 20 20

• 0.2

September 6, 2007 | Issue 43•37 In The Know: Are America's Rich Falling Behind The Super-Rich? Panelists discuss a new study showing the gap between the wealthy and the absurdly wealthy is widening, and how we can help the merely rich catch up merely rich catch up.

• I. Introduction

 Some previous work has examined income

and/or consumption poverty or inequality and/or consumption poverty or inequality

 P60 Series Reports (annual)  Gottschalk and Danziger (2005)  Gottschalk and Danziger (2005)  Burkhauser et al. (various)  Johnson Smeeding and Torrey (2005)  Johnson, Smeeding, and Torrey (2005)  Krueger and Perri (2006)  Heathcote Perri and Violante (2010)  Heathcote, Perri, and Violante (2010)  Attanasio, Battistin and Ichimura (2004)

0 25

Figure 2: Real Changes in Consumption at Various Percentiles, 1972-2008

0.20 0.25

5th Percentile Consumption Excluding HI 10th Percentile Consumption Excluding HI 90th Percentile Consumption Excluding HI

0.15

to 1980 90th Percentile Consumption Excluding HI 25th Percentile Consumption Excluding HI 50th Percentile Consumption Excluding HI 75th Percentile Consumption Excluding HI

0.10

nce Relative t

0.00 0.05

2 4 6 8 2 4 6 8 2 4 6 8 2 4 6 8 Log Differen

• 0.05

1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008

• 0.10

Figure 5: Consumption Inequality 1961-2008

6 5 6.0 6.5 Consumption Excluding HI (90/10) 5.0 5.5 Consumption Excluding HI (90/10) Predicted Consumption Excluding HI (90/10) 4.0 4.5

90/10 Ratio

3.0 3.5 2 0 2.5 2.0

1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007