Race and Economic Well-Being in the United States Jean-Felix - - PowerPoint PPT Presentation

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Race and Economic Well-Being in the United States Jean-Felix - - PowerPoint PPT Presentation

May 06, 2023 106 likes •430 views

Race and Economic Well-Being in the United States Jean-Felix Brouillette, Charles I. Jones and Peter J. Klenow November 4, 2020 Race and economic well-being Large and persistent racial differences in economic outcomes in the U.S.: Earnings:

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Race and Economic Well-Being in the United States

Jean-Felix Brouillette, Charles I. Jones and Peter J. Klenow November 4, 2020

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Race and economic well-being

Large and persistent racial differences in economic outcomes in the U.S.:

  • Earnings: Chetty, Hendren, Jones and Porter (2020)
  • Mortality and morbidity: Case and Deaton (2015) and Chetty et al. (2016)

Studied separately, but likely correlated:

  • How large is the racial gap in overall living standards?
  • How has it changed over time?

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Methodology

Build on the expected utility framework of Jones and Klenow (2016) Construct a consumption-equivalent welfare statistic:

  • Life expectancy
  • Consumption
  • Consumption inequality
  • Leisure
  • Leisure inequality

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Preview

  • Black welfare started at 49% of White welfare in 1984 and rose to 69% by 2018
  • Progress coming evenly from rising relative consumption and life expectancy
  • Welfare growth has slowed markedly in recent years
  • COVID-19 mortality has reversed a decade’s worth of progress

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Theory

Expected utility for individual of race i: Ui = E

100

∑

a=0

Saiu (Cai, Lai) where Sai = survival rate, Cai = consumption and Lai = leisure. Expected utility if consumption is multiplied by factor λ at each age: Ui (λ) = E

100

∑

a=0

Saiu (λCai, Lai) .

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Theory

How to adjust consumption of White Americans for them to be indifferent between living their lives in the conditions faced by Black Americans and their own? UW (λEV) = UB (1) Analogously, how to adjust consumption of Black Americans for them to reach the same indifference point? UW (1) = UB (1/λCV) Our consumption-equivalent welfare statistic averages λEV and λCV

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Data

Welfare calculation requires data on mortality, consumption and leisure:

  • Period: 1984 to 2018
  • Groups: Black and White Americans
  • Mortality: Centers for Disease Control and Prevention (CDC)
  • Consumption: Consumer Expenditure Survey (CEX)
  • Leisure: Current Population Survey (CPS)

CDC and CPS data go back as far as 1970, but annual CEX only starts in 1984

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Consumer Expenditure Survey

  • Rotating panel of 20,000 households, interviewed for up to four quarters
  • We aggregate expenditures on hundreds of items
  • Approximate the flow services of durable goods when possible
  • Divide consumption evenly within households
  • Re-scale to reflect real non-health NIPA consumption per capita each year

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Per capita consumption by race

1985 1990 1995 2000 2005 2010 2015

Year

40 60 80 100

Consumption White Black

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Consumption age profile in 2018

20 40 60 80 100

Age

9.8 10.0 10.2 10.4 10.6 10.8

Log consumption White Black

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Current Population Survey

  • Over 60,000 households interviewed for up to 8 months
  • Detailed information on employment, occupation and income
  • Leisure = (5,840 – hours worked in the year)/5,840
  • 5,840 = 16 hours per day × 365 days
  • Divide hours worked equally among 25 to 64 year olds within households
  • Consistent with leisure gender gap found by Aguiar and Hurst (2007)

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Leisure by race

1985 1990 1995 2000 2005 2010 2015

Year

0.80 0.82 0.84 0.86 0.88 0.90

Leisure White Black

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Leisure age profile in 2018

20 40 60 80 100

Age

0.70 0.75 0.80 0.85 0.90 0.95 1.00

Leisure White Black

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Centers for Disease Control and Prevention (CDC)

  • Universe of individual death records
  • Detailed information on the deceased
  • Population at risk: U.S. Census Bureau’s intercensal population estimates
  • Probability of surviving up to age a:

Sa =

a

∏

s=0

(1 − Ms) where Ms = Ds/Ps

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Life expectancy by race

1985 1990 1995 2000 2005 2010 2015

Year

70 72 74 76 78 80

Life expectancy White Black

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Life expectancy by race and gender

1985 1990 1995 2000 2005 2010 2015

Year

64 66 68 70 72 74 76 78 80 82

Life expectancy White male Black male White female Black female

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Survival age profile in 2018

20 40 60 80 100

Age

0.0 0.2 0.4 0.6 0.8 1.0

Survival rate White Black

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Assumptions and definitions

Assume additively separable flow utility: u (C, L) = u + log (C) + v (L) where v (L) = − θǫ 1 + ǫ × (1 − L)

1+ǫ ǫ

Define average sub-utility from consumption and leisure as: AUCi ≡ ∑

a

SaWE [log (Cai)] /LEW and AULi ≡ ∑

a

SaWE [v (Lai)] /LEW Define sub-utility from average consumption and leisure as: UACi ≡ log

  • ∑

a

SaWE [Cai] /LEW

  • and

UALi ≡ v

  • ∑

a

SaWE [Lai] /LEW

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Decomposition

log (λCV) = ∑

a

(SaB − SaW) E [u (CaB, LaB)] /LEW Life expectancy + UACB − UACW Consumption + UALB − UALW Leisure + (AUCB − UACB) − (AUCW − UACW) Consumption inequality + (AULB − UALB) − (AULW − UALW) Leisure inequality

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Calibration

Parameter Symbol Value Source Frisch elasticity ǫ 1.0 Hall (2009) and Chetty et al. (2012) Leisure utility weight θ 14.2 Static first-order condition Flow utility intercept u 6.4 VSL of $7.4M in 2006 (EPA)

  • Intercept: one year of life is worth 6.4 years of consumption in 2018

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Black relative to White welfare

1985 1990 1995 2000 2005 2010 2015

Year

0.4 0.5 0.6 0.7 0.8

λ

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Welfare and income gap

1985 1990 1995 2000 2005 2010 2015

Year

0.4 0.5 0.6 0.7 0.8

Relative welfare and income Welfare Income

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Welfare and wealth gap

1985 1990 1995 2000 2005 2010 2015

Year

0.1 0.2 0.4 0.6 0.8

Relative welfare and wealth Welfare Wealth

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Welfare gap decomposition

1985 1990 1995 2000 2005 2010 2015

Year

0.4 0.6 0.8 1.0

λ Leisure Inequality Life expectancy Consumption

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Welfare gap decomposition

log (λ) LE C σ (C) L σ (L) 2018

  • 0.37
  • 0.26
  • 0.17

0.02 0.03 0.00 2000

  • 0.61
  • 0.40
  • 0.27

0.01 0.04 0.01 1984

  • 0.71
  • 0.38
  • 0.40
  • 0.01

0.05 0.02

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Welfare growth between 1984 and 2018

Welfare Income LE C σ (C) L σ (L) Black 3.35 2.40 1.17 2.48

  • 0.04
  • 0.15
  • 0.12

White 2.28 1.59 0.76 1.84

  • 0.12
  • 0.11
  • 0.08

Gap 1.06 0.80 0.41 0.65 0.08

  • 0.04
  • 0.04

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Cumulative welfare growth

1985 1990 1995 2000 2005 2010 2015

Year

1.0 1.5 2.0 2.5 3.0 3.5

λ White Black

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COVID-19 welfare statistics

Deaths per thousand Age of victims Years of life lost per victim Group welfare loss (%) Black 1.04 71.7 15.0 11.1 White 0.57 80.1 10.2 3.7

Note: As of October 24, 2020, the CDC reports a total of 212,328 COVID-19 deaths.

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Welfare gap with COVID-19 mortality

1985 1990 1995 2000 2005 2010 2015

Year

0.4 0.5 0.6 0.7 0.8

λ

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Summary

  • Black welfare started at 49% of White welfare in 1984 and rose to 69% by 2018
  • Progress coming evenly from rising relative life expectancy and consumption
  • Welfare growth has slowed markedly in recent years
  • COVID-19 mortality has reversed a decade’s worth of progress

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Work in progress...

  • Morbidity
  • Unemployment
  • Incarceration
  • Gender
  • Education
  • Go back farther in time

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