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Research ArticleArticles
Open Access

The Impact of Health on Labor Supply near Retirement

View ORCID ProfileRichard Blundell, View ORCID ProfileJack Britton, View ORCID ProfileMonica Costa Dias and View ORCID ProfileEric French
Journal of Human Resources, January 2023, 58 (1) 282-334; DOI: https://doi.org/10.3368/jhr.58.3.1217-9240R4
Richard Blundell
Richard Blundell is at University College London and the Institute for Fiscal Studies.
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Jack Britton
Jack Britton is at the University of York and the Institute for Fiscal Studies.
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Monica Costa Dias
Monica Costa Dias is at the University of Bristol and the Institute for Fiscal Studies.
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Eric French
Eric French is at the University of Cambridge and the Institute for Fiscal Studies.
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Article Figures & Data

Figures

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  • Figure 1
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    Figure 1

    ELSA and HRS Education Groups by Birth Year for Men

  • Figure 2
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    Figure 2

    ELSA and HRS Education Groups by Birth Year for Women

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    Figure 3

    ELSA Employment on Age, by Gender and Education

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    Figure 4

    Prevalence of Arthritis by Age, Gender, and Education

    Notes: MA(3) indicates a three-year moving average, and FE indicates fixed-effects estimates.

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    Figure 5

    Single Subjective Health Index by Age, Gender, and Education

    Notes: MA(3) indicates a three-year moving average, and FE indicates fixed-effects estimates.

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    Figure 6

    Cognition Index by Age, Gender, and Education

    Notes: MA(3) indicates a three-year moving average, and FE indicates fixed-effects estimates.

Tables

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    Table 1

    ELSA and HRS Years and Sample Sizes

    YearELSAHRS
    WaveSample SizeWaveSample Size
    1996 3 10,215
    1998 4 13,369
    2000 5 11,996
    20021 8,008 6 10,724
    20042 6,104 7 12,126
    20063 6,403 8 10,618
    20084 7,426 9  9,264
    20105 6,62010 13,156
    20126 6,83411 11,805
    Total41,39511103,273
    • Notes: Sample sizes for individuals 50–70 years old only. Total row gives total number of observations, meaning some individuals appear multiple times.

    • View popup
    Table 2

    Objective Health Variables, Averages by Gender

    VariableELSAHRS
    MenWomenMenWomen
    Cancer0.030.030.080.11
    Diabetes0.090.060.190.17
    Sight0.020.020.040.05
    Hearing0.050.020.060.02
    Blood pressure0.300.260.500.50
    Arthritis0.230.340.440.57
    Psychiatric0.050.080.120.21
    Lung disease0.040.040.080.10
    Stroke0.020.010.060.04
    Heart attack0.030.010.020.01
    N18,91322,48244,49958,764
    • Notes: Includes individuals aged 50–70. All variables are binary measures

    • View popup
    Table 3

    Subjective Health Variables, Averages by Gender

    VariableELSAHRS
    MenWomenMenWomen
    Health limits activities0.410.540.540.67
    Self reported health2.612.572.752.78
    Health limits work0.240.250.250.27
    N18,85122,44644,50058,773
    • Notes: Includes individuals aged 50–70. “Health limits activities” and “Health limits work” are binary measures; “Self-reported health” is a five-point categorical variable, where “5” is excellent.

    • View popup
    Table 4

    Cognitive Variables, Averages by Gender

    VariableELSAHRS
    MenWomenMenWomen
    Immediate recall (out of 10)5.966.285.556.02
    Delayed recall (out of 10)4.675.144.485.08
    Difficulty navigating using map0.020.040.060.13
    Difficulty managing money0.020.010.040.04
    N18,85122,44844,40158,641
    • Notes: Includes individuals aged 50–70.

    • View popup
    Table 5

    Coefficient Estimates—Employment Regression on Cognition and Subjective Health

    MenWomen
    ELSAHRSELSAHRS
    NoICs
    (1)
    ICs
    (2)
    NoICs
    (3)
    ICs
    (4)
    NoICs
    (5)
    ICs
    (6)
    NoICs
    (7)
    ICs
    (8)
    Panel A: Employment on Subjective Health
    High school dropout0.177***0.085***0.194***0.138***0.128***0.057***0.161***0.127***
    (0.004)(0.006)(0.004)(0.005)(0.005)(0.005)(0.004)(0.004)
    High school0.110***0.049***0.158***0.106***0.115***0.063***0.140***0.109***
    (0.005)(0.005)(0.003)(0.003)(0.004)(0.005)(0.002)(0.003)
    College0.071***0.047***0.096***0.070***0.068***0.044***0.087***0.077***
    (0.007)(0.007)(0.004)(0.004)(0.008)(0.008)(0.004)(0.005)
    Panel B: Employment on Cognition
    High school dropout0.087***0.013*0.085***0.043***0.058***0.013**0.073***0.037***
    (0.006)(0.007)(0.006)(0.007)(0.005)(0.005)(0.005)(0.005)
    High school0.033***0.011**0.067***0.030***0.031***0.0070.061***0.030***
    (0.006)(0.005)(0.003)(0.004)(0.005)(0.005)(0.003)(0.003)
    College0.013*0.0040.049***0.031***0.019**−0.0010.029***0.018***
    (0.007)(0.008)(0.004)(0.005)(0.008)(0.008)(0.005)(0.005)
    Panel C: Employment on Cognition and Subjective Health
    Cognition
    High school dropout0.035***0.0010.044***0.029***0.026***0.0060.034***0.016***
    (0.006)(0.007)(0.006)(0.006)(0.005)(0.005)(0.005)(0.005)
    High school0.009*0.0050.035***0.017***0.008*0.0010.030***0.016***
    (0.005)(0.005)(0.003)(0.003)(0.005)(0.005)(0.003)(0.003)
    College−0.001−0.0020.030***0.021***0.006−0.0060.014***0.009*
    (0.007)(0.008)(0.004)(0.004)(0.008)(0.008)(0.005)(0.005)
    Subjective Health
    High school dropout0.168***0.085***0.185***0.135***0.122***0.056***0.153***0.125***
    (0.005)(0.006)(0.005)(0.005)(0.005)(0.005)(0.004)(0.004)
    High school0.108***0.048***0.151***0.104***0.114***0.063***0.134***0.106***
    (0.005)(0.005)(0.003)(0.003)(0.004)(0.005)(0.002)(0.003)
    College0.071***0.047***0.090***0.067***0.066***0.045***0.084***0.076***
    (0.007)(0.007)(0.004)(0.004)(0.008)(0.008)(0.004)(0.005)
    Sample sizes  4,692  4,692  5,777  5,777  6,957  6,957  9,199  9,199
      6,326  6,326 18,756 18,756  7,911  7,911 29,905 29,905
      3,362  3,362  9,238  9,238  2,759  2,759  9,682  9,682
    • Notes: All estimates include age, age-squared, and wave dummies. ICs stands for initial conditions. These include the initial value of the health and cognition variables included in the regression, as well as initial employment, working experience, wealth, and marital status, and health in childhood. Significance:

    • ↵* p < 0.10,

    • ↵** p < 0.05,

    • ↵*** p < 0.01.

    • View popup
    Table 6

    Share of Employment Decline Explained by Cognition and Subjective Health

    MenWomen
    ELSAHRSELSAHRS
    Panel A: Subjective Health
    High school dropout0.072***0.123***0.045***0.101***
    (0.013)(0.017)(0.007)(0.014)
    High school0.041***0.111***0.047***0.112***
    (0.008)(0.006)(0.009)(0.006)
    College0.040***0.084***0.023***0.077***
    (0.011)(0.010)(0.008)(0.009)
    Panel B: Cognition
    High school dropout0.0090.037***−0.0030.057***
    (0.003)(0.010)(0.003)(0.011)
    High school0.0010.028***−0.0010.033***
    (0.002)(0.004)(0.001)(0.005)
    College−0.0010.034***0.0000.018***
    (0.002)(0.007)(0.001)(0.006)
    Panel C: Cognition and Subjective Health
    High school dropout0.072***0.145***0.043***0.124***
    (0.013)(0.019)(0.008)(0.016)
    High school0.041***0.125***0.047***0.127***
    (0.008)(0.007)(0.009)(0.007)
    College0.040***0.104***0.023***0.085***
    Sample sizes  4,692  5,777  6,957  9,199
      6,326 18,756  7,911 29,905
      3,362  9,238  2,759  9,682
    • Notes: All estimates include age, age-squared, wave dummies, and the full set of initial conditions. Standard errors are bootstrapped with 500 repetitions. Significance:

    • * p < 0.10,

    • ** p < 0.05,

    • ↵*** p < 0.01.

    • View popup
    Table 7

    Percent Differences in the Explained Share of Employment Decline and p-Values for Testing Null of No Differences—Explanatory Value of Adding Cognition

    Percent Differencesp-Values
    MenWomenMenWomen
    ELSA
    (1)
    HRS
    (2)
    ELSA
    (3)
    HRS
    (4)
    ELSA
    (5)
    HRS
    (6)
    ELSA
    (7)
    HRS
    (8)
    High school dropout0.118.1−4.322.10.4990.1890.4390.146
    High school−0.312.7−0.413.40.4960.0780.4950.055
    College1.622.63.210.20.4840.1110.4730.298
    • Notes: Estimates of relative differences in Columns 1–4 compare figures in Panels A and C of Table 6, with Panel A as the baseline. p-values in Columns 5–8 for testing the equality of the same δ estimates.

    • View popup
    Table 8

    Share of Employment Decline Explained by Subjective Health—Various Specifications

    MenWomen
    ELSAHRSELSAHRS
    Panel A: First Principal Component
    High school dropout0.072***0.123***0.045***0.101***
    (0.013)(0.017)(0.007)(0.014)
    High school0.041***0.111***0.047***0.112***
    (0.008)(0.006)(0.009)(0.006)
    College0.040***0.084***0.023***0.077***
    (0.011)(0.010)(0.008)(0.009)
    Panel B: Three Subjective Measures Separately
    High school dropout0.060***0.106***0.033***0.107***
    (0.015)(0.017)(0.009)(0.017)
    High school0.032***0.110***0.039***0.123***
    (0.011)(0.007)(0.008)(0.007)
    College0.0110.080***0.028***0.078***
    (0.013)(0.012)(0.011)(0.010)
    Panel C: Health Limits Work
    High school dropout0.029***0.084***0.014*0.104***
    (0.011)(0.016)(0.007)(0.016)
    High school0.020***0.101***0.020***0.119***
    (0.006)(0.007)(0.006)(0.006)
    College−0.0030.068***0.0030.071***
    (0.007)(0.009)(0.006)(0.009)
    Sample sizes  4,692  5,777  6,957  9,199
      6,326 18,756  7,911  29,905
      3,362  9,238  2,759  9,682
    • Notes: All estimates include age, age-squared, wave dummies, and the full set of initial conditions. Standard errors are bootstrapped with 500 repetitions. Significance:

    • ↵* p < 0.10,

    • ** p < 0.05,

    • ↵*** p < 0.01.

    • View popup
    Table 9

    Percent Differences in the Explained Share of Employment Decline and p-values for Testing Null of No Differences—Explanatory Value of Added Subjective Health Information

    Percent Differencesp-Values
    MenWomenMenWomen
    ELSA
    (1)
    HRS
    (2)
    ELSA
    (3)
    HRS
    (4)
    ELSA
    (5)
    HRS
    (6)
    ELSA
    (7)
    HRS
    (8)
    Panels B vs. A (Three Separate Subjective Measures)
    High school dropout−16.0−13.7−27.55.40.0760.0390.0750.274
    High school−21.1−1.0−16.99.80.1480.4040.1710.001
    College−72.8−5.426.41.50.0010.1830.2310.411
    Panels C vs. A (Health Limits Work)
    High school dropout−58.9−32.1−68.63.00.0000.0020.0000.388
    High school−51.6−8.9−58.46.10.0000.0480.0010.084
    College−106.3−19.6−84.6−8.10.0000.0120.0050.193
    • Notes: Estimates of relative differences in Columns 1–4 compare figures in Panels A–C of Table 8, with Panel A as the baseline. p-values in Columns 5–8 for testing the equality of the same δ estimates.

    • View popup
    Table 10

    Share of Employment Decline Explained by Subjective Health and Cognition— Subjective Health Instrumented Using Objective Health

    MenWomen
    ELSAHRSELSAHRS
    Panel A: Subjective Health
    High school dropout0.086***0.142***0.055***0.136***
    (0.022)(0.024)(0.015)(0.023)
    High school0.053***0.112***0.058***0.134***
    (0.015)(0.011)(0.016)(0.011)
    College0.052***0.132***0.028**0.100***
    (0.019)(0.021)(0.013)(0.018)
    Panel B: Subjective Health and Cognition
    High school dropout0.085***0.158***0.054***0.147***
    (0.022)(0.024)(0.016)(0.022)
    High school0.053***0.122***0.058***0.144***
    (0.014)(0.011)(0.016)(0.011)
    College0.054***0.142***0.029**0.103***
    (0.020)(0.020)(0.014)(0.018)
    Sample sizes  4,692  5,777  6,957  9,199
      6,326 18,756  7,911 29,905
      3,362  9,238  2,759  9,682
    • Notes: All estimates include age, age-squared, wave dummies, and the full set of initial conditions. Standard errors are bootstrapped with 500 repetitions. Significance:

    • * p < 0.10,

    • ↵** p < 0.05,

    • ↵*** p < 0.01.

    • View popup
    Table 11

    Percent Differences in the Explained Share of Employment Decline and p-values for Testing Null of No Differences—Comparing OLS and IV Estimates

    Percent Differencesp-Values
    MenWomenMenWomen
    ELSA
    (1)
    HRS
    (2)
    ELSA
    (3)
    HRS
    (4)
    ELSA
    (5)
    HRS
    (6)
    ELSA
    (7)
    HRS
    (8)
    Panels B vs. A (Three Separate Subjective Measures)
    High school dropout19.615.422.534.50.2940.2720.2800.100
    High school29.81.122.520.10.2470.4620.2840.048
    College31.255.723.029.40.2950.0210.3770.136
    Panels C vs. A (Health Limits Work)
    High school dropout18.89.027.018.80.3000.3420.2630.198
    High school29.6−2.223.213.10.2470.4150.2750.117
    College32.937.322.721.10.2900.0490.3780.201
    • Notes: Estimates of relative differences in Columns 1–4 compare figures in Panels A and C of Table 6 with those in Panels A and B of Table 10, with Table 6 as the baseline. p-values in Columns 5–8 for testing the equality of the same δ estimates.

    • View popup
    Table 12

    Overidentification Test

    MenWomen
    ELSA
    (1)
    HRS
    (2)
    ELSA
    (3)
    HRS
    (4)
    Panel A: Subjective Health
    High school dropout0.2210.2170.1340.001
    High school0.1060.0000.2840.000
    College0.2800.0000.0930.000
    Panel B: Subjective Health, with Cognition
    High school dropout0.2030.2380.1360.001
    High school0.1100.0000.2900.000
    College0.2830.0000.0790.000
    • Notes: Table compares F-statistic to χ2 critical values, giving p-values for the null of no statistical relationship between our objective measures and the IV residuals.

    • View popup
    Table 13

    Share of Employment Decline Explained by Objective Health

    MenWomen
    ELSAHRSELSAHRS
    Panel A: Blood Pressure Only
    High school dropout0.030**0.050***0.0130.053***
    (0.013)(0.013)(0.009)(0.012)
    High school0.0080.023***0.0040.024***
    (0.009)(0.006)(0.007)(0.006)
    College0.0070.034***0.0050.035***
    (0.009)(0.010)(0.010)(0.009)
    Panel B: Add Arthritis, Psychiatric, Lung
    High school dropout0.061***0.102***0.045***0.126***
    (0.017)(0.015)(0.015)(0.017)
    High school0.022*0.061***0.039***0.075***
    (0.012)(0.009)(0.013)(0.009)
    College0.024*0.062***0.0040.056***
    (0.013)(0.014)(0.016)(0.015)
    Panel C: Add Cancer, Diabetes, Stroke, Heart Attack
    High school dropout0.080***0.156***0.068***0.181***
    (0.018)(0.019)(0.017)(0.022)
    High school0.033**0.081***0.039***0.098***
    (0.013)(0.011)(0.013)(0.010)
    College0.038**0.096***0.0120.075***
    (0.015)(0.017)(0.016)(0.016)
    Panel D: Add Sight, Hearing—Full Specification
    High school dropout0.081***0.152***0.067***0.197***
    (0.019)(0.019)(0.018)(0.023)
    High school0.034**0.084***0.038***0.101***
    (0.013)(0.011)(0.013)(0.010)
    College0.038**0.100***0.0170.073***
    (0.015)(0.017)(0.016)(0.017)
    Sample sizes  4,692  5,777  6,957  9,199
      6,326 18,756  7,911  29,905
      3,362  9,238  2,759  9,682
    • Notes: All estimates include age, age-squared, wave dummies, and the full set of initial conditions. Standard errors are bootstrapped with 500 repetitions. Significance:

    • ↵* p < 0.10,

    • ↵** p < 0.05,

    • ↵*** p < 0.01.

    • View popup
    Table 14

    Percent Differences in the Explained Share of Employment Decline and p-values for Testing Null of No Differences—Comparing Subjective and Objective Health Measures

    Percent Differencesp-Values
    MenWomenMenWomen
    ELSA
    (1)
    HRS
    (2)
    ELSA
    (3)
    HRS
    (4)
    ELSA
    (5)
    HRS
    (6)
    ELSA
    (7)
    HRS
    (8)
    High school dropout−5.76.821.644.60.4050.3310.1630.006
    High school−36.6−24.9−33.9−25.00.0220.0010.0660.000
    College−27.4−23.9−38.8−26.40.1590.0280.1590.004
    • Notes: Estimates of relative differences in Columns 1−4 compare figures in Panel D of Table 13 and those in Panel A of Table 10, with the latter as baseline. p-values in Columns 5–8 for testing the equality of the same δ estimates.

    • View popup
    Table 15

    Oaxaca Decomposition of U.S.-English Differences

    MenWomen
    θΔHΔYθΔHΔY
    Subjective health
    High school dropout0.97−0.040.070.85−0.240.38
    High school0.97−0.080.110.690.090.22
    College0.570.110.320.760.030.20
    Subjective health and cognition
    High school dropout1.03−0.080.050.85−0.190.33
    High school0.93−0.020.100.740.060.20
    College0.700.010.300.86−0.060.20
    • Notes: Decomposition of the U.S.-English differences in the estimates of δ by its different components. Estimates are blanked out where they are uninformative. Columns labeled θ, ΔH, and ΔY show the shares explained by differences in the estimated coefficients, health declines, and employment declines, respectively.

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Journal of Human Resources
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The Impact of Health on Labor Supply near Retirement
Richard Blundell, Jack Britton, Monica Costa Dias, Eric French
Journal of Human Resources Jan 2023, 58 (1) 282-334; DOI: 10.3368/jhr.58.3.1217-9240R4

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The Impact of Health on Labor Supply near Retirement
Richard Blundell, Jack Britton, Monica Costa Dias, Eric French
Journal of Human Resources Jan 2023, 58 (1) 282-334; DOI: 10.3368/jhr.58.3.1217-9240R4
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  • Article
    • ABSTRACT
    • I. Introduction
    • II. Literature
    • III. Methods for Estimating the Effect of Health and Cognition on Employment
    • IV. Data and Descriptive Statistics
    • V. Empirical Results
    • VI. A Framework to Understand the Employment Choices of Older Workers
    • VII. Conclusions
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