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Health and Financial Strain: Evidence from the Survey of Consumer Finances. Angela Lyons University of Illinois at Urbana-Champaign Tansel Yilmazer Purdue University National Taiwan University November 2006. The Motivation (Recent Financial Trends in the U.S.).

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Health and financial strain evidence from the survey of consumer finances

Health and Financial Strain: Evidence from the Survey of Consumer Finances

Angela Lyons

University of Illinois at Urbana-Champaign

Tansel Yilmazer

Purdue University

National Taiwan University

November 2006

The motivation recent financial trends in the u s

The Motivation(Recent Financial Trends in the U.S.)

  • Uncertain economy and higher unemployment

  • Rise in bankruptcies and delinquencies

  • Large debt burdens from the 1990s

  • Rising health care costs

    The Research Question:

    What is the impact of financial strain on health?

Previous research

Previous Research

  • Strong positive relationship between health and socioeconomic status (SES).

  • However, little consensus on the direction of causality.

  • Is poor health both a cause and a consequence of socioeconomic status (SES)?

On the one hand

On the one hand….

Some studies find that poor health affects SES.

  • Individuals who are in poor health work fewer hours or are unemployed, limiting abiltity to accumulate income and wealth.

  • Serious health conditions have a larger effect on SES than less serious conditions.

  • Smith and Kington 1997; Zagorsky, 1999; Wu 2003

On the other hand

On the other hand….

Studies find that lower SES affects health.

  • Individuals health can be affected in 2 ways:

    • Financial problems creates physical or psychosocial stress which affects health

    • Limited access to quality health care services and preventative care

  • Caplovitz 1974; Smith 1998, 1999; Roberts et al. 1999; Drentea and Lavrakas 2000; Meer, Miller, and Rosen 2003

  • Also note

    Also, note….

    Focus on income and wealth

    • Smith and Kington (1997)

    • Adams et al. (2003)

    • Zagorsky (1999)

      Focus on liability holdings and financial stress

    • Drentea and Lavrakas (2000)

    • Roberts et al. (1999)

    Health and financial strain evidence from the survey of consumer finances

    Specific Studies

    • Smith and Kington (1997)

      • Health and Retirement Survey (HRS) and the Asset and Health Dynamics among the Oldest Old (AHEAD).

      • Find direction of causality primarily from health to SES.

    • Adams et al. (2003)

      • Panel data from AHEAD; distinguish between acute, chronic, and mental health conditions; control for existing health conditions.

      • Find some evidence that wealth increases incidence of some mental and chronic conditions.

      • But in general reject hypothesis that SES results in health problems.

    • Meer, Miller, and Rosen (2003)

      • Use PSID to examine changes in wealth and health.

      • Control for endogeneity of SES using IV that controls for changes in wealth (receipt of an inheritance).

      • The effect of wealth on health becomes insignificant when endogeneity of wealth is taken into account.

    Contributions of this study to the literature

    Contributions of this study to the literature:

    • Moves beyond income and wealth and focuses on the relative financial position of the household.

    • Controls for the possible endogeneity between health and financial burden.

    • Uses a representative sample of the U.S. population.

    Description of the data

    Description of the Data

    Data from the 1995, 1998, and 2001 Survey of Consumer Finances

    Features of the SCF:

    • Cross-sectional survey that collects data every three years.

    • Detailed info on financial holdings, income and demographics.

    • Includes a self-reported measure of health status.

      Households are identified as “financially strained” if

    • Delinquent on any type of loan payment by two months or more

    • Total assets/total debts < 1.0

    • Liquid assets/disposable income < 0.25

    Health and financial strain evidence from the survey of consumer finances

    Table 1

    Demographic Statistics by Financial Strain and Health Status


    Financial Strain____________ _Health

    Delinq Assets/debts<1. Liq/inc<0.25 H PH

    FS=1 FS=0 FS=1 FS=0 FS=1 FS=0H=0 H=1

    No. of obs. (552) (12,250) (739) (12,063) (4,065) (8,737) (10,281) (2,521)


    Poor health 32.4 23.8 27.0 24.0 31.4 19.4 -.- -.-

    Measures of Financial Strain

    % delinquent100.0 0.0 20.1 4.4 9.6 2.7 4.9 7.4

    % (assets/debts) < 1.0 26.4 6.1 100.0 0.0 15.7 1.5 7.0 8.1

    % (liq assets/inc) < 0.25 70.7 38.7 87.8 36.7 100.0 0.0 36.6 52.3


    For each measure of financial strain, FS=1 indicates the household is financially strained and

    FS=0 indicates the household is not financially strained. H represents household heads who are not

    in poor health and PH represents household heads who are in poor health.

    Summary of descriptive statistics

    Summary of Descriptive Statistics

    • Financially-strained households are significantly more likely to be in poor health.

    • Those who are financially strained by one measure are more likely to be financially strained by other measures.

    • With respect to reverse causality, those in poor health are more likely to be financially strained.

    • HOWEVER, it is likely that health status plays a more important role in explaining why some households are under financial strain than vice versa.

    Empirical framework

    Empirical Framework

    Simultaneous two-equation probit models:


    FSi* = the degree to which the household is under financial strain

    Hi*= the degree to which the head of the household is in poor


    Probability of financial strain

    Probability of Financial Strain

    X1i includes:

    • Financial factors: income of head, liquid assets, other assets

    • Demographics: head’s age, education, marital status, gender, ethnicity, employment status, number of children, whether household receives welfare, whether household has private health insurance coverage

    • Identification: whether household experienced negative income shock in past year that was unrelated to health; household’s attitudes, preferences, or values for borrowing specific consumption goods

    Probability of poor health

    Probability of Poor Health

    X2i includes:

    • Samefinancial and demographic factors as X1i

    • Identification: whether head currently smokes (health behaviors), whether household expects major medical expenses in the next 5-10 years (expectations), whether head’s father is still living (biological)

    Testing the overidentifying restrictions hausman 1983 p 444 johnson and skinner 1986 p 465

    Testing the Overidentifying Restrictions(Hausman 1983, p. 444; Johnson and Skinner 1986, p. 465)

    • Each structural equation was estimated with and without the excluded variables from the other equation.

    • Null hypothesis: Addition of excluded variables should have little effect on explanatory power of the equation.

    • Use likelihood-ratio tests.

    • Tests reveal that overidentifying restrictions have not been seriously violated.

    Health and financial strain evidence from the survey of consumer finances

    Table 2

    Two-Stage Probit Models: Effect of Poor Health on Probability of Financial Strain (N=12,802)


    DelinquentAssets/Debts < 1.0Liq Assets/Income < 0.25


    Predicted value: Poor health 0.742 (0.146)*** 0.324 (0.117)*** 0.293 (0.088)***

    log (Income)-0.009(0.030)-0.156(0.031)*** -.----(-.----)

    log (Liquid assets)-0.044(0.012)*** -.----(-.----) -.----(-.----)

    log (Other assets) 0.031(0.009)*** -.----(-.----)-0.082(0.006)***


    Education (years) 0.041(0.013)*** 0.037(0.013)***-0.080(0.009)***

    Female-0.002(0.085) 0.110(0.073)-0.005(0.058)

    Black 0.092(0.078) 0.013(0.063) 0.014(0.048)

    Number of children 0.084(0.022)***-0.051(0.023)** 0.036(0.016)***

    Divorced/Separated 0.155(0.084)* 0.170(0.084)** 0.119(0.056)**

    Single 0.052(0.091) 0.042(0.079)-0.130(0.051)**

    Widowed 0.029(0.133) 0.094(0.129) 0.178(0.077)***


    Self-employed-0.050(0.069)-0.319(0.080)*** 0.033(0.039)

    Receives welfare-0.426(0.124)***-0.038(0.101) 0.118(0.089)

    Private health insurance 0.066(0.071)-0.250(0.058)***-0.593(0.043)***

    Negative income shock 0.249(0.068)*** 0.051(0.058)-0.002(0.039)

    All right to borrow for vacation 0.083(0.074) 0.077(0.057) 0.027(0.039)

    All right to borrow when income cut 0.130(0.051)*** 0.099(0.049)** 0.058(0.032)**

    All right to borrow for fur/jewelry 0.048(0.093) 0.186(0.084)** 0.106(0.057)**

    All right to borrow for car 0.129(0.065)**-0.026(0.060) 0.096(0.042)**

    All right to borrow for education-0.019(0.074) 0.094(0.066)-0.179(0.036)***

    Year 1998 0.052(0.056) 0.119(0.054)**-0.136(0.031)***

    Year 2001 0.016(0.053) 0.058(0.060)-0.098(0.029)***

    Constant-0.835(0.286)*** 1.301(0.311)*** 3.744(0.115)***


    Health and financial strain evidence from the survey of consumer finances

    Table 3

    Two-Stage Probit Models: Effect of Financial Strain on Probability of Poor Health (N=12,802)


    Probability of Poor Health

    VariableCoeffSE CoeffSE Coeff.SE

    Pred value: Delinquent 0.114(0.115) -.----(-.----) -.----(-.----)

    Pred value: Assets/Debts < 1.0 -.----(-.----) 0.020(0.195) -.----(-.----)

    Pred value: Liq Assets/Inc < 0.25 -.----(-.----) -.----(-.----) 0.142(0.185)

    log (Income)-0.061(0.020)*** -0.131(0.042)*** -.----(-.----)

    log (Liquid assets)-0.033(0.011)*** -.----(-.----) -.----(-.----)

    log (Other assets)-0.016(0.006)*** -.----(-.----) -0.023(0.018)

    Age 0.018(0.002)*** 0.016(0.005)*** 0.018(0.005)***

    Education (years)-0.060(0.005)*** -0.069(0.006)*** -0.066(0.019)***

    Female-0.109(0.052)** -0.114(0.055)** -0.085(0.053)*

    Black 0.101(0.049)** 0.173(0.050)*** 0.138(0.050)***

    Number of children-0.035(0.013)** -0.024(0.017) -0.033(0.015)**

    Divorced/Separated-0.031(0.054) -0.003(0.061) 0.012(0.056)

    Single-0.012(0.055) 0.013(0.070) 0.033(0.064)

    Widowed-0.029(0.058) -0.026(0.070) -0.005(0.083)

    Retired 0.188(0.093)** 0.086(0.057) 0.144(0.055)***

    Self-employed-0.091(0.046)** -0.123(0.079)* -0.150(0.034)***

    Receives welfare 0.447(0.065)*** 0.528(0.060)*** 0.469(0.071)***

    Private health insurance-0.096(0.038)** -0.173(0.073)*** -0.100(0.136)

    Currently smokes 0.147(0.042)*** 0.192(0.042)*** 0.166(0.051)***

    Expects medical expenses 0.375(0.051)*** 0.400(0.055)*** 0.411(0.039)***

    Father still living-0.136(0.037)*** -0.141(0.047)*** -0.137(0.039)***

    Year 1998 0.003(0.035) 0.007(0.046) 0.012(0.041)

    Year 2001 0.078(0.033)** 0.086(0.038)** 0.076(0.036)**

    Constant 0.409(0.169)** 0.779(0.346)*** -0.555(0.667)


    Health and financial strain evidence from the survey of consumer finances

    Table 4

    The Effect of a Change in Poor Health Status on the Probability of Financial Strain

    and a Change in Financial Strain on the Probability of Poor Health


    Pred Prob Pred Prob ME of a change ME of a change

    of being under of being in in Health Status in Financial Strain

    Models Financial Strain Poor Health on Financial Strain on Poor Health


    All Households

    Delinquent 2 months or more0.033 0.207 0.054*** 0.033

    (Total Assets/Total Debts) < 1.00.040 0.207 0.028*** 0.006

    (Liquid Assets/Income) < 0.250.366 0.201 0.110*** 0.040


    Marginal effects were calculated using the weighted sample means.

    Effects by education level

    Effects by Education Level

    The effect of poor health on financial strain may vary for

    different income groups.

    • Difficult to calculate permanent income using SCF.

    • We use education groups (high school education or less, some college, college degree) as proxies for permanent income.

    • The impact that poor health has on delinquency and assets/debts < 1.0 decreases and becomes less significant as education level of the head increases.

    • The impact that poor health has on liquid assets/income < 0.25 increases and becomes more significant as education level of the head increases.



    • Use marginal effects and predicted probabilities to calculate elasticities:

      E= (% financial strain / %  in poor health)

      = 0.054 * [20.7 / 3.3] = 0.339

    • 10% increase in percentage of households in poor health increases percentage of delinquent households by 3.39%.

    • Increases percentage of households with assets/debts < 1.0 by 1.45% and liquid assets/income < 0.25 by 0.62%.

    • Poor health has the largest effect on the percentage of delinquent households.



    • Using a more robust conceptualization of SES, evidence shows that the direction of causality is primarily from health to SES than SES to health.

    • Findings are robust across all 3 measures of financial burden.

    • Poor health increases the probability of financial strain.

    • Little evidence that financial strain contributes to poor health.



    • Gaps in health inequality may be contributing to widening financial disparities.

    • Those most likely to be affected are low-to-middle income families, especially those already in poor health.

    • Those with lower incomes who are in poor health may find themselves in a vicious cycle.

    • Severe health conditions may result in larger financial burdens while large financial burdens are unlikely to accelerate a decline in health status.

    Policy implications

    Policy Implications

    • May result in greater dependency on government assistance.

    • Reduction in overall household welfare.

    • More affordable and quality health care services for the poor may result in improved health outcomes and overall economic well-being.

    Limitations and directions for future research

    Limitations and Directions for Future Research

    • Longitudinal data to examine in more detail the relationship between household finances and health.

    • Further investigation of the definition of financial strain and the definition of health.

    • Issues of identification and instruments.

    • Additional research on the relationship between financial burden and health across households (i.e. income, age, gender, and race).

    Where do we go from here

    Where do we go from here?

    No Pain, No Strain:

    Impact of Health on the Financial Security of the Elderly

    (with Hyungsoo Kim, University of Kentucky)


    • U.S. population is rapidly aging.

    • Rising costs of health care (insurance premiums and medical expenses).

    • Dramatic growth in household debt levels for families near or in retirement.

    • Elderly will be particularly vulnerable to financial strain from rising health care burdens.

    Description of the data1

    Description of the Data

    Data from the 2004 Health and Retirement Study (HRS)

    Measures of health status:

    • Self-reported health status (SRH)

    • Objective measures of health:

      • Severe chronic health condition

      • Mild chronic health condition

        Households are identified as “financially strained” if

    • Solvency ratio: total assets/total debts < 1.0

    • Liquidity ratio: liquid assets/monthly income < 2.5

    • Wealth accumulation ratio: investment assets/net worth < 0.25

    Direction of causality

    Direction of Causality

    • At retirement, shift from accumulating wealth to spending it down.

    • Also, there is a point where additional spending on health services results in little improvement in health status.

    • Research shows the pathway from health to financial strain is more likely to be dominant.

      • Smith (1997, 1999)

        As individuals grow older, changes in economic resources have little additional impact on health.

      • Smith & Kington (1997) and Lee & Kim (2003)

        Direction of causation for older populations is from health to wealth.

    Empirical framework1

    Empirical Framework

    • Focus on effect of health on financial strain.

    • Assume the effect of financial strain on health is negligible for elderly.

      Two-stage probit model:


      FSi* = the degree to which the respondent is under financial strain

      Hi*= the degree to which the respondent is in poor health

    Probability of financial strain1

    Probability of Financial Strain

    Xi includes:

    • Financial characteristics of household: income, assets, monetary transfers

    • Demographics: elderly person’s age, education, gender, marital status, race/ethnicity, living arrangements, employment status, health insurance coverage (Medigap, Medicare HMO, employer-sponsored health insurance plan, Medicaid)

      Instruments for H*i :

      smoking and exercise (measures of health behaviors)

    Key findings

    Key Findings

    • Health problems significantly increase likelihood of financial strain for the elderly, especially those with severe chronic conditions.

    • Findings were consistent for all measures of financial strain and health.

    • Impact of poor health was significantly larger for severe chronic conditions than for mild chronic conditions and SRH.

    • Supplementary health insurance coverage significantly mitigated financial strain for the elderly.

    • The oldest elderly (aged 80+) may be most vulnerable.



    • Using financial ratios provides a more comprehensive picture of how health affects overall financial security of the elderly.

    • Important to consider both subjective and objective health measures to determine who is likely to bear greatest financial burden.

    • For elderly persons who have not adequately saved for retirement, a severe chronic condition could result in rapid wealth depletion, resulting in serious financial strain.

    • The results could be devastating for low-income elderly, who do not qualify for Medicaid and who cannot afford health insurance.

    Health and financial strain evidence from the survey of consumer finances

    Other directions for future research….

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