Do economic fluctuations have negative health consequences? Studies of the effects of economic shocks on health have come to very different answers to this question. Studies based on aggregate data (such as mortality rates) often claim that health improves during economic downturns. It is argued that this occurs largely because people change their health behaviours, for example by smoking and drinking less when they lose income, or by losing weight and exercising more when they gain leisure time. (Ruhm and Black 2002, Ruhm 2000, 2003, 2005). Studies using individual-level data often reach the opposite conclusion, finding that increases in unemployment are associated with poorer health, perhaps due to stress associated with either losing a job, or fearing job loss, and/or because of reductions in income and wealth that curtail purchases of health enhancing goods and services (Dee 2001, Eliason and Storrie 2009a, 2009b, Sullivan and Wachter 2009, Browning and Heinesen 2012). The lack of consensus suggests that additional research on this question is warranted.
In a departure from the existing literature, in a recent paper my co-authors and I examine the effects of the Great Recession on the health and health behaviours of mothers (Currie et al 2015). Most evidence regarding the link between economic fluctuations and health has focused on employed workers (usually men), who have traditionally had the strongest labour force attachment. Much less is known about mothers, who have varying degrees of labour force participation but may also be impacted by high unemployment in their communities regardless of their own employment status. Focusing on mothers is especially interesting given recent research showing that inequality starts early in life and that the children of disadvantaged mothers are more likely to grow up to be disadvantaged themselves (Currie and Stabile 2003, Case et al. 2005, Currie 2009, Almond and Currie 2011). Thus maternal economic distress has the potential to generate intergenerational effects.
By including data that incorporate the Great Recession (from mid-2007 to the beginning of 2010), we are able to exploit greater exogenous variation in the unemployment rate across states and years, compared to previous studies of milder macroeconomic downturns. Figure 1 shows the wide variation in unemployment rates across time, and across the 15 US states represented in the Fragile Families data set.
Figure 1. State unemployment rate (%) during Fragile Family interview rounds
Our study is also one of the first studies to use longitudinal data to analyse the effects of economic fluctuations on health, and the first to do so for the case of the Great Recession. We employ panel data from the Fragile Families and Child Well-being Study, which allows us to observe the same mother both before and during the Global Crisis. Thus, individual time-invariant characteristics that might be correlated with both the probability of residing in an area with high unemployment and with experiencing declines in health are controlled by the inclusion of maternal fixed effects. Fragile Families provides a wide range of self-reported health outcomes – including physical and mental health, as well as health behaviours.
We find unambiguous evidence that the crisis worsened mothers’ self-reported health status and led to increases in smoking and drug use.
- A one percentage point increase in unemployment was associated with a 4.3% decline in the probability of being in excellent or very good health overall, a 5.1% increase in the probability of smoking, and a 15.2% increase in the probability of using illegal drugs (or using legal drugs in an illicit manner).
- Unmarried mothers were also more likely to increase smoking.
Since it is unlikely that adult women with children would suddenly start smoking or using drugs when they had never done so before, a possible interpretation of these results is that economic distress causes back-sliding in populations who used substances in their youth, but had given them up.
- The effects of the recession were even larger for disadvantaged mothers, especially African Americans and Hispanics, those with a high school education or less, and those who were unmarried.
The fraction of African-American mothers reporting excellent or very good health declined by 9.1% for each one point increase in unemployment and the probability of using drugs increased by 10.1%. Hispanic women experienced an 18.2% increase in the probability of being depressed.
In contrast, there were few negative effects of increases in unemployment on mothers who were white, married, and/or college educated. White women were somewhat more likely to binge drink as the economy deteriorated, but among white women, obesity fell by 4.5% for each 1% increase in unemployment, and the incidence of depression fell by 11.1%. Married mothers were also less likely to be depressed. College educated mothers did report increases in smoking, but also reported fewer overall health problems.
Overall, our findings suggest a possible reconciliation of some of the findings in the prior literature. The effects of recessions on health are heterogeneous so that measured effects are likely to depend on which group and which time period is being analysed.
- Increases in unemployment worsened physical and mental health, and increased smoking and drug use among minorities, unmarried mothers, and less educated mothers;
- By contrast, more advantaged women may have actually experienced better mental health and some improvements in their physical health.
These results are consistent with recent findings suggesting that the employment effects of the crisis were disproportionately concentrated in some subpopulations (Hoynes et al. 2012).
Future research should explore what is driving these heterogeneous impacts. Many studies have argued that unemployment could impact people’s health through changes in health behaviour, increased stress, and/or declines in income and wealth. Whether the relative importance of these pathways differs across social groups and whether it is greater for those experiencing higher economic burdens remains an open question. Another useful extension of our work would be to investigate the impacts of the Great Recession on children’s health.
The declines in mothers’ health among the disadvantaged suggest important short- and long-term effects on young children that could contribute to inequality for years to come.
Almond, D and J Currie (2011) “Human capital development before age five”, in D Card and O Ashenfelter (eds), Handbook of Labor Economics, chapter 15, vol 4, part B: 1315–1486, New York: American Elsevier Publishing Co.
Browning, M and E Heinesen (2012) “Effect of job loss due to plant closure on mortality and hospitalisation”, Journal of Health Economics, 31(4): 599-616.
Currie, J (2009) “Healthy, wealthy, and wise? Socioeconomic status, poor health in childhood, and human capital development”, Journal of Economic Literature, 47(1): 87-122.
Currie, J and M Stabile (2003) “Socioeconomic status and child health: Why is the relationship stronger for older children?”, American Economic Review, 93(5): 1813-1823.
Currie, J, V Duque and I Garfinkel (2015) “The Great Recession and mother’s health”, The Economic Journal, Nov.
Dee, T S (2001) “Alcohol abuse and economic conditions: Evidence from repeated cross-sections of individual-level data”, Health Economics, 10(3): 257-270.
Eliason, M and D Storrie (2009a) “Does job loss shorten life?”, Journal of Human Resources, 44(2): 277-302.
Hoynes, H W, D Miller and J Schaller (2012) “Who suffers during recessions?”, Journal of Economic Perspectives, 26(3): 27-48.
Ruhm, C (2000) “Are recessions good for your health?”, Quarterly Journal of Economics, 115(2): 617-650.
Ruhm, C (2003) “Good times make you sick”, Journal of Health Economics, 22(4): 637-658.
Ruhm, C (2005) “Healthy living in hard times”, Journal of Health Economics, 24(2): 341-363.
Ruhm, C and W E Black (2002) “Does drinking really decrease in bad times?”, Journal of Health Economics, 21(4): 659-678.
Sullivan, D and T von Wachter (2009) “Job displacement and mortality: An analysis using administrative data”, Quarterly Journal of Economics, 124(3): 1265-1306.