This paper investigates the effect of the Affordable Care Act’s Medicaid expansion on the retirement decision of low-educated adults aged 55–64. I employ a difference-in-differences strategy that exploits the timing and expansion decisions of states for adults without dependent children. I find that the expansions increase Medicaid enrollment for both men and women. The estimates also suggest that the expansions result in women retiring early, whereas there is no significant change in the retirement behavior of men. These findings imply that the effect of health insurance on women’s retirement decisions may depend on men’s labor market responses to health insurance.
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As of January 2018, there are 33 expansion states and 18 non-expansion states.
See Figure 11.1, 2017 Employer Health Benefits Annual Survey, Kaiser Family Foundation and Health Research and Educational Trust, retrieved May 1, 2017 from: https://www.kff.org/health-costs/report/2017-employer-health-benefits-survey/.
For example, Bailey and Chorniy (2016) investigate the job lock effect using the dependent coverage mandate as a natural experiment.
These estimates are similar to those found in the literature (see, for example, Kaestner et al. 2017).
Using the 2006 Massachusetts health reform as a natural experiment, Heim and Lin (2017) find an increase in women’s early retirement from full-time employment by 1.1 percentage points and no effect on men’s retirement behavior.
These two modules of SIPP are on education, work history, and job characteristics.
The paper addresses censoring problems related to the outcome variable, as well as selection into jobs.
The authors are conservative with respect to the causal interpretation of their estimates.
Retirement is defined as a transition from full-time employment in the baseline year to retirement at the next survey date.
The effect on self-employment is negative, but it is not statistically different from zero.
One limitation of the study is with regards to external validity because the author drops public schools in large cities.
As discussed by Aslim (2016), large and heterogeneous treatment groups may jeopardize the estimates for labor market outcomes.
For adults aged 51–56 years, some of the effective provisions of the ACA within those periods are the changes to private health insurance with respect to preexisting conditions, the introduction of health insurance exchanges, and some early expansions.
In addition, some of the studies that look at the relationship between RHI and retirement have confounded the estimates by not controlling for defined benefit pensions. Note that defined pension plans, which are correlated with the availability of RHI, may increase the probability of early retirement (Gustman and Steinmeier 1994).
Using a dynamic model, they also simulate the effect of employer-provided health insurance on labor force participation rates.
Since marginal medical care received decreases as health worsens, it is reasonable that M is nonlinear in H.
In a dynamic framework, however, it would be interesting to investigate the employment outcomes of individuals who choose between RHI and Medicaid.
See full list of mandatory benefits at http://www.Medicaid.gov.
Health variables are mainly related to disabilities, including self-care difficulty, hearing difficulty, vision difficulty, independent living difficulty, ambulatory difficulty, and cognitive difficulty.
Note that the publicly available HRS does not include geographic identifiers.
A minor limitation is the absence of survey months that could be used to capture the monthly variation in policy variables. Note that March CPS does not also vary by months.
This restriction is consistent with the literature; for example, Kaestner et al. (2017) restrict the sample to low-educated adults to explore the effect of Medicaid expansions on labor supply.
Note that the availability of Medicare may confound the estimates on Medicaid. Thus, I exclude adults above the age of 64. In addition, some studies denote stronger retirement incentives for adults who are closer to the 64 age cutoff; I also test this by restricting the age to 59–64.
Note that retirement income is highly correlated with the probability of leaving the labor force. An alternative definition could be the probability of leaving the labor force conditional on working full time in the past 12 months (Heim and Lin 2017). The findings of the IV model are robust to the changes in the definition of the outcome variable and are available upon request.
When early and late expansion states are included in the analysis, the timing of expansion changes, and Post also changes accordingly.
The findings for the 2009–2013 pre-policy period are in “Appendix”.
The estimates for private health insurance are available upon request.
The OLS estimates are available upon request.
The findings are, however, robust to changes in the sample period to 2010–2016.
The benchmark sample includes childless adults aged 55–64 years. This age restriction for the lower boundary is the same as the previous studies that investigate the effect of RHI on early retirement (Gruber and Madrian 1996; Rogowski and Karoly 2000; Boyle and Lahey 2010; Shoven and Slavov 2014; Fitzpatrick 2014). On the other hand, there are some retirement studies that use either 50 or 51 as the lower boundary for age (Strumpf 2010; Robinson and Clark 2010; Levy et al. 2018).
Note that these individuals do not have dependent children under the age of 18.
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I would like to thank Dhaval Dave (editor) and two anonymous referees for their very helpful suggestions. I would also like to thank Shin-Yi Chou, Muzhe Yang, Seth Richards-Shubik, Karen S. Conway, Naim Chy, Liqun Liu, Ashley Bullock, Chelsea Temple, and the participants at the 2018 Eastern Economic Association meeting. All errors are mine.
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Aslim, E.G. The Relationship Between Health Insurance and Early Retirement: Evidence from the Affordable Care Act. Eastern Econ J 45, 112–140 (2019). https://doi.org/10.1057/s41302-018-0115-8
- Affordable Care Act
- Job lock