A. “Labor Force Transitions at Older Ages: Burnout, Recovery, and Reverse Retirement,” by Lindsay Jacobs and Suphanit Piyapromdee (2016-053, 2016, .pdf format, 43p.).
Abstract:
Abstract: Partial and reverse retirement are two key behaviors characterizing labor force dynamics for individuals at older ages, with half working part-time and over a third leaving and later re-entering the labor force. The high rate of exit and re-entry is especially surprising given the declining wage profile at older ages and opportunities for re-entry in the future being uncertain. In this paper we study the effects of wage and health transition processes as well as the role of accrues work-related strain on the labor force participation on older males. We find that a model incorporating a work burnout-recovery process can account for such reverse retirement behavior that cannot be generated by health and wealth shocks alone, suggesting re-entry patterns result in large part from planned behavior. We first present descriptive statistics of the frequency and timing of re-entry and characteristics of those who re-enter using Health and Retirement Study (HRS) panel data. We then develop and estimate a dynamic model of retirement that captures the occurrence and timing of re-entry decisions observed in the data–as well as the transition to part-time work–while incorporating uncertainty in earnings, health, and stress accumulation. The burnout-recovery process allows us to account of for about 40 percent of re-entry, and one-quarter of the shifts to part-time work with age. We also consider the lower exit and re-entry rates after 2008, and attribute this to high option values of work in an environment where future re-entry is less certain. Consistent with out burnout-recovery model, we see that respondents are more likely to report high levels of job stress as they continue to work when they would have otherwise stopped working, recovered, and re-entered. This offers us some information about the relative option value of work versus the burnout-recovery process.
www.federalreserve.gov/econresdata/feds/2016/files/2016053pap.pdf
B. “Occupational Choice, Retirement, and the Effects of Disability Insurance,” by Lindsay Jacobs (2016-051, 2016, .pdf format, 53p.).
Abstract:
There is much variation in the physical requirements across occupations, giving rise to great differences in later-life productivity, disability risk, and the value of Social Security Disability Insurance (SSDI). In this paper, I look at how such differences across occupations affect initial career choice as well as the extent to which SSDI, which insures shocks to productivity due to disability, prompts more people to choose physically intense occupations. Using data from the Health and Retirement Study (HRS) and the Current Population Survey (CPS), I estimate a dynamic model of occupational choice and retirement with heterogeneous agents and equilibrium effects on earnings across occupations. I document the differences between blue-collar and white-collar occupations in the effects of declining health and disability on productivity, which affects labor supply in later life and, in the context of a life-cycle model, influences the occupation decision. Thro ugh counterfactual exercises, I show that the additional disability risk in blue-collar jobs relative to white-collar jobs is equivalent to an additional six percentage point reduction in lifetime consumption and that the absence of SSDI, which insures some of this risk, would be equivalent to, respectively, a twelve and seven percent reduction in consumption for those in blue- and white-collar jobs. Furthermore, I find that the presence of SSDI results in three percent more individuals choosing blue-collar occupations, which is comparable to the effect on occupation selection resulting from an eight-percent increase in blue-collar earnings. This overall effect, however, masks the importance of the selection of less risk-averse individuals into blue-collar jobs and the equilibrium effects on wages; earnings for the most risk-averse type would have to be nearly fifteen percent greater to choose blue-collar occupations in the absence of SSDI.
www.federalreserve.gov/econresdata/feds/2016/files/2016051pap.pdf
