Abstract
The dramatic rise and sustained participation of recent cohorts of women in the labor force has coincided with their increased attachment to the labor market. In this paper we use twelve waves of the Health and Retirement Study (1992-2014) and investigate how married couples belonging to more recent birth cohorts compare with their predecessors in terms of coordinating their retirement decisions. Using a multinomial logit model we estimate the labor force dynamics of dual-earner married couples and find that couples with wives belonging to more recent birth cohorts are less likely to jointly exit the labor force. Further, this declining cohort trend in joint retirement can only partially be explained by commonly observed socio-economic, employment, and health related factors that affect retirement decisions, suggesting an important role for cohort changes in preferences and social norms such as preference for work and attitudes toward gender roles.
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Notes
Source : U.S. Census Bureau, National Projections 2014.
An example is the increase in the eligibility age for unreduced retirement benefits in the U.S. from age 65 to 67 with the normal retirement age (NRA) of 67 becoming fully effective for workers who reach age 62 in 2022 or later.
An exception is the study by Schellenberg and Ostrovsky (2008) who used the Canadian Longitudinal Administrative Database (LAD) to analyze the retirement patterns of dual-earner couples in which at least one spouse retired in 1986, 1991, 1996 or 2001. They found that between 1986 and 2001 the proportion of dual-earner couples in which both spouses retire within two years of each other declined by two percentage points while the proportion of wives retiring five or more years after their husbands increased by seven percentage points, implying some evidence for increasingly disjointed spousal retirements in Canadian data. However, their results at best provide suggestive evidence on this issue as they only compare cross sections of retiring cohorts at different points in time and hence their results may be confounded by the presence of cohort specific effects.
We use an exhaustive list of controls that include labor market characteristics, socio-economic and demographic variables, health status of both spouses. “Empirical Model” provides a full list of economic factors used in the benchmark estimation.
A related finding is by Ho and Raymo (2009) who use the first seven wave of the HRS data and found that couples retirement expectations are correlated with their joint retirement realization.
The baseline year is the first year when a married couple is observed in our sample.
For each such variable we include an indicator variable for non-response in our estimation model to account for missing observations.
Age difference is defined as age of the husband minus the wife’s age.
It should be noted that the main results of the paper are not sensitive to these sample restrictions. I have conducted the analysis with alternative sets of sample restrictions and obtained qualitatively similar results. These results are not reported in the paper for brevity but they are available upon request.
We also used an alternative definition of joint retirement based on the self reported retirement status of respondents in the HRS. Our main results are not sensitive to this alternative definition of retirement. These robustness checks are not reported for brevity and are available upon request.
Note that age difference is a linear function of the husband’s age and wife’s age. In our estimation equation we also control for the survey years and wife’s birth years. Hence, we effectively control for the effect age on the retirement decision of both spouses.
Of the included 2272 couples, 10.43% retired jointly, in 18.75% of couples the husband retired first and in 15.61% of couples the wife retired first.
Table 2 reports the transition probabilities by combining observations into a 4 year band for the wife’s birth year. The main findings of this analysis are not dependent on the choice of the birth year band.
Based on our current definition we abstract away from other kinds of transitions such as partial retirement or self-employment. However, our framework can be easily extended to include additional states where one or both spouses may transition to partial retirement or self employment.
Given the biennial nature of the HRS, a period in our framework represents two years.
Without loss of generality, we assume here that R c t = 4, capturing the outcome that both spouses are working in period t, is the reference group.
Note that age difference is linear function of the husband’s age and wife’s age. In our empirical specification, in addition to the age difference, we also control for wife’s birth years and survey years. Hence, we are effectively controlling for age effect on the retirement decision in our model.
For brevity we do not report the predicted probabilities for other three outcomes as our goal here is to simply show that there is a declining cohort trend in joint retirement in the data.
Ho and Raymo (2009) use this approach to estimate the effect of initial retirement expectation on realized joint retirement outcomes for married couples using the HRS data.
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Bhatt, V. Cohort Differences in Joint Retirement: Evidence from the Health and Retirement Study. J Labor Res 38, 475–495 (2017). https://doi.org/10.1007/s12122-017-9258-3
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DOI: https://doi.org/10.1007/s12122-017-9258-3