Abstract
“Doubling up” (sharing living arrangements) with family and friends is one way in which individuals and families can cope with job loss, but relatively little research has examined the extent to which people use coresidence to weather a spell of unemployment. This project uses data from the Survey of Income and Program Participation (SIPP) to provide evidence on the relationship between household composition and unemployment across working ages, focusing on differences in behavior by educational attainment. Using the SIPP panels, I find that individuals who become unemployed are three times more likely to move in with other people. Moving into shared living arrangements in response to unemployment is not evenly spread across the distribution of educational attainment: it is most prevalent among individuals with less than a high school diploma and those with at least some college.
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Notes
I use Waves 10–12 of the 1996 panel covering the period after 1998, when welfare reform had been fully implemented. There is mixed evidence that welfare reform affected living arrangements (Bitler et al. 2006).
The classification in this article differs from that of Mykyta and Macartney (2010), who used an age cutoff of 18 years for children. Even with the differences in methodology, the levels and distribution of doubling up in this article are broadly consistent with their results.
The measure of Hispanic overlaps with race and includes all individuals who describe their origin as Hispanic.
Kaplan (2012) analyzes the relationship between unemployment and living with parents for younger men who never attended college and discusses the implications of selecting a sample by educational attainment.
To avoid spurious transitions, I also exclude all people with imputed employment status.
The other possible transition to unemployment is to be out of the labor force in t and unemployed in t + 1. I check whether results are robust to counting these transitions as becoming unemployed and whether results are robust to including only people employed in t in the sample. Coefficients and standard errors are reported in the notes of Tables 4 and 5.
I estimated Eqs. (1) and (2) on the outcome of receiving a new household member. In Eq. (1), the coefficient on unemployment is positive and statistically significant, showing that becoming unemployed increases the probability of receiving a new household member by 50 %. In Eq. (2), and in all subsequent estimates using individual fixed effects, the coefficient on unemployment is much smaller and not statistically significant. The differences between the results with and without fixed effects for the receiving households suggest that the coefficient estimates without fixed effects are biased upward by the unobserved transitions of the people who enter the household. Hence, analysis on these transitions is excluded from the article.
Angrist and Pischke (2009) argue in favor of using linear models for discrete choice dependent variables, but because the probability of the outcome is low, the use of a linear model is less obvious. Nonlinear models with individual fixed effects are inconsistent for small T, large N because of the incidental parameters problem (Greene 2009; Lancaster 2000). The conditional logit can be used to estimate a nonlinear binary choice model with fixed effects captured in a sufficient statistic that conditions the likelihood function, similar to how fixed effects are differenced out in a linear model.
In Eq. (3), age group is defined by age at the beginning of the SIPP panel and does not vary through time. Thus, the direct effect of age group cannot be explicitly estimated because it is perfectly correlated with the individual fixed effect. How the effect of unemployment varies by age group relative to a base group can be estimated by including an interaction between unemployment and age group dummy variables, omitting the age group dummy variables themselves.
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Acknowledgments
This project was supported by the National Poverty Center at the University of Michigan, using funds received from the U.S. Census Bureau, Housing and Household Economics Statistics Division through contract number 50YABC266059/TO002. The opinions and conclusions expressed herein are solely mine and should not be construed as representing the opinions or policy of the National Poverty Center or of any agency of the Federal government. The research presented in this article benefitted from the resources provided by the Population Studies Center at the University of Michigan, and I am grateful for funding from the National Institute on Aging through Grant AG000221-17. For many helpful comments and suggestions, I thank the anonymous reviewers as well as Charles Brown, Sheldon Danzinger, V. Joseph Hotz, David Johnson, Kathleen McGarry, and Robert Schoeni; and Martha Stinson and Luke Shaefer for their assistance with SIPP data. All errors are my own.
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Wiemers, E.E. The Effect of Unemployment on Household Composition and Doubling Up. Demography 51, 2155–2178 (2014). https://doi.org/10.1007/s13524-014-0347-0
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DOI: https://doi.org/10.1007/s13524-014-0347-0