Family Trajectories and the Burden of Care in the Aftermath of Old-Age Health Shocks [SSRN - updated February 6, 2025]
Co-authors Kuan-Ming Chen and Kuan-Ju Tseng
Abstract:
Due to increasing longevity and declining fertility, families in many rich countries have experienced sharply rising aging-related care needs at the same time that the labor capacity within those families has fallen. How families meet those care needs given their constraints---and at what cost---is an increasingly important question. This paper shows that sudden declines in the health of elderly Taiwanese adults disrupts the life cycles of their adult children. Rather than causing substitution away from the labor force, elderly parental health shocks are followed by increased mortality, poorer indicators of health, and reduced marriage and fertility rates. Burdensome care needs are likely a key mechanism, judging from the observable characteristics that predict particularly adverse responses to a parental stroke. We find evidence that allowing families to hire migrant care workers can attenuate the negative associations between old-age health issues and family outcomes, improving the survival, health, and well-being of adult children of the elderly.
Explaining the decline in SSDI applications and awards since 2010
Co-authors Manasi Deshpande, Magne Mogstad, and Kuan-Ju Tseng
"Self-Insurance and Selection into Disability Insurance."
Forthcoming in the Journal of Political Economy: Microeconomics
Abstract:
The U.S. Disability Insurance (DI) system has a lengthy application process and strict work limitations. This paper presents evidence that these features cause negative selection into DI benefit receipt by screening out poorly self-insured individuals, other things equal. Taking the evidence to a rich life cycle model, this paper finds that expansionary DI reforms do not generate ex-ante welfare value in excess of their fiscal costs, as benefits can accrue to negatively-selected individuals with low marginal utility of consumption and strong self-insurance capacity. However, combining an asset test with expansions to the DI system can improve targeting and welfare.
"Combining Matching and Synthetic Controls to Trade off Biases from Extrapolation and Interpolation" [JASA]
Co-authors Magne Mogstad, Guillaume Pouliot, and Alex Torgovitsky
Journal of the American Statistical Association, 2021, 116, 536, 1804-1816
Abstract
The synthetic control method is widely used in comparative case studies to adjust for differences in pre-treatment characteristics. A major attraction of the method is that it limits extrapolation bias that can occur when untreated units with different pre-treatment characteristics are combined using a traditional adjustment, such as a linear regression. Instead, the SC estimator is susceptible to interpolation bias because it uses a convex weighted average of the untreated units to create a synthetic untreated unit with pre-treatment characteristics similar to those of the treated unit. More traditional matching estimators exhibit the opposite behavior: they limit interpolation bias at the potential expense of extrapolation bias. We propose combining the matching and synthetic control estimators through model averaging to create an estimator called MASC. We show how to use a rolling-origin cross-validation procedure to train the MASC to resolve trade-offs between interpolation and extrapolation bias.
"Marketing-level exposure to state antismoking media campaigns and public support for tobacco control policy in the United States, 2001-2002."
Co-authors Jeff Niederdeppe, Christofer Skurka, and Rosemary Avery
Tobacco Control, 2018, 27, 177-184
"Mixed Messages, Mixed Outcomes: Exposure to Direct-to-Consumer Advertising for Statin Drugs is Associated with More Frequent Visits to Fast Food Restaurants and Exercise"
Co-authors Jeff Niederdeppe, Rosemary Avery, and Alan Mathios
Health Communication, 2017,32:7, 845-856
"Explaining Geographic Differences in Young Disability Insurance Rates"
Co-authors John Friedman, Ithai Lurie, and Magne Mogstad
2018
Abstract
Although much research has explored the rise in young disability insurance (DI) receipt, there has been much less work explaining the large geographic differences in DI rates across cities and states. We explore the drivers of this heterogeneity using administrative tax data that allows us to link young adults (age 24-34) to their parents. Our findings are threefold. First, children from low income families display sharply varying probabilities of receiving DI depending on the place where they grew up, while those from rich families show no similar differences. Second, we show that DI take-up of children from low income families exhibits heterogeneity both over time (cyclically) and over place which is not apparent for children from richer families. Third, we show that places where poor children grow up to have the highest rate of DI receipt tend to be “good” areas based on many standard characteristics, including lower inequality, lower segregation, higher school quality, and higher social capital. State level tax policies are also predictive of DI rates; states with more generous EITCs, lower tax rates, and less progressive tax structures each tend to have higher DI take-up. These are also the characteristics of places that tend to produce higher income mobility. We show that the relationship between child outcomes in terms of DI take-up and income mobility across places is mixed, but the places that tend to generate good outcomes on both measures are more rural. By comparison, this appears to be less true for the places generating particularly bad outcomes on both measures.