NB19-17: Optimal Disability Insurance Payments with Health and Employment Effects

We will examine the optimal replacement rate for DI benefits. According to classic public finance theory, assessing the welfare effects of DI requires weighing the benefits of allowing people with disabilities to maintain their consumption against the moral hazard costs from the resulting reductions in labor supply (Baily 1978, Chetty 2006). We will adapt the Baily-Chetty optimal insurance framework to account for DI payments’ positive effect on life expectancy, and then use administrative data to estimate what level of benefits balance these priorities optimally. This builds on two papers we have written on how DI income affects the earnings and mortality of beneficiaries (Gelber, Moore, and Strand 2017, 2018).
Prior research has focused primarily on how DI affects work decisions, concluding that DI substantially reduces employment and earnings. Less attention has been given to the potential benefits of DI (Chetty and Finkelstein 2013), apart from focusing on the benefits that DI provides by smoothing beneficiaries’ income and consumption (e.g., Bound et al. 2004, Meyer and Mok 2013, Low and Pistaferri 2015, Autor et al. 2017). By ignoring benefits related to health, previous research may understate how much DI income should be provided to DI beneficiaries. It is important that this gap be addressed, especially as lawmakers have recently considered reforms to DI that include changing the cash paid to beneficiaries. We will pursue the following plan:
• Literature Review: investigators will draw on studies from the literature on optimal disability insurance payments, as well as the literature on optimal social insurance more generally.
• Theoretical model: investigators will derive a model showing how to calculate optimal DI replacement rates when DI payments can affect health.
• Data: the key information necessary to calibrate our model has been gathered in our previous research using the SSA Disability Analysis File (Gelber Moore and Strand 2017, 2018). We supplement this information with survey data to inform other model parameters. Note: no new administrative data are needed for this project.
• Analysis: investigators will use effects of DI on health and earnings estimated in previous papers to calibrate optimal DI replacement rates.