by Ruwei Wang, University of Virginia
The Social Security Disability Insurance (SSDI) Program, as one main component of the OASDI program, provides income protection to qualified workers who suffer from disabilities. Loss of earnings capacity is a major risk faced by workers, and yet it is difficult to insure against it in private markets, perhaps because of adverse selection and moral hazards. The DI program, however, ensures financial help to people who become disabled.
Because of a rapid expansion in the DI rolls in recent years, the DI program is now facing insolvency. So far, few reforms have worked efficiently to reduce the number of DI beneficiaries by inducing them to return to work, and a newly proposed reform called “$1 for $2 Offset” is currently under study. Under this policy, beneficiaries can receive reduced DI benefits for a certain period even if they return to work and earn above the Substantial Gainful Activity (SGA) threshold. This project will use a general equilibrium model to analyze the effects of the “1 for 2″ policy on workers’ behaviors, such as their decisions on entering and exiting DI, and the financial health of OASDI. Furthermore, the dynamic model will also be used to analyze other related DI policies as well as their interactions with Social Security retirement benefits reforms.
My research methodology is to set up a dynamic general equilibrium life-cycle model and simulate different DI policies. I incorporate both DI and Old Age (OA) retirement benefits since these two programs are closely related. Workers are heterogeneous in the impact of health shocks, education and gender on productivity, and make decisions about OA/DI benefits application based on their age and health. Workers face uncertainty about future health status, mortality, and DI acceptance. DI recipients can choose to stay on the DI rolls or return to work if they recover. The government can only observe a DI applicant’s health status imperfectly and therefore makes mistakes in the award decisions. This is consistent with the existing literature on the classification errors of DI awards.
The major data set I use to calibrate parameters is the Health and Retirement Study (HRS), which offers panel data on older people’s health, work, and DI application status. The Current Population Survey (CPS) is used to measure disability prevalence among younger workers. I have preliminary results from a simplified version of the model, where workers are heterogeneous only by health. My preliminary results show that the “1 for 2″ policy does succeed in reducing total DI payments while increasing the number of DI beneficiaries. Through the general equilibrium impact on the whole economy, average labor supply, capital, consumption, and social welfare all increase. Next, I will further develop the simple model to match additional important moments in data and use it to analyze the “1 for 2″ policy and other possible reforms in order to propose an optimal DI system.