Social Insurance: Connecting Theory to Data
نویسنده
چکیده
We survey the literature on social insurance, focusing on recent work that has connected theory to evidence to make quantitative statements about welfare and optimal policy. Our review contains two parts. We rst discuss motives for government intervention in private insurance markets, focusing primarily on selection. We review the original theoretical arguments for government intervention in the presence of adverse selection, and describe how recent work has re ned and challenged the conclusions drawn from early theoretical models. We then describe empirical work that tests for selection in insurance markets, documents the welfare costs of this selection, and analyzes the welfare consequences of potential public policy interventions. In the second part of the paper, we review work on optimal social insurance policies. We discuss formulas for the optimal level of insurance bene ts in terms of empirically estimable parameters. We then consider the consequences of relaxing the key assumptions underlying these formulas, e.g., by allowing for scal externalities or behavioral biases. We also summarize recent work on other dimensions of optimal policy, including mandated savings accounts and the optimal path of bene ts. Finally, we discuss the key challenges that remain in understanding the optimal design of social insurance policies. We are grateful to Alan Auerbach, Liran Einav, Hilary Hoynes, Emmanuel Saez, and participants at the Handbook of Public Economics conference held at UC-Berkeley for helpful comments. Shelby Lin, Heather Sarsons,and Michael Stepner provided excellent research assistance. We gratefully acknowledge support from the NIA R01 AG032449 (Finkelstein) and the National Science Foundation SES 0645396 (Chetty).
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تاریخ انتشار 2012