Social Insurance: Connecting Theory to Data
By Raj Chetty, Amy N. Finkelstein. 2012
145 citations recorded by the source corpus.
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 first 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 refined 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 benefits in terms of empirically estimable parameters. We then consider the consequences of relaxing the key assumptions underlying these formulas, e.g., by allowing for fiscal externalities or behavioral biases. We also summarize recent work on other dimensions of optimal policy, including mandated savings accounts and the optimal path of benefits. Finally, we discuss the key challenges that remain in understanding the optimal design of social insurance policies.
Subfields: Accounting, Economics and Econometrics, Gender Studies
View Paper: https://www.semanticscholar.org/paper/8b9e05fc3b822b0f136be439f9eb45a50f8e4c95
Citations in the corpus
- A Macroeconomic Approach to Optimal Unemployment Insurance: Theory (2018, unknown): “The statistics from the Baily-Chetty formula ( ε m , Δ U , U ′ ( c ) , ϕ ) have been estimated in many studies ( see Krueger and Meyer 2002 and Chetty and Finkelstein 2013 for surveys .”
- Predictably Unequal? The Effects of Machine Learning on Credit Markets (2020, unknown): “In insurance markets, see, e.g., Einav and Finkelstein (2011), Chetty and Finkelstein (2013), Bundorf et al. (2012), and Geruso (2016).”