Knowledge that Transforms

The debate about behavioral economics–the incorporation of insights from psychology into economics–is often framed as a question about the foundational assumptions of economic models. This paper presents a more pragmatic perspective on behavioral economics that focuses on its value for improving empirical predictions and policy decisions. I discuss three ways in which behavioral economics can contribute to public policy: by offering new policy tools, improving predictions about the effects of existing policies, and generating new welfare implications. I illustrate these contributions using applications to retirement savings, labor supply, and neighborhood choice. Behavioral models provide new tools to change behaviors such as savings rates and new counterfactuals to estimate the effects of policies such as income taxation. Behavioral models also provide new prescriptions for optimal policy that can be characterized in a non-paternalistic manner using methods analogous to those in neoclassical models. Model uncertainty does not justify using the neoclassical model; instead, it can provide a new rationale for using behavioral nudges. I conclude that incorporating behavioral features to the extent they help answer core economic questions may be more productive than viewing behavioral economics as a separate subfield that challenges the assumptions of neoclassical models.

We measure the breadth of insurance networks in the Massachusetts health insurance exchange. Using our measures, we estimate consumer willingness-to-pay for broad and narrow networks. We find that consumers have a wide range of plans available with dramatically different networks. While consumers value broader networks, their willingness-to-pay is smaller than the brand premium, indicating an additional role for brand preferences. Consumers place additional value on star hospitals, which may affect upstream negotiations. Finally, we find significant geographic heterogeneity in the value of broad networks.

Consumer bankruptcy is one of the largest social insurance programs in the United States, but little is known about its impact on debtors. We use 500,000 bankruptcy filings matched to administrative tax and foreclosure data to estimate the impact of Chapter 13 bankruptcy protection on subsequent outcomes. Exploiting the random assignment of bankruptcy filings to judges, we find that Chapter 13 protection increases annual earnings by $5,562, decreases five-year mortality by 1.2 percentage points, and decreases five-year foreclo-sure rates by 19.1 percentage points. These results come primarily from the deterioration of outcomes among dismissed filers, not gains by granted filers. (JEL D14, I12, J22, J31, K35)