Essays on the Economics of Information and the Design of Public Policy

Abstract

I study how incomplete information affects decision-making processes. I combine tools from industrial organization, behavioral economics, and public finance to provide frameworks that empirically quantify the effects of information on market structures and public policies. Chapter 1 of my dissertation analyzes the consumer-welfare effects of intermediaries in a pension and annuity market with adverse selection. Intermediaries provide advice, helping individuals improve decisions when understanding products is complex and costly, but may introduce distortions due to agency problems. In an insurance market, intermediary effects on choices can impact adverse selection and, through it, prices. I develop and estimate a dynamic demand model that includes life-cycle decisions, product, and intermediation choices. I find intermediaries have the potential to improve welfare: retirees would give up around 250 USD a year to eliminate frictions in product choices. Despite intermediaries steering a majority of their customers into annuities, a ban on intermediation is approximately consumer-welfare neutral. Chapter 2 (co-authored with Jordan Richmond) studies the ability of the government to target fiscal stimulus through the design of the tax code. We study the role of Net Operating Losses -- when tax deductions exceed taxable income -- in focusing billions of dollars of tax relief into firms. We build a rich, dynamic firm investment model that accommodates carryforwards, tax code incentives -- which exclude loss firms from immediate investment stimulus -- and financing constraints. The model flexibly replicates patterns in the data and allows us to quantify the effect of tax design on fiscal policies aiming to incentivize investment. Chapter 3 (co-authored with Álvaro Carril) deals with the role of universities' preferences for students and their impact on academic achievement and access to higher education. Using a reform that expanded the set of admission requirements -- information used to select students --, we show the importance and limits of universities' discretion over these tools. Through their responses and predictions of students' performance, we infer preferences over different student "types." We use these results to study the effects of allowing university discretion in selecting admission weights and the potential trade-off between inclusion and university-specific predictors of academic success.