Jack Berger

I am a PhD Candidate in Economics at Indiana University Bloomington with research interests in empirical industrial organization, behavioral economics, and healthcare.

I will be joining the Rotman School of Management at the University of Toronto as a postdoctoral fellow in July 2025.

In my job market paper, I develop a structural econometric model of the hospital industry to evaluate how patients' limited consideration of all contracted options affects healthcare prices, access, and the accuracy of counterfactual predictions.

You can contact me at bergerjr@iu.edu.

Research

Job Market Paper

The Impact of Limited Consideration on Market Outcomes in the Hospital Industry

Abstract: This paper introduces a random consideration sets model of hospital demand to analyze market interactions while relaxing the assumption that patients necessarily consider all options available from within their contracted networks of providers. A key contribution of the model is its ability to quantify the impact of bounded rationality on equilibrium market outcomes when firms compete for attention. The demand model identifies and estimates the probability that each patient considers and chooses each in-network hospital within a geographic radius of their home. On the supply side, hospitals compete in a two-stage game: (i) with each other for patients’ attention through advertising expenditure, and (ii) with insurers through Nash-in-Nash bargaining over prices. Assuming full consideration in hospital demand biases distance elasticities downward in magnitude, as it fails to account for attention decreasing with distance. Counterfactual simulations show that limited consideration reduces healthcare access and artificially differentiates products, leading to higher average prices and greater price dispersion across hospitals. Insurer-provided nudges through a recommender system can achieve competitive outcomes comparable to those under an unobtainable full consideration scenario. A retrospective merger is used as a natural experiment, providing evidence that accounting for bounded rationality in models of imperfect competition can improve the accuracy of counterfactual predictions.

Presented at: Annual Meeting of the MEA (March 2024), International Industrial Organization Conference (May 2024), North American Summer Meeting of the Econometric Society (June 2024), Graduate Student Conference at WUSTL (October 2024), SEA Annual Meeting (November 2024), AEA Meetings (January 2025)
Slides

Working Papers

Limited Consideration and Time Discounting in Mortgage Refinance Decisions, with Haizhen Lin, Ruli Xiao, and Jun Zhu

Abstract: This paper develops a structural dynamic discrete choice model to analyze how sequential deadline extensions in government mortgage refinancing programs affect borrower behavior, using the Home Affordable Refinance Program (HARP) as a case study. While dynamic discrete choice models are commonly used across various fields to empirically analyze intertemporal decision-making, existing approaches assume that decision-makers pay attention to available choice options each period. Our model relaxes this assumption by separately identifying consideration probabilities, the utility function of each alternative without imposing a normalization, and the discount factor. Preliminary findings reveal that sequential deadline extensions reduce the expected option value of waiting for attentive borrowers, leading to ex-post suboptimal refinancing. These insights extend beyond mortgage markets, offering broader implications for how inattention interacts with the design of government programs involving real-options problems.

How Does Specialty Care Access Affect Preventive Behavior? Evidence from Robotic Surgery Adoption

Abstract: This paper studies how access to advanced medical technologies—specifically, robotic surgery—affects preventive care behavior. I combine a change in U.S. Preventive Services Task Force screening guidelines with staggered hospital-level adoption of robotic surgery to estimate the causal effect of downstream treatment availability on preventive screening. Using a triple-differences design, I find that screening rates increased more in areas with greater access to robotic surgery following the guideline shift. Evidence suggests that this increase is driven by a higher likelihood of patients visiting primary care providers, rather than changes in physician behavior. These findings indicate that the presence of specialized treatment options can increase engagement with preventive care by encouraging patients to initiate contact with the healthcare system.

Teaching

Summer 2023: ECON-E 321 Intermediate Microeconomic Theory (Online)
Fall 2021, Spring 2022, Fall 2022, Spring 2023: ECON-B 251 Fundamentals of Economics for Business I
Spring 2021: ECON-E 201 Introduction to Microeconomics (Online)