About

I am an Assistant Professor of Economics at Rice University. My areas of research are health economics and empirical industrial organization.

Research topics

• Computer Science
• Actuarial science
• Microeconomics
• Econometrics
• Mathematics
• Mathematical economics
• Economics

Selected publications

• Local population characteristics and access equity of 340B contract pharmacies

  Health Affairs Scholar · 2025-06-11

  articleOpen access1st authorCorresponding

  The 340B Drug Pricing Program allows certain US medical entities with vulnerable patient populations to receive large discounts on outpatient prescriptions and use those savings at the entity's discretion. Since reforms in 2010, the number of pharmacies with whom 340B entities contract grew massively. This article explores the locations of 340B contract pharmacies and corresponding local populations within Texas. We measured and tested for statistical differences in population characteristics between 340B and non-340B pharmacies and the association with other local amenities. We focused on measures of pharmacy accessibility, local population social vulnerability, and local access to other crucial amenities, measures of population well-being previously not investigated in this debate. We found that 340B and non-340B pharmacies are located in fairly similar local populations, but 340B pharmacies are located in statistically significantly less-vulnerable populations than the facilities with which they contract. We found that comparisons of pharmacy accessibility measures are complicated by sensitivity to data sources. Our results suggest that the contract pharmacy program within Texas may target less-vulnerable populations through the shift from covered entity pharmacies to outside pharmacies. Impacts on the target patient population at the covered entity require further research to measure.

  PublisherOA PDFDOI

• Association of Level I and II Trauma Center Expansion With Insurer Payments in Texas From 2011 to 2019

  JAMA Network Open · 2022-03-17

  articleOpen access

  31 189 vs $39 773) in 2019.

  PublisherOA PDFDOI

• Heterogeneous Choice Sets and Preferences

  Econometrica · 2021 · 55 citations

  • Computer Science
  • Econometrics
  • Mathematical economics

  We propose a robust method of discrete choice analysis when agents' choice sets are unobserved. Our core model assumes nothing about agents' choice sets apart from their minimum size. Importantly, it leaves unrestricted the dependence, conditional on observables, between choice sets and preferences. We first characterize the sharp identification region of the model's parameters by a finite set of conditional moment inequalities. We then apply our theoretical findings to learn about households' risk preferences and choice sets from data on their deductible choices in auto collision insurance. We find that the data can be explained by expected utility theory with low levels of risk aversion and heterogeneous non‐singleton choice sets, and that more than three in four households require limited choice sets to explain their deductible choices. We also provide simulation evidence on the computational tractability of our method in applications with larger feasible sets or higher‐dimensional unobserved heterogeneity.

  PublisherOA PDFDOI

• Heterogeneous choice sets and preferences

  2020 · 2 citations

  • Computer Science
  • Computer Science

  We propose a robust method of discrete choice analysis when agents' choice sets are unobserved. Our core model assumes nothing about agents' choice sets apart from their minimum size. Importantly, it leaves unrestricted the dependence, conditional on observables, between agents' choice sets and their preferences. We first characterize the sharp identification region of the model's parameters by a finite set of conditional moment inequalities. We then apply our theoretical findings to learn about households' risk preferences and choice sets from data on their deductible choices in auto collision insurance. We find that the data can be explained by expected utility theory with low levels of risk aversion and heterogeneous choice sets, and that more than three in four households require limited choice sets to explain their deductible choices. We also find that the data are consistent with some models of choice set formation, but not others.

  PublisherOA PDFDOI

• Heterogeneous choice sets and preferences

  2020-09-25 · 12 citations

  reportOpen access

  We propose a robust method of discrete choice analysis when agents' choice sets are unobserved. Our core model assumes nothing about agents' choice sets apart from their minimum size. Importantly, it leaves unrestricted the dependence, conditional on observables, between agents' choice sets and their preferences. We first characterize the sharp identification region of the model's parameters by a finite set of conditional moment inequalities. We then apply our theoretical findings to learn about households' risk preferences and choice sets from data on their deductible choices in auto collision insurance. We find that the data can be explained by expected utility theory with low levels of risk aversion and heterogeneous choice sets, and that more than three in four households require limited choice sets to explain their deductible choices. We also find that the data are consistent with some models of choice set formation, but not others.

  PublisherOA PDFDOI

• Heterogeneous Choice Sets and Preferences

  2019-07-05 · 4 citations

  reportOpen access

  We propose a robust method of discrete choice analysis when agents' choice sets are unobserved. Our core model assumes nothing about agents' choice sets apart from their minimum size. Importantly, it leaves unrestricted the dependence, conditional on observables, between agents' choice sets and their preferences. We first establish that the model is partially identified and characterize its sharp identification region. We also show how the model can be used to assess the welfare cost of limited choice sets. We then apply our theoretical findings to learn about households' risk preferences and choice sets from data on their deductible choices in auto collision insurance. We find that the data can be explained by expected utility theory with relatively low levels of risk aversion and heterogeneous choice sets. We also find that a mixed logit model, as well as some familiar models of choice set formation, are rejected in our data.

  PublisherOA PDFDOI

• Heterogeneous Choice Sets and Preferences

  2019-07-05 · 1 citations

  report

  We propose a robust method of discrete choice analysis when agents' choice sets are unobserved. Our core model assumes nothing about agents' choice sets apart from their minimum size. Importantly, it leaves unrestricted the dependence, conditional on observables, between agents' choice sets and their preferences. We first establish that the model is partially identified and characterize its sharp identification region. We also show how the model can be used to assess the welfare cost of limited choice sets. We then apply our theoretical findings to learn about households' risk preferences and choice sets from data on their deductible choices in auto collision insurance. We find that the data can be explained by expected utility theory with relatively low levels of risk aversion and heterogeneous choice sets. We also find that a mixed logit model, as well as some familiar models of choice set formation, are rejected in our data.

  PublisherDOI

Frequent coauthors

• Joshua C. Teitelbaum

  26 shared

• Levon Barseghyan

  Cornell University

  26 shared

• Francesca Molinari

  Cornell University

  26 shared

• Chuck Houde

  Cornell University

  25 shared

• Aureo Barwick

  Institute for Fiscal Studies

  25 shared

• Matthew Müller

  Rice University

  25 shared

• Lin Thirkettle

  Institute for Fiscal Studies

  25 shared

• Jean-Francois De Paula

  Institute for Fiscal Studies

  25 shared