Evan D. Peet

Evan D. Peet
Economist; Co-director, RAND Center for Causal Inference; Professor, Pardee RAND Graduate School
Off Site Office

Education

Ph.D. in economics, Duke University; M.A. in economics, Duke University; B.A. in economics, math, statistics, Brigham Young University

Media Resources

This researcher is available for interviews.

To arrange an interview, contact the RAND Office of Media Relations at (310) 451-6913, or email media@rand.org.

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Overview

Evan Peet (he/him/his) is an economist at the RAND Corporation, co-director of the RAND Center for Causal Inference, and a professor of policy analysis at the Pardee RAND Graduate School. His research focuses on health, human capital, labor, and environmental policy. His current research focuses on maternal and child health, and the opioid crisis. Previous focuses of his research include: COVID-19, pollution, health service utilization, social service utilization, child development, educational reforms, long-term labor market outcomes, and more. His research is policy oriented, seeking to understand the optimal design, targeting, and implementation of policies to improve outcomes. Peet is an expert in causal inference, econometrics, machine learning, and predictive modeling. As an example, he is currently leading efforts to integrate causal inference and predictive methods within healthcare and social service provider systems to alert providers to patient risks of poor maternal and child health outcomes, and to provide individualized intervention recommendations to reduce risks. Prior to joining RAND, Peet received his Ph.D. in economics from Duke University and completed a postdoctoral fellowship in global and environmental health at Harvard University’s T.H. Chan School of Public Health.

Recent Projects

  • Prediction and Reduction of Infant Mortality in Allegheny County
  • Measures and Methodology for International Comparisons of Health Care System Performance,
  • Improving Naloxone Access and Its Effects on Drug Abuse and Overdoses
  • Improving Maternal Health Outcomes: Targeting Resources to Areas Based on Standardized Empirical Measures of Need
  • The Effects of Opioid Supply-Side Policies on Substitutionary Prescribing and Health

Selected Publications

Evan D. Peet, "Early-life Environment and Human Capital: Evidence from the Philippines," Environment and Development Economics, 26(1), 2020

Vermeer, Michael J. D., Evan D. Peet, Securing Communications in the Quantum Computing Age: Managing the Risks to Encryption, RAND Corporation (RR-3102), 2020

Evan Peet, Gunther Fink, and Wafaie Fawzi, "Returns to Education in Developing Countries: Evidence from the Living Standards and Measurement Study Surveys," Economics of Education Review

Evan Peet, Dana C. McCoy, Goodarz Danaei, Majid Ezzati, Wafaie Fawzi, Marjo-Riitta Jarvelin, Demetris Pillas, Gunther Fink, "Early Childhood Development and Schooling Attainment: Longitudinal Evidence from British, Finnish and Philippine Birth Cohorts," PLOS One

Gunther Fink, Evan Peet, Goodarz Danaei, Kathryn Andrews, Dana Charles McCoy, Christopher R Sudfeld, Mary C Smith Fawzi, Majid Ezzati, and Wafaie W Fawzi, "Schooling and Wage Income Losses Due to Early Childhood Growth Faltering in Developing Countries: National, Regional and Global Estimates," The American Journal of Clinical Nutrition

Dana Charles McCoy, Evan D. Peet, Majid Ezzati, Goodarz Danaei, Maureen M. Black, Christopher R. Sudfeld, Wafaie Fawzi, Günther Fink, "Early Childhood Developmental Status in Low- and Middle-Income Countries: National, Regional and Global Estimates," PLOS Medicine

Lilian Perez, Evan D. Peet, Brain Vegetabile, Regina Shih, "Risk Factors for Childhood Stunting in 137 Developing Countries: A Comparative Risk Assessment Analysis at Global, Regional, and Country Levels,," PLOS Medicine, 32(2), 2022

Peet, Evan D., Dana Schultz, and Susan L. Lovejoy, Using an Innovative Database and Machine Learning to Predict and Reduce Infant Mortality, RAND Corporation (RB-A858-1), 2021

Recent Media Appearances

Interviews: PainRelief.com

Commentary

  • Data Analysis

    Equitable Data Analysis: Lessons from a COVID-19 Research Collaborative

    The health inequities exposed by COVID-19 underscored the importance of collecting race-stratified data to inform local policymakers. For the public health researchers trying to provide that, the pandemic also revealed some major pitfalls, especially about relying on open-source data.

    Jul 27, 2021

    The RAND Blog

  • Global Climate Change

    Adapting to a Hotter World

    Because climate change is largely irreversible, mitigation alone won't solve the problem. While mitigation will prevent even greater, future climatic changes, adaptation — efforts to adjust to climate change's effects — will prepare the world for a new set of living conditions, whatever they may be.

    Oct 2, 2015

    U.S. News & World Report

Publications