David Laibson

About

David Laibson is the Robert I. Goldman Professor of Economics and a Faculty Dean of Lowell House at Harvard University. His research focuses on behavioral economics, with emphasis on intertemporal choice, self-regulation, behavior change, household finance, public finance, macroeconomics, asset pricing, aging, and biosocial science. Laibson is a member of the National Bureau of Economic Research, where he is a Research Associate in the Aging, Asset Pricing, and Economic Fluctuations Working Groups. He serves on Harvard’s Pension Investment Committee and on the Board of the Russell Sage Foundation, where he chairs the finance committee. Additionally, Laibson serves on the advisory boards of the Social Science Genetics Association Consortium and the Consumer Finance Institute of the Federal Reserve Bank of Philadelphia. He has served as the Chair of the Department of Economics at Harvard University and as a member of the Academic Research Council of the Consumer Financial Protection Bureau. Laibson is a recipient of a Marshall Scholarship and is an elected member of the Econometric Society, the American Academy of Arts and Sciences, the National Academy of Social Insurance, and the National Academy of Sciences. He holds degrees from Harvard University (AB Economics, summa cum laude), the London School of Economics (MSc in Econometrics and Mathematical Economics), and the Massachusetts Institute of Technology (PhD in Economics). He received his PhD in 1994 and has taught at…

Research topics

• Computer Science
• Psychology
• Sociology
• Economics
• Medicine
• Econometrics
• Artificial Intelligence
• Biology
• Information Retrieval
• Business

Selected publications

• Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals

  Nature Genetics · 2022 · 673 citations

  We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI's magnitude of association with EA and other…

  DOI

• A megastudy of text-based nudges encouraging patients to get vaccinated at an upcoming doctor’s appointment

  Proceedings of the National Academy of Sciences · 2021 · 348 citations

  = 47,306) testing 19 nudges delivered to patients via text message and designed to boost adoption of the influenza vaccine. Our findings suggest that text messages sent prior to a primary care visit can boost vaccination rates by an average of 5%. Overall, interventions performed better when they were 1) framed as reminders to get flu shots that were already reserved for the patient and 2) congruent with the sort of communications patients expected to receive from their healthcare provider (i.e.…

  PublisherOA PDFDOI

• Measuring Time Preferences

  Journal of Economic Literature · 2020 · 338 citations

  We review research that measures time preferences-i.e., preferences over intertemporal tradeoffs. We distinguish between studies using financial flows, which we call "money earlier or later" (MEL) decisions and studies that use time-dated consumption/effort. Under different structural models, we show how to translate what MEL experiments directly measure (required rates of return for financial flows) into a discount function over utils. We summarize empirical regularities found in MEL studies an…

  DOI

• Problems with Using Polygenic Scores to Select Embryos

  New England Journal of Medicine · 2021 · 183 citations

  Companies have recently begun to sell a new service to patients considering in vitro fertilization: embryo selection based on polygenic scores (ESPS). These scores represent individualized predictions of health and other outcomes derived from genomewide association studies in adults to partially predict these outcomes. This article includes a discussion of many factors that lower the predictive power of polygenic scores in the context of embryo selection and quantifies these effects for a variet…

  PublisherOA PDFDOI

• Resource profile and user guide of the Polygenic Index Repository

  Nature Human Behaviour · 2021 · 178 citations

  Polygenic indexes (PGIs) are DNA-based predictors. Their value for research in many scientific disciplines is growing rapidly. As a resource for researchers, we used a consistent methodology to construct PGIs for 47 phenotypes in 11 datasets. To maximize the PGIs' prediction accuracies, we constructed them using genome-wide association studies-some not previously published-from multiple data sources, including 23andMe and UK Biobank. We present a theoretical framework to help interpret analyses…

  DOI

Recent grants

• NIH Grant R01AG016605

  NIH · $380k · 2002

• Core C - Measurement and Methods in ADRD and Racial Disparities Research

  NIH · $78.7M · 1997–2029

• Behavioral Intervention Development Core

  NIH · $17.2M · 2009–2029

Frequent coauthors

• James J. Choi

  306 shared

• Brigitte C. Madrian

  Brigham Young University

  293 shared

• Xavier Gabaix

  212 shared

• Daniel J. Benjamin

  University of California, Los Angeles

  212 shared

• John Beshears

  National Bureau of Economic Research

  201 shared

• David Cesarini

  172 shared

• Peter M. Visscher

  University of Cambridge

  139 shared

• Patrick Turley

  University of Southern California

  128 shared

Education

• B.A., Economics

  Harvard University

  1993

• M.A., Economics

  Harvard University

  1994

• Ph.D., Economics

  Harvard University

  1998

Awards & honors

• Marshall Scholarship
• Fellow of the Econometric Society
• Fellow of the American Academy of Arts and Sciences
• TIAA-CREF Paul A. Samuelson Award for Outstanding Scholarly…

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