
Liran Einav
· Professor of EconomicsVerifiedStanford University · Economics
Active 1998–2026
About
Liran Einav is a professor of economics at Stanford University and the Charles R. Schwab Professor in Economics. He is also a research associate at the National Bureau of Economic Research, where he directs the Industrial Organization Program. His areas of specialization include industrial organization and applied microeconomics. A significant focus of his work is on insurance markets, including the development of empirical models of insurance demand and pricing, as well as empirical analyses of the implications of adverse selection and moral hazard. Much of his current research concentrates on healthcare markets. In addition to his work on insurance and healthcare, he has studied consumer behavior, the pricing of subprime auto loans, competition in the motion picture industry, strategic commitment, and peer-to-peer internet markets. Einav holds an undergraduate degree in computer science and economics from Tel Aviv University and earned his PhD in economics from Harvard University in 2002. He is currently a co-editor at the American Economic Review, having previously served as a co-editor at Econometrica and AEJ Applied.
Research topics
- Microeconomics
- Actuarial science
- Business
- Economics
Selected publications
Customer Overlap and Diversion Ratios
SSRN Electronic Journal · 2026-01-01
preprintOpen access1st authorCorrespondingOn the optimality of deferred public annuities
Journal of Public Economics · 2026-02-25
article1st authorCustomer Overlap and Diversion Ratios
National Bureau of Economic Research · 2026-01-01 · 1 citations
reportOpen access1st authorCorrespondingWe define the concept of customer overlap of product j with product k as the share of j's customers who buy k.We then argue that, in appropriate contexts, customer overlaps are an excellent proxy for diversion ratios, a useful and popular way to summarize competition between sellers of substitute products.Unlike diversion ratios, which are often challenging to estimate, customer overlaps are straightforwardly observed in many data sets.We show theoretically, and then validate empirically, the close connection between customer overlaps and diversion ratios.We then illustrate the potential use of customer overlap in contexts where estimation of diversion ratios could be prohibitive.
Producing Health: Measuring Value Added of Nursing Homes
Econometrica · 2025-01-01 · 5 citations
article1st authorCorrespondingWe develop a stylized model that allows us to estimate a value‐added measure for nursing homes (“SNFs”) which accounts for patient selection both into and out of a SNF. We use the model, together with detailed data on the physical and mental health of about 6 million Medicare SNF patients between 2011 and 2016, to estimate the value added for about 14,000 distinct SNFs. We document substantial heterogeneity in value added. Nationwide, compared to a 10th percentile SNF, a 90th percentile SNF is able to discharge a patient at the same health level almost a week sooner, or one quarter of the median length of stay. Heterogeneity in value added within a market is almost as large as it is nationwide. Our results point to the potential for substantial gains through policies that encourage reallocation of patients to higher‐quality SNFs within their market.
Overlapping Policy Interventions: Evidence from Home Health
National Bureau of Economic Research · 2025-12-01
reportOpen access1st authorCorrespondingGovernments often concurrently deploy multiple policy instruments to tackle a common objective, yet researchers typically analyze each policy's impacts independently.We study interactions across policies and their implications within the context of efforts to reduce Medicare-financed home health services.We consider two geographically targeted policies: strike force prosecutions of suspected fraud and moratoria on the entry of new home health agencies.Depending on location and time, we observe either both, one, or neither policy in place.Individually, each policy reduced home health use substantially, and was well-targeted to places with higher treatment effects.Although we estimate only a modest interaction between the two policies, we find that optimally allocating them across the areas that received at least one policy could have increased their total impact by about 20% relative to the observed placement.Our exercise highlights the potential gains from coordination across different policy instruments pursuing similar objectives.
On the Optimality of Deferred Public Annuities
National Bureau of Economic Research · 2025-10-01
reportOpen access1st authorCorrespondingWhat is the optimal path of Social Security benefits for an individual who has retired with a stock of wealth, faces stochastic mortality, and has no access to annuities and no preferences for bequests?It is a deferred annuity in which the government annuity pays out zero for some periods and a constant amount after that.The optimal length of the deferral period is increasing in the retiree's initial wealth and in their survival probability.
On the Optimality of Deferred Public Annuities
SSRN Electronic Journal · 2025-01-01
preprintOpen accessSenior author2025-01-01
book-chapter1st authorCorrespondingOn the Optimality of Deferred Public Annuities
SSRN Electronic Journal · 2025-01-01
articleOpen access1st authorCorrespondingThe Impact of a Child with Down Syndrome
National Bureau of Economic Research · 2025-07-01
reportOpen access1st authorCorresponding
Recent grants
Determinants of Medical Spending for the Elderly: Insurance, Patients, Providers
NIH · $5.6M · 2009–2020
Estimating Risk and Risk Preferences in Insurance Markets
NSF · $164k · 2005–2007
CAREER: Empirical Analysis of Markets with Adverse Selection
NSF · $400k · 2007–2012
Frequent coauthors
- 226 shared
Amy Finkelstein
National Bureau of Economic Research
- 112 shared
Jonathan Levin
RAND Corporation
- 66 shared
Neale Mahoney
Stanford University
- 38 shared
Ran D. Balicer
Ben-Gurion University of the Negev
- 31 shared
Dan Zeltzer
Tel Aviv University
- 31 shared
Jay Bhattacharya
Stanford University
- 29 shared
Neel Sundaresan
- 24 shared
Vilsa Curto
Harvard University
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