About

Bo Honoré is the Class of 1913 Professor of Political Economy and Professor of Economics at Princeton University. His research focuses on econometrics. He earned his Ph.D. at the University of Chicago and has taught at Northwestern University. Additionally, he has held Visiting Positions at the University of Chicago and the University of Copenhagen. Throughout his career, Professor Honoré has served in various administrative roles at Princeton, including Director of Graduate Studies, Director of Graduate Admissions, Director of the Gregory C. Chow Econometric Research Program, Associate Chair, and Chair of the Department of Economics. He is a Fellow of the Econometric Society and a Member of the American Academy of Arts and Sciences. His accolades include the Richard E. Quandt Teaching Prize awarded in 2012 and 2018, and the Rigmor and Carl Holst-Knudsen Award for Scientific Research from the University of Aarhus in 2017. He has also been a member of the Board of Trustees of the Danish National Research Foundation.

Research topics

• Computer Science
• Statistics
• Mathematics
• Econometrics
• Artificial Intelligence
• Applied mathematics
• Physics
• Mathematical optimization
• Economics

Selected publications

• Composition-Adjusted Wage Growth: A Robust Measure from Microdata

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access1st authorCorresponding
  PublisherDOI

• Composition-Adjusted Wage Growth: A Robust Measure from Microdata

  2025-01-01

  reportOpen access1st authorCorresponding

  Wage growth is a key indicator of labor market conditions, but common measures often conflate individual wage changes with shifts in workforce composition.This paper develops a composition-adjusted measure of wage growth using nonparametric decomposition and program evaluation methods.The adjusted measure tracks unadjusted growth in stable periods but diverges during disruptions: during the Covid-19 pandemic, wage growth falls from 12% to 6% after adjustment.The method accommodates rich covariates, is robust to data quality issues such as rounding, heaping and top-coding, and enables distributional and subgroup analysis using micro data, offering more accurate views of underlying wage dynamics.

  PublisherDOI

• Dynamic ordered panel logit models

  Quantitative Economics · 2025-01-01

  preprintOpen access1st authorCorresponding

  This paper studies a dynamic ordered logit model for panel data with fixed effects. The main contribution of the paper is to construct a set of valid moment conditions that are free of the fixed effects. The moment functions can be computed using four or more periods of data, and the paper presents sufficient conditions for the moment conditions to identify the common parameters of the model, namely the regression coefficients, the autoregressive parameters, and the threshold parameters. The availability of moment conditions suggests that these common parameters can be estimated using the generalized method of moments, and the paper documents the performance of this estimator using Monte Carlo simulations and an empirical illustration to self‐reported health status using the British Household Panel Survey.

  PublisherDOI

• IV Estimation of Panel Data Tobit Models with Normal Errors

  arXiv (Cornell University) · 2024-01-09 · 1 citations

  preprintOpen access1st authorCorresponding

  Amemiya (1973) proposed a ``consistent initial estimator'' for the parameters in a censored regression model with normal errors. This paper demonstrates that a similar approach can be used to construct moment conditions for fixed--effects versions of the model considered by Amemiya. This result suggests estimators for models that have not previously been considered.

  PublisherOA PDFDOI

• Moment Conditions for Dynamic Panel Logit Models with Fixed Effects

  The Review of Economic Studies · 2024-10-10 · 4 citations

  articleOpen access1st authorCorresponding

  Abstract This paper investigates the construction of moment conditions in discrete choice panel data with individual-specific fixed effects. We describe how to systematically explore the existence of moment conditions that do not depend on the fixed effects, and we demonstrate how to construct them when they exist. Our approach is closely related to the numerical “functional differencing” construction introduced in a seminal paper by Bonhomme, but our emphasis is to find explicit analytic expressions for the moment functions. We first explain the construction and give examples of such moment conditions in various models. Then, we focus on the dynamic binary choice logit model and explore the implications of the moment conditions for the identification and estimation of the model parameters that are common to all individuals.

  PublisherOA PDFDOI

• Simultaneity in binary outcome models with an application to employment for couples

  Empirical Economics · 2023-05-04

  articleOpen access1st authorCorresponding

  Two of Peter Schmidt's many contributions to econometrics have been to introduce a simultaneous logit model for bivariate binary outcomes and to study estimation of dynamic linear fixed effects panel data models using short panels. In this paper, we study a dynamic panel data version of the bivariate model introduced in Schmidt and Strauss (Econometrica 43:745-755, 1975) that allows for lagged dependent variables and fixed effects as in Ahn and Schmidt (J Econom 68:5-27, 1995). We combine a conditional likelihood approach with a method of moments approach to obtain an estimation strategy for the resulting model. We apply this estimation strategy to a simple model for the intra-household relationship in employment. Our main conclusion is that the within-household dependence in employment differs significantly by the ethnicity composition of the couple even after one allows for unobserved household specific heterogeneity.

  PublisherOA PDFDOI

• Simultaneity in binary outcome models with an application to employment for couples

  Advanced studies in theoretical and applied econometrics · 2023-05-04

  book-chapterOpen access1st authorCorresponding

  Abstract Two of Peter Schmidt’s many contributions to econometrics have been to introduce a simultaneous logit model for bivariate binary outcomes and to study estimation of dynamic linear fixed effects panel data models using short panels. In this paper, we study a dynamic panel data version of the bivariate model introduced in Schmidt and Strauss (Econometrica 43:745–755, 1975) that allows for lagged dependent variables and fixed effects as in Ahn and Schmidt (J Econom 68:5–27, 1995). We combine a conditional likelihood approach with a method of moments approach to obtain an estimation strategy for the resulting model. We apply this estimation strategy to a simple model for the intra-household relationship in employment. Our main conclusion is that the within-household dependence in employment differs significantly by the ethnicity composition of the couple even after one allows for unobserved household specific heterogeneity.

  PublisherOA PDFDOI

• Analytic and bootstrap-after-cross-validation methods for selecting penalty parameters of high-dimensional M-estimators

  2022-01-11

  reportOpen access

  We develop two new methods for selecting the penalty parameter for the 1 -penalized high-dimensional M-estimator, which we refer to as the analytic and bootstrap-aftercross-validation methods.For both methods, we derive nonasymptotic error bounds for the corresponding 1 -penalized M-estimator and show that the bounds converge to zero under mild conditions, thus providing a theoretical justification for these methods.We demonstrate via simulations that the finite-sample performance of our methods is much better than that of previously available and theoretically justified methods.

  PublisherOA PDFDOI

• Moment conditions for dynamic panel logit models with fixed effects

  2022-12-01 · 7 citations

  preprintOpen access1st authorCorresponding

  This paper investigates the construction of moment conditions in discrete choice panel data with individual specific fixed effects. We describe how to systematically explore the existence of moment conditions that do not depend on the fixed effects, and we demonstrate how to construct them when they exist. Our approach is closely related to the numerical "functional differencing" construction in Bonhomme ( We first explain the construction and give examples of such moment conditions in various models. Then, we focus on the dynamic binary choice logit model and explore the implications of the moment conditions for identification and estimation of the model parameters that are common to all individuals.

  PublisherOA PDFDOI

• Sample Selection Models Without Exclusion Restrictions: Parameter Heterogeneity and Partial Identification

  2022-01-01

  reportOpen access1st authorCorresponding

  This paper studies semiparametric versions of the classical sample selection model (Heckman (1976, 1979)) without exclusion restrictions. We extend the analysis in Honor'e and Hu (2020) by allowing for parameter heterogeneity and derive implications of this model. We also consider models that allow for heteroskedasticity and briefly discuss other extensions. The key ideas are illustrated in a simple wage regression for females. We find that the derived implications of a semiparametric version of Heckman's classical sample selection model are consistent with the data for women with no college education, but strongly rejected for women with a college degree or more.

  PublisherOA PDFDOI

Frequent coauthors

• Áureo de Paula

  72 shared

• Hiroaki Kaido

  49 shared

• Daniele Ballinari

  49 shared

• Ulrich Mueller

  University of California, Berkeley

  49 shared

• Enrico De Giorgi

  University of California, Berkeley

  49 shared

• Yi Zhang

  Courant Institute of Mathematical Sciences

  49 shared

• Andrin Pelican

  49 shared

• Gabriel Okasa

  Swiss National Science Foundation

  49 shared

Awards & honors

• The Richard E. Quandt Teaching Prize in 2012 and 2018
• The Rigmor and Carl Holst-Knudsen Award for Scientific Resea…
• Fellow of the Econometric Society
• Member of the American Academy of Arts and Sciences