Stéphane Bonhomme

Professor at the University of Chicago-Department of Economics


I did my PhD at CREST and Université Paris I, under the supervision of Jean-Marc Robin.

You can see my CV HERE.



Econometrics, MicroeconometricsLabour economics.


I teach Econometrics at the graduate level.

You can see some class notes at the bottom of this page.





Working papers

[NEW] Teams: Heterogeneity, Sorting and Complementarity

Keywords: Networks, production, complementarity, sorting. 

Summary: How much do individuals contribute to team output? I propose an econometric framework to quantify individual contributions when only the output of their teams is observed. 

Slides of the presentation at the 2020 World Congress of the Econometric Society.

[NEW] Discussion of "On the Informativeness of Descriptive Statistics for Structural Estimates" by Isaiah Andrews, Matt Gentzkow and Jesse Shapiro

In preparation for Econometrica.  

[NEW] How Much Should We Trust Estimates of Firm Effects and Worker Sorting, (with Thibaut Lamadon, Magne Mogstad, Bradley Setzler, Kerstin Holzheu, and Elena Manresa)

Keywords: Matched employer employee data, worker and firm fixed-effects, sorting.

Summary: We revisit influential conclusions obtained using fixed-effects estimates of worker and firm heterogeneity in wage regression. Using data sources from multiple countries and several econometric methods, we find that conventional estimates suffer from large biases. 

[NEW] Discussion of "Transparency in Structural Research" by Isaiah Andrews, Matt Gentzkow and Jesse Shapiro

In preparation for the Journal of Business and Economic Statistics.  

Keywords:  Model misspecification, robustness, sensitivity analysis, structural models, counterfactuals, latent variables.
Summary: We propose an approach to estimation and inference in the presence of model misspecification.

Keywords: Unobserved heterogeneity, dimension reduction, panel data, structural estimation.
Summary: We develop two-step and iterative estimators based on a discretization of unobserved individual heterogeneity. We view discrete estimators as approximations, and study their properties in environments where population heterogeneity is unrestricted. 
Revision requested at Econometrica

Posterior Average Effects (with Martin Weidner

Keywords:  Model misspecification, robustness, sensitivity analysis, posterior estimators, latent variables.
Summary: We consider the estimation of expectations taken with respect to a latent distribution. We show that posterior estimators, which are computed conditional on the sample, enjoy local and global robustness properties when the latent distribution is misspecified.

Keywords: Unobserved heterogeneity, nonparametric estimation, matching, factor models, optimal transport.
Summary: We propose a matching method based on optimal transport to nonparametrically estimate linear models with independent latent variables. We apply the method to document the cyclicality of permanent and transitory income and wage shocks in the US.

Published and forthcoming papers

A Distributional Framework for Matched Employer Employee Data (with Thibaut Lamadon and Elena Manresa

Econometrica, 87(3), 699-738, May 2019.
Keywords: Matched employer employee data, sorting, job mobility, models of heterogeneity.
Summary: We develop methods to estimate the contributions of firms and workers to earnings dispersion that allow for complementarities and dynamics. 

To appear in The Econometric Analysis of Network Data, edited by B. Graham and A. de Paula.
Keywords: Bipartite graph, network analysis, unobserved heterogeneity.
Summary: We review econometric techniques to analyze bipartite networks. We study fixed-effects, random-effects, and discrete heterogeneity approaches in linear and nonlinear models. We also discuss how to account for endogenous link formation and network dynamics.     

Earnings and Consumption Dynamics: A Nonlinear Panel Data Framework (with Manuel Arellano and Richard Blundell)

Econometrica, 85(3), 693-734, May 2017.

Keywords: Earnings Dynamics, Consumption, Latent Variables.

Summary: We develop a flexible framework to study the nonlinear relationship between shocks to household earnings and consumption over the life cycle.

Replication codes

Nonlinear Persistence and Partial Insurance: Income and Consumption Dynamics in the PSID (with Manuel Arellano and Richard Blundell)

American Economic Review Papers and Proceedings, vol. 108, May 2018

Nonlinear Panel Data Methods for Dynamic Heterogeneous Agent Models (with Manuel Arellano)

Annual Review of Economics, 9, 471-496, August 2017.

Keywords: Dynamic Models, Structural Economic Models, Panel Data, Unobserved Heterogeneity.

Summary: A review of work on identification and estimation of nonlinear dynamic systems and their relationships with structural economic models with heterogeneous agents.

Econometrica, 85(1), 1-28, January 2017.

Keywords: Quantile regression, sample selection, gender wage gap, copula.

Summary: We propose a method to correct quantile regression estimates for sample selection, and apply it to study wage and employment in the UK

Supplementary appendix

Replication codes

Code of the quantile selection estimator (in matlab), to be used on any data set.

Survey on Sample Selection in Quantile Regression (to appear in the Handbook of Quantile Regression), with Manuel Arellano

Nonlinear Panel Data Estimation via Quantile Regressions (with Manuel Arellano)

Econometrics Journal, 19(3), C61-C94, October 2016.

Keywords: Panel data, quantile regression, Expectation-Maximization.

Summary: We introduce a class of quantile regression estimators for short panelsOur correlated random-effects approach uses quantile regressions as flexible tools to model conditional distributions.

Keeping the Econ in Econometrics: (Micro-)Econometrics in the Journal of Political Economy (with A. Shaikh)

Journal of Political Economy (Special Issue on the 125th Anniversary of the Journal), Vol. 125, 6, 1846-1853, December 2017.

Summary: A review of several seminal econometric contributions published by the JPE.


The Cycle of Earnings Inequality: Evidence from Spanish Social Security Data (with Laura Hospido)

Economic Journal, 127, 1244-1278 August 2017.

Keywords: Earnings Inequality, Social Security data, Unemployment, Business cycle.

Summary: We use Spanish Social Security data to document the evolution of earnings inequality since the end of the 1980's.  Male inequality is strongly countercyclical, and partly reflects the effects of the housing boom and bust on the construction sector.

A complement of the paper using tax data is:

Earnings Inequality in Spain: New Evidence Using Tax Data (with Laura Hospido).

Applied Economics, 45, 2013, 4212-4225.

School Characteristics and Teacher Turnover: Assessing the Role of Preferences and Opportunities (with Grégory Jolivet and Edwin Leuven)

Economic Journal, 126(594), 1342-1371, August 2016.

Keywords: labor turnover, compensating differentials, teacher labor markets, sample selection.

Summary: We propose a method to estimate workers' preferences for job amenities using data on job changes. We apply it to administrative data on Dutch primary school teachers.                 

Estimating Multivariate Latent-Structure Models (with Koen Jochmans and Jean-Marc Robin)

Annals of Statistics, 44(2), 540-563, April 2016.

Keywords: finite-mixture models, hidden Markov models, simultaneous matrix diagonalization.

Summary: We develop an approach to identify and estimate latent structure models, such as finite mixture models or hidden Markov models.  


A companion paper is Nonparametric Estimation of Non-Exchangeable Latent Variable Models (with Koen Jochmans and Jean-Marc Robin)

To appear in Journal of Econometrics

Nonparametric Estimation of Finite Mixtures From Repeated Measurements (with Koen Jochmans and Jean-Marc Robin)

Journal of Royal Statistical Society, Series B, 78(1), 211-229, January 2016.

Keywords: finite-mixture models, repeated-measurement data, re-weighting, two-step estimation.

Summary: We develop a practical two-step procedure to nonparametrically estimate finite mixture models from data on repeated measurements.       


Replication files

Grouped Patterns of Heterogeneity in Panel Data (with Elena Manresa)

Econometrica, 83(3), 1147-1184, May 2015.

Keywords: Discrete heterogeneity, panel data, fixed effects, democracy.

Summary: We propose an alternative to fixed-effects estimation in linear panel data regression that allows for group-level time-varying unobservablesWe use this approach to document the evolution of income and democracy in the last part of the XXth century.

Supplementary appendix

Replication files

Stata code to compute the grouped fixed-effects estimator on your data        


Functional Differencing

Econometrica, 80(4), 1337-1385, July 2012.

Keywords: Panel data, incidental parameters, inverse problems.

Summary: We propose a general method (a ``nonlinear within transformation'') to difference out the individual fixed effects in likelihood-based panel data models.

Supplementary appendix

Matlab codes              


Identifying Distributional Characteristics in Random Coefficients Panel Data Models (with Manuel Arellano)

Review of Economic Studies, 79(3), 987-1020, July 2012.

Keywords: Panel data, random coefficients, multiple effects, nonparametric identification.

Summary: We provide identification results and construct estimators for variances, and more generally densities, of individual fixed effects in linear panel data models.

Supplementary appendix

Stata codes                 


Penalized Least Squares Methods for Latent Variables Models

Discussion of papers prepared for the World Congress of the Econometric Society (Shanghai, 2010), 338-352, September 2011.

Keywords: Latent variables models, lasso, penalization.

Summary: A discussion of papers by Susanne Schennach and Victor Chernozhukov. We apply a penalized least squares (``lasso'') density estimator to a simple measurement error model.



Nonlinear Panel Data Analysis (with Manuel Arellano)

Annual Review of Economics, 3, 395-424, 2012.                 

Keywords: Panel data, incidental parameters, partial identification.

Summary: A survey of recent advances in panel data, including a discussion of the computation of random-effects estimators, and partial identification. 


Recovering Distributions in Difference-in-Differences: A Comparison of Selective and Comprehensive Schooling (with Ulrich  Sauder)

Review of Economics and Statistics93(2), 479–494, May 2011.

Keywords: Selective education, difference-in-differences, treatment effects, quantiles.

Summary: We introduce a method to estimate distributions of potential outcomes in difference-in-differences models. We apply it to study the effect of selective secondary education in the UK.

WP version

Stata codes

Generalized Nonparametric Deconvolution with an Application to Earnings Dynamics (with Jean-Marc Robin) 

Review of Economic Studies, 77(2), 491-533, April 2010.

Keywords: Factor models, nonparametric deconvolution, earnings dynamics.

Summary: We propose a nonparametric estimator of factor distributions in linear factor independent factor models. We use it to estimate the distribution of earnings shocks in a simple permanent/transitory model, on PSID data.

Gauss codes

The Pervasive  Absence of Compensating Differentials (with Grégory Jolivet)

Journal of Applied Econometrics, 24(5), 763-795, June 2009.

Keywords: Compensating wage differentials, job mobility, amenities.

Summary: We build and estimate a structural job search model of wages, non-wage amenities, and job mobility on European data. We find strong preferences for some amenities, which are not reflected in wage/amenity correlations.

Consistent Noisy Independent Component Analysis (with Jean-Marc Robin)

Journal of Econometrics, 149(1), 12-25, April 2009.

Keywords: Factor analysis, Independent Component Analysis, higher-order moments.

Summary: We propose a method to estimate linear independent factor models using higher-order moments. We apply it to schooling data on test scores, and to the Fama-French data on stock returns. 

Supplementary appendix

Gauss codes for the ``quasi-JADE'' estimator


Robust Priors in Nonlinear Panel Data Models (with Manuel Arellano)

Econometrica, 77(2), 489-536, March 2009.

Keywords: Panel data, integrated likelihood, bias reduction

Summary: We show under which condition panel data integrated likelihood estimators reduce first-order bias on common parameters and average marginal effects. Our framework covers fixed-effects, random-effects, and Bayesian approaches as special cases.   

Supplementary appendix

Robust Priors for Average Marginal Effects: Comment


Assessing the Equalizing Force of Mobility Using Short Panels: France, 1990-2000 (with Jean-Marc Robin)

Review of Economic Studies, 76(1), 63-92, January 2009.

Keywords: Inequality, mobility, earnings dynamics, copula.

Summary: We build a model of earnings dynamics that combines a flexible modelling of the marginal distributions (inequality) with a tight parameterization of the dynamics (mobility). We use it to compute inequality in Present Values. We estimate the model on the French Labor Force Survey.

Stata do-file




Standard Errors Estimation in Mixtures of Partial Likelihood Models

Keywords: EM algorithm, standard errors.

Summary: A simple method to estimate asymptotic standard errors of sequential EM estimators, using the generalized information identity.




Statistical Methods in Econometrics


1. Preliminaries

2. Univariate Distributions

3. Multivariate Distributions

4. Moments

5. Sampling

6. Asymptotic Theory

7. Estimation

8. Tests of Hypotheses

9. Regression




1. Introduction

2. The Linear Model

3. Maximum Likelihood and asymptotic tests

4. Stochastic Processes

5. Regression with Dependent Data

6. Endogeneity

7. Generalized Method of Moments

8. Limited Dependent Variables

9. Introduction to Panel Data

10. Nonparametric Regression


A gentle introduction to quantile regression