Journal Articles

Testing and Relaxing the Exclusion Restriction in the Control Function Approach

In a nonparametric triangular structure typical of the control function literature, and provided the instrument satises a “local irrelevance” condition, we show that we can test the exclusion restriction. Second, if the “instrument” also directly affects the outcome variable, we show that the identication of average causal effects can be achieved in linear random coefficients models and single index models.

(Find here Y. Sasaki’s webpage for the Stata command testex implementing our test of the exclusion restriction)

Stefan Hoderlein, Yuya Sasaki, forthcoming in Journal of Econometrics
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Empirical Process Results for Exchangeable Arrays

We show the weak convergence of empirical processes and some bootstrap processes with multiadic (e.g., dyadic) data or multiway clustering. These results imply asymptotic normality and the validity of the bootstrap for a large class of nonlinear estimators. We illustrate our results with trade data.

The last version of the WP can be found here:

(this paper supersedes our previous paper “Asymptotic results under multiway clustering”).

with Laurent Davezies and Yannick Guyonvarch (2021), Annals of Statistics (49)
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Rationalizing Rational Expectations: Characterization and Tests

We construct the best possible test of rational expectations (RE) when we observe expectations on future variables on a certain sample, and realizations of that variable on another sample of different units. we apply our methodology to test for RE about future earnings.

You can find the corresponding R package here:

Note: this version supersedes “Rationalizing Rational Expectations: Tests and Deviations” (v1 on arXiv), which also considers deviations from RE.

with Christophe Gaillac and Arnaud Maurel (2021), Quantitative Economics (12).
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Segregsmall: A command to estimate segregation in the presence of small units

The Stata command Segregsmall estimates usual segregation indices (e.g. Duncan or Theil) when units (=geographical areas, firms, classrooms…) are small. In such cases, naive estimators are biased upwards. The command computes in particular the estimators described in R. Rathelot’s JBES paper and in our join, QE paper.

with Lucas Girard and Roland Rathelot (2021), Stata Journal (21)
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The Provision of Wage Incentives: A Structural Estimation Using Contracts Variation

To what extent do people react to incentives? Are observed contracts (nearly) optimal? We answer to these questions using a nonparametric principal agent model and an exogenous variation in contracts between the French national institute of statistics and its interviewers.

with Philippe Février (2020), Quantitative Economics (11).
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Estimating Selection Models without Instrument with Stata

This paper presents the Stata command eqregseg, which computes the extremal quantile regression estimator for sample selection developed in our paper “Extremal Quantile Regressions for Selection Models and the Black-White Wage Gap”.

with Arnaud Maurel, Xiaoyun Qiu and Yichong Zhang (2020), Stata Journal (20).
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Two-way fixed effects estimators with heterogeneous treatment effects

We show that if treatment effects are not constant, regressions with groups and time fixed effects identify weighted averages of treatment effects across groups and time periods, with potentially (many) negative weights. We suggest sensitivity checks and better estimands under testable restrictions on the design.

See for the last WP version

with Clément de Chaisemartin (2020), American Economic Review (110).
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A cautionary tale on instrument vector calibration for the treatment of unit nonresponse in surveys

We show that the calibration method based on instruments, proposed by Deville (2002), leads to a large variance when the instrumental variable are poorly related to the calibrating variables. If the exclusion restriction is violated, the bias is also large under the same condition.

with David Haziza and Eric Lesage (2019). Journal of the American Statistical Association (114).
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Fuzzy differences-in-differences with Stata

This paper presents the Stata command fuzzydid, which computes various estimators of the LATE and LQTE for fuzzy DID designs, following our paper “Fuzzy DID”. It can handle non-binary treatments, multiple periods and groups, covariates and partial identification.

Fuzzydid Stata package available from the SSC repository. You can find the files to replicate the application on Clément’s webpage.

with Clément de Chaisemartin and Yannick Guyonvarch (2019). Stata Journal (19)
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Automobile Prices in Market Equilibrium with Unobserved Price Discrimination

We consider inference on a demand and supply model for differentiated products with price discrimination that is unobserved by the econometrician. We show how to extend BLP’s GMM estimation to this setting, using restrictions on marginal costs. We apply our framework to the French automobile market.

with Isis Durrmeyer and Philippe Février (2019), Review of Economic Studies (86).
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Extremal Quantile Regressions for Selection Models and the Black-White Wage Gap

We consider models with endogenous selection and no instrument nor large support regressors. Identification relies on the independence between the covariates and selection, when the outcome tends to infinity. We propose a simple estimator based on extremal quantile regressions and apply it to the evolution of the black-white wage gap in the US.

with Arnaud Maurel and Yichong Zhang (2018). Journal of Econometrics (203).
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Fuzzy Differences-in-Differences

In many applications of the DID method, the treatment rate only increases more in the treatment group. In such fuzzy designs, we show that the popular “Wald-DID” (the DID of the outcome divided by the DID of the treatment) identifies a LATE only if two homogeneous treatment effect assumptions hold. We then propose two alternative estimands that do not rely on such assumptions.

with Clément de Chaisemartin (2018) Review of Economic Studies (85)
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Measuring Segregation on Small Units: A Partial Identification Analysis

Suppose that an individual in a small unit j (a classroom, a small firm…) belongs to a minority with a probability pj. To measure segregation of this minority, one would ideally use an inequality index on the pj, but they are unobserved. Using the observed proportion instead leads to an overestimation. The segregation indices are actually partially identified. We provide tractable bounds and develop inference.

The supplement and code can be found following the link to the journal’s website.

with Roland Rathelot (2017). Quantitative Economics (8)
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Identification of Additive and Polynomial Models of Mismeasured Regressors Without Instruments

Suppose that Y = g(X*) + h(Z) + U, E(U|X*,Z)=0 but X* is measured with error. We show that g and h can be identified nonparametrically without side information provided that, basically, Z affects X*. A similar result holds when Y=P(X*,Z) + U, with P polynomial.

with Dan Ben-Moshe and Arthur Lewbel (2017). Journal of Econometrics (200).
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A Convenient Method for the Estimation of the Multinomial Logit Model with Fixed Effects

We propose a computationally convenient alternative to the conditional MLE for fixed effect multinomial logit models.

The Matlab code can be found here.

with Alessandro Iaria (2016), Economics Letters (141).
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Disentangling Sources of Vehicle Emissions Reduction in France: 2003-2008

We study the factors of the decrease in average CO2 emissions of new cars in France between 2003 and 2008. We show that the evolution of consumers’ preferences account for 43% of this decrease, and that these changes follow two environmental policies put in place during this period.

with Isis Durrmeyer and Philippe Février (2016). International Journal of Industrial Organization (47).
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Identification of Nonseparable Triangular Models with Discrete Instruments

Consider a model Y = g(X,U) with X endogenous, and suppose that we have instruments Z such that X = h(Z,V). If Z is independent of (U,V) and  both g(X,.) and h(Z,.) are strictly monotonic, then g can be partially or pointly identified if Z is binary. It is fully identified in general if Z takes three values or more.

with Philippe Février. Econometrica (83)
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Identification of Mixture Models Using Support Variation

Suppose that observed variables (X1,…,XK) are independent conditional on a continuous and unobserved variable X*. We show that the distributions of Xi conditional on X* are identified if the bounds of the conditional support of Xi are strictly increasing with X*. We also develop a test of this condition.

with Philippe Février (2015). Journal of Econometrics (189).
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The Environmental Effect of Green Taxation: the Case of the French “Bonus/Malus”

In 2008 was introduced in France a feebate system for new automobiles. We investigate the effect of this policy on CO2 emissions. We find that the policy actually led to an increase in these emissions, mostly because of a substantial increase in the sales of new automobiles.

with Pauline Givord and Xavier Boutin (2014), Economic Journal (Features, 124).
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La régression quantile en pratique

This article (in French) is an introduction to quantile regression, with an emphasis on its interpretation.

with Pauline Givord (2014), Economie et Statistique (471)
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Another Look at Identification at Infinity of Sample Selection Models

The sample selection model can be identified without instrument if basically, the probability of selection, conditional on the potential outcome and covariates, does not depend on covariates as the potential outcome tends to infinity.

with Arnaud Maurel (2013), Econometric Theory (29).
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Inference on an Extended Roy Model, with an Application to Schooling Decisions in France

Consider an extended Roy model where a binary decision depends on expected gains and an unobserved cost. The model is identified without instruments if, basically, the unobserved cost only depends on covariates. Applying our results to French data, we show that nonpecuniary components are a key factor for going to college.

with Arnaud Maurel (2013), Journal of Econometrics (174)
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On the Completeness Condition for Nonparametric Instrumental Problems

Sufficient conditions for the completeness condition (E(g(X)|Z) = 0 => g(X)=0) used in nonparametric IV problems are given. It holds in particular under a large support condition on n(Z) and technical restrictions on V in the generalized additive model X = m(n(Z) + V).

2011, Econometric Theory (27)
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Le coût du bonus/malus écologique : que pouvait-on prédire ?

(in French)

with Isis Durrmeyer and Philippe Février (2011), Revue Economique (62)
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A New Instrumental Method for Dealing with Endogenous Selection

Consider the sample selection model under the nonstandard IV restriction that D is independent of Z conditional on Y. Nonparametric identification is achieved under a completeness condition between Y and Z. Partial identification can also be obtained if one replaces independence by monotonicitiy restrictions.

2010, Journal of Econometrics, 154
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Identification of Peer Effects Using Group Size Variation

A linear-in-means model close to the one of Manski (1993) is identified provided that we observe groups with three distinct sizes. This applies even if one does not observe all members of the group, and can also be extended to binary outcomes.

with Laurent Davezies and Denis Fougère (2009), The Econometrics Journal, 12(3), 397-413.
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Measuring the Evolution of Complex Indicators: Theory and Application to the Poverty Rate in France

with Fabien Dell (2008), Annals of Economics and Statistics (90)
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