333 citations · 489 across the 17 of their papers we have counts for
19 papers
Asymptotic Properties of Empirical Quantile-Based Estimators
Julien Chhor, Xavier D'Haultfœuille, Jérémy L'Hour +1
We consider inference for parameters of the form for some variables , and . Such parameters appear, in particular, in the ``changes-in-cha…
Using did_multiplegt_dyn to Estimate Event-Study Effects in Complex Designs: Overview, and Four Examples Based on Real Datasets
Clément de Chaisemartin, Diego Ciccia, Felix Knau +8
The command did_multiplegt_dyn can be used to estimate event-study effects in complex designs with a potentially non-binary and/or non-absorbing treatment. This paper starts by pro…
Treatment-Effect Estimation in Complex Designs under a Parallel-trends Assumption
Clément de Chaisemartin, Xavier D'Haultfœuille
This paper considers the identification of dynamic treatment effects with panel data, in complex designs where the treatment may not be binary and may not be absorbing. We first sh…
Analytic inference with two-way clustering
Laurent Davezies, Xavier D'Haultfœuille, Yannick Guyonvarch
This paper studies analytic inference along two dimensions of clustering. In such setups, the commonly used approach has two drawbacks. First, the corresponding variance estimator…
Linear Regressions with Combined Data
Xavier D'Haultfoeuille, Christophe Gaillac, Arnaud Maurel
We study linear regressions in a context where the outcome of interest and some of the covariates are observed in two different datasets that cannot be matched. Traditional approac…
Is Inference Conditional on Not Rejecting a Pre-test Less Reliable than Unconditional Inference?
Clément de Chaisemartin, Xavier D'Haultfœuille
Researchers often report an estimate and confidence interval only if a specification test does not reject - for example, only if a pre-trend test supports a difference-in-differenc…
Difference-in-Differences Estimators with Continuous Treatments and no Stayers
Clément de Chaisemartin, Xavier D'Haultfœuille, Gonzalo Vazquez-Bare
Many treatments or policy interventions are continuous in nature. Examples include prices, taxes or temperatures. Empirical researchers have usually relied on two-way fixed effect…
Graphon Estimation in bipartite graphs with observable edge labels and unobservable node labels
Etienne Donier-Meroz, Arnak S. Dalalyan, Francis Kramarz +2
Many real-world data sets can be presented in the form of a matrix whose entries correspond to the interaction between two entities of different natures (number of times a web user…
Partially Linear Models under Data Combination
Xavier D'Haultfœuille, Christophe Gaillac, Arnaud Maurel
We study partially linear models when the outcome of interest and some of the covariates are observed in two different datasets that cannot be linked. This type of data combination…
Difference-in-Differences Estimators for Treatments Continuously Distributed at Every Period
Clément de Chaisemartin, Xavier D'Haultfœuille, Félix Pasquier +2
When studying the effects of taxes, tariffs, or prices using panel data, the treatment is often continuously distributed in every period. We develop difference-in-differences (DID)…
Two-Way Fixed Effects and Differences-in-Differences with Heterogeneous Treatment Effects: A Survey
Clément de Chaisemartin, Xavier D'Haultfœuille
Linear regressions with period and group fixed effects are widely used to estimate policies' effects: 26 of the 100 most cited papers published by the American Economic Review from…
Identification and Estimation of Average Causal Effects in Fixed Effects Logit Models
Laurent Davezies, Xavier D'Haultfœuille, Louise Laage
This paper studies identification and estimation of average causal effects, such as average marginal or treatment effects, in fixed effects logit models with short panels. Relating…
Two-way Fixed Effects and Differences-in-Differences Estimators with Several Treatments
Clément de Chaisemartin, Xavier D'Haultfœuille
We study two-way-fixed-effects regressions (TWFE) with several treatment variables. Under a parallel trends assumption, we show that the coefficient on each treatment identifies a…
Difference-in-Differences Estimators of Intertemporal Treatment Effects
Clément de Chaisemartin, Xavier D'Haultfœuille
We study treatment-effect estimation using panel data. The treatment may be non-binary, non-absorbing, and the outcome may be affected by treatment lags. We make a parallel-trends…
Empirical MSE Minimization to Estimate a Scalar Parameter
Clément de Chaisemartin, Xavier D'Haultfœuille
We consider the estimation of a scalar parameter, when two estimators are available. The first is always consistent. The second is inconsistent in general, but has a smaller asympt…
An alternative to synthetic control for models with many covariates under sparsity
Marianne Bléhaut, Xavier D'Haultfoeuille, Jérémy L'Hour +1
The synthetic control method is a an econometric tool to evaluate causal effects when only one unit is treated. While initially aimed at evaluating the effect of large-scale macroe…
Rationalizing Rational Expectations: Characterization and Tests
Xavier D'Haultfoeuille, Christophe Gaillac, Arnaud Maurel
In this paper, we build a new test of rational expectations based on the marginal distributions of realizations and subjective beliefs. This test is widely applicable, including in…
Asymptotic results under multiway clustering
Laurent Davezies, Xavier D'Haultfoeuille, Yannick Guyonvarch
If multiway cluster-robust standard errors are used routinely in applied economics, surprisingly few theoretical results justify this practice. This paper aims to fill this gap. We…
Fuzzy Differences-in-Differences
Clement de Chaisemartin, Xavier D'Haultfoeuille
Difference-in-differences (DID) is a method to evaluate the effect of a treatment. In its basic version, a "control group" is untreated at two dates, whereas a "treatment group" be…