2 citations · 6 across the 9 of their papers we have counts for
9 papers · 1 filter
Difference-in-Differences Models in the Presence of Time-Varying Mediators and Lagged outcomes
Kyunghoon Ban, Zhengrun Chen, Désiré Kédagni
We study difference-in-differences (DiD) designs in which a binary treatment changes an endogenous time-varying (continuous, discrete, or mixed) mediator that in turn affects an ou…
Testing Identifying Assumptions in Parametric Separable Models: A Conditional Moment Inequality Approach
Leonard Goff, Désiré Kédagni, Huan Wu
In this paper, we propose a simple method for testing identifying assumptions in parametric separable models, namely treatment exogeneity, instrument validity, and/or homoskedastic…
and : Stata commands for robust difference-in-differences
Kyunghoon Ban, Désiré Kédagni
This article provides a Stata package for the implementation of the robust difference-in-differences (RDID) method developed in Ban and Kédagni (2023). It contains three main comma…
Robust Identification in Randomized Experiments with Noncompliance
Désiré Kédagni, Huan Wu, Yi Cui
Instrument variable (IV) methods are widely used in empirical research to identify causal effects of a policy. In the local average treatment effect (LATE) framework, the IV estima…
Evaluating the Impact of Regulatory Policies on Social Welfare in Difference-in-Difference Settings
Dalia Ghanem, Désiré Kédagni, Ismael Mourifié
Quantifying the impact of regulatory policies on social welfare generally requires the identification of counterfactual distributions. Many of these policies (e.g. minimum wages or…
Robust Difference-in-differences Models
Kyunghoon Ban, Désiré Kédagni
The difference-in-differences (DID) method identifies the average treatment effects on the treated (ATT) under mainly the so-called parallel trends (PT) assumption. The most common…
Misclassification in Difference-in-differences Models
Augustine Denteh, Désiré Kédagni
The difference-in-differences (DID) design is one of the most popular methods used in empirical economics research. However, there is almost no work examining what the DID method i…
Local Average and Marginal Treatment Effects with a Misclassified Treatment
Kyunghoon Ban, Désiré Kédagni, Santiago Acerenza
This paper studies identification of the local average and marginal treatment effects (LATE and MTE) with a misclassified binary treatment variable. We derive bounds on the (genera…
Discordant Relaxations of Misspecified Models
Lixiong Li, Désiré Kédagni, Ismaël Mourifié
In many set-identified models, it is difficult to obtain a tractable characterization of the identified set. Therefore, researchers often rely on non-sharp identification condition…