Recent Submissions
Instrumental Variable Regression with Varying-intensity Repeated Treatments with Jaerim Choi and Dakyung Seong, R&R at Journal of Econometrics
Abstract: Instrumental variable models with repeated endogenous treatments are popular in empirical research using pooled cross-sectional or short panel datasets. This paper proposes a novel semi-parametric approach that explicitly considers treatment effect dynamics by allowing for 1) path-dependency in the contemporaneous treatment effect and 2) a direct carryover effect from last period's treatment. We show that if either of these new features is present, the textbook two-stage least-squares estimator is generally invalid. We apply the proposed semi-parametric estimation and inference approach to revisit the work of Acemoglu et al. (2016). Using industry-level data, we find that the magnitude of contemporaneous impact of increased Chinese import competition on US manufacturing employment depends on an industry's past import exposure. In particular, industries with larger trade shocks in the 1990s tend to experience stronger impacts from contemporaneous trade shocks in the 2000s.
Dynamic Difference-in-Discontinuities, with Dakyung Seong, submitted
Abstract: The difference-in-discontinuities (diff-in-disc design) is a widely used empirical framework to address identification failures in the traditional regression discontinuity (RD) design due to a recurring confounding treatment that utilizes the same policy eligibility cutoff as the new policy of interest. This paper formalizes the repeated treatment nature of the diff-in-disc design within a general potential outcome framework. The new framework accounts for both treatment effect heterogeneity and dynamic treatment effects, including carryover effects and path-dependency in contemporaneous effects. Both standard sharp and fuzzy diff-in-disc setups are considered. We propose new identification and estimation strategies for different scenarios and study the small sample performance of proposed estimators using Monte Carlo simulations. The proposed method is applied to the seminal study of Grembi et al. (2016) on the impact of relaxing fiscal rules. The application illustrates how the proposed methods complement the existing approach.
Forthcoming
Dynamic Regression Discontinuity under Treatment Effect Heterogeneity with Yu-Chin Hsu, Quantitative Economics, accepted
Abstract: Regression discontinuity (RD) is a popular tool for the analysis of economic policies or treatment interventions. This research extends the classic static RD model to a dynamic framework, where observations are eligible for repeated RD experiments and, therefore, treatments. Such dynamics often complicate the identification and estimation of longer-term average treatment effects. Previous empirical papers with such designs typically ignored the dynamics in the model or adopted restrictive identifying assumptions. This paper presents identification strategies under various sets of weaker identifying assumptions and proposes associated estimation and inference methods. The proposed methods are applied to revisit the effect of California local school bonds in the seminal study of Cellini et al. (2010).
Working Papers/Projects
Robust Regression Discontinuity Extrapolation, with Yu-Chin Hsu, Ying-Ying Lee, and Takuya Ura
Long-run Direct vs. Total Effects in Panel Models with Endogenous Varying-intensity Treatments, with Jaerim Choi and Dakyung Seong
Dynamic Treatment Effect with Endogenous Participation Decisions, with Yu-Chin Hsu and Yu-Chang Chen
Lack of Identification Diagnostics in GMM Contexts with Stephen G. Donald and Yu-Chin Hsu
Publications
Inference on Optimal Treatment Assignment with Tim Armstrong, Japanese Economic Review , 2023
Instrumental Variable Estimation With First-stage Heterogeneity with Alberto Abadie and Jiaying Gu, Journal of Econometrics, 2023
A Censored Maximum Likelihood Approach to Quantifying Manipulation in China's Air Pollution Data with Dalia Ghanem and Junjie Zhang, Journal of Association of Environmental and Resource Economics, 2020
Two-sample Instrumental Variables Regression with Potentially Weak Instruments with Jaerim Choi, Stata Journal, 2020
Stata addon weaktsiv can be installed on Stata
Testing for Treatment Effect Heterogeneity in Regression Discontinuity Design with Yu-Chin Hsu, Journal of Econometrics, 2019
Weak-instrument Robust Inference for Two-sample Instrumental Variables Regression with Jaerim Choi and Jiaying Gu, Journal of Applied Econometrics, 2018
Testing for Rank Invariance or Similarity in Program Evaluation with Yingying Dong, Review of Economics & Statistics, 2018
Oracle and Adaptive False Discovery Rate Controlling Methods for One-sided Testing: Theory and Application in Treatment Effect Evaluation with Jiaying Gu, Econometric Journal, 2018
Estimation and Inference of Distributional Partial Effects: Theory and Application Journal of Business & Economic Statistics, 2019
Distributional Tests for Regression Discontinuity: Theory and Empirical Examples with Xiaohan Zhang, Review of Economics & Statistics, 2016
Estimation of Censored Panel-data Models with Slope Heterogeneity with Jason Abrevaya, Journal of Applied Econometrics, 2014