报告详情

Details

主题Title

Wild Bootstrap Inference for Instrumental Variables Regressions with Weak and Few Clusters

01报告人Speaker<<<<

王文杰 助理教授 南洋理工大学

02主持人Chair<<<<

刘达禹 副教授 吉林大学

03时间Time<<<<

September/28/2022

9：00(UTC+8)

04地点Venue<<<<

ZOOM ID: 9625852673

报告摘要

Abstract

We study the wild bootstrap inference for instrumental variable regressions with a small number of large clusters. We first show that the wild bootstrap Wald test controls size asymptotically up to a small error as long as the parameters of endogenous variables are strongly identified in at least one of the clusters and has power against local alternatives if the parameters of endogenous variables are strongly identified in five or six clusters. We further develop a wild bootstrap Anderson-Rubin test for the full-vector inference and show that it controls size asymptotically even under weak identification in all clusters. We illustrate their good performance using simulations and provide an empirical application to a well-known dataset about US local labor markets.

报告人介绍

Introduction

王文杰，新加坡南洋理工大学计量经济学助理教授，2022年TEDS管理主席。拥有日本京都大学经济学博士学位，在加入南洋理工大学之前，曾在广岛大学社会科学研究生院担任经济学助理教授。他的主要研究方向为计量经济学理论、机器学习、应用计量经济学和行为经济学。在Journal of Econometrics、European Economic Review、Economics Letters等国际期刊上发表过多篇高水平论文。

代表性成果Selected Publications

1. Wang, W., T. Ida, and H. Shimada. (2020). Default effect versus active decision: Evidence from a field experiment in Los Alamos. European Economic Review, 128, 103498.

2. Wang W. (2020). On the inconsistency of nonparametric bootstraps for the subvector Anderson–Rubin test. Economics Letters, 191, 109157.

3. Wang, W. and F. Doko Tchatoka. (2018). On bootstrap inconsistency and Bonferroni-based size-correction for the subset Anderson-Rubin test under conditional homoskedasticity. Journal of Econometrics, 207(1), 188-211.

4. Kaffo, M. and W. Wang. (2017). On bootstrap validity for specification testing with many weak instruments. Economics Letters, 157, 107-111.

5. Wang, W. and M. Kaffo. (2016). Bootstrap inference on instrumental variable models with many weak instruments. Journal of Econometrics, 192(1), 231-268.

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