h视频

时间：2026年4月1日15:30-17:00(周三)

地点：明德主楼729

主讲人：王玮宁 布里斯托大学教授

主持人：李勇教授

题目：Plausible GMM:a quasi-bayesian approach

摘要：

Structural estimation in economics often makes use of models formulated in terms of momentconditions.While these moment conditions are generally well-motivated,it is often unknown whether the moment restrictions hold exactly.We consider a framework where researchers model their belief about the potential degree of misspecification via a prior distribution and adopt a quasi-Bayesian approach for performing inference on structural parameters.We provide quasi-posterior concentration results,verify that quasi-posteriors can be used to obtain approximately optimal Bayesian decision rules under the maintained prior structure over misspecification,and provide a form of frequentist coverage results.We illustrate the approach through empirical examples where we obtain informative inference for structural objects allowing for substantial relaxations of the requirement that moment conditions hold exactly.

主讲人简介：

Dr.Weining Wang is currently a professor in economics in University of Bristol.Dr.Weining Wang was a chair professor in econometrics at the University of Groningen,faculty of economics and business.Dr.Weining Wang was a chair professor of financial econometrics in department economics and related studies at the University of York,UK.She received a Doctor Degree in Economics from Humboldt University in Berlin.Her research fields mainly include non-parametric and semi-parametric econometrics,high-dimensional econometrics,network models,time series.She published in several top journals in the areas,including"Annals of Statistics","Journal of Business and Economic Statistics"",Journal of Econometrics","Journal American Statistics Association","Econometric Theory",and others.Her research mainly focuses on panel data,high-dimensional time series models,and other applied econometrics methods.The goal is to address specific economic and financial research questions,such as system risk model analysis,financial derivatives asset pricing,and social network analysis.