概要
日時：2024年2月1日(木) 16:30-18:00
場所：3号館1階 130室(経済経営学部会議室)
講演者：Jiang Peiyun氏(東京都立大学)
タイトル：Testing for structural change in heterogeneous panels using common correlated effects estimators
【abstract】
A new test is proposed to detect structural breaks in heterogeneous panel data models with potentially strong cross-sectional dependence. The error structure is captured by an unknown number of common factors, and we allow for correlations between unobserved factors and explanatory variables. The common correlated effects (CCE) method is applied to eliminate the unknown factors such that it does not require estimating the number of latent factors. The asymptotic analyses indicate that the detecting statistic has the same asymptotic distribution regardless of cross-sectional dependence, as both N and T go to infinity. Monte Carlo simulations show good performance of the test in the presence of strong or weak cross-sectional dependence.