第648期岭南学术论坛（经济学系列Seminar）

语 言            中文+英文

Abstract:

This study provides new mechanisms for identifying and estimating explosive bubbles in mixed-root panel autoregressions with a latent group structure. A post-clustering approach is employed that combines a recursive k-means clustering algorithm with panel-data test statistics for testing the presence of explosive roots in time series trajectories. Uniform consistency of the k-means clustering algorithm is established, showing that the post-clustering estimate is asymptotically equivalent to the oracle counterpart that uses the true group identities. Based on the estimated group membership, right-tailed self-normalized t-tests and coefficient-based J-tests, each with pivotal limit distributions, are introduced to detect the explosive roots. The usual Information Criterion (IC) for selecting the correct number of groups is found to be inconsistent and a new method that combines IC with a Hausman-type specification test is proposed that consistently estimates the true number of groups. Extensive Monte Carlo simulations provide strong evidence that in finite samples, the recursive k-means clustering algorithm can correctly recover latent group membership in data of this type and the proposed post-clustering panel-data tests lead to substantial power gains compared with the time series approach. The proposed methods are used to identify bubble behavior in US and Chinese housing markets, and the US stock market, leading to new findings concerning speculative behavior in these markets.

报告人简介：

       余俊(Jun Yu)，新加坡管理大学 (Singapore Management University)经济学院经济学教授和李光前商学院金融学教授，国际金融计量学会理事，同时担任国际权威学术期刊Econometric Theory和Journal of Financial Econometrics的副主编。余俊教授于1990年获得武汉大学学士学位，并于1998年获得加拿大西安大略大学经济学博士学位。他的研究领域涉及金融市场、计量经济学理论、资本定价、宏观经济学等多个方面。

       欢迎感兴趣的师生参加！

       中山大学岭南学术论坛分经济学和金融学两大系列，是定期邀请国内外优秀学者前来开展学术交流的平台。每系列每个月定期举办2-3次。目前已经成功举办多期，并得到了各界的高度评价。