題 目：A New Wald Test for Hypothesis Testing Based on MCMC outputs

主講嘉賓：李 勇教授 中國人民大學

講座時間：2017年11月1日（周三） 15:00--17:00

講座地點：學術會堂603

嘉賓簡介：

李勇，盤古智庫學術委員，中國人民大學漢青經濟與金融高級研究院院長助理，香港中文大學博士，新加坡管理大學金融學博士後。在Journal of Econometrics, Journal of Future Market, Quantitative Finance等國内外優秀刊物上發表了近三十篇學術論文，其SSCI/SCI收錄20篇，主持多項國家自然科學基金，省部級基金項目。曾獲得教育部新世紀人才、北京市青年優秀人才稱号。

内容提要：

In this paper, a new and convenient χ2 wald test based on MCMC outputs is proposed for hypothesis testing. The new statistic can be explained as MCMC version of Wald test and has several important advantages that  make it very convenient in practical applications. First, it is well-defined under improper prior distributions and avoids Jeffrey-Lindley’s paradox. Second, it’s asymptotic distribution can be proved to follow the χ2 distribution so that the threshold values can be easily calibrated from this distribution. Third, it’s statistical error can be derived using the Markov chain Monte Carlo (MCMC) approach. Fourth, most importantly, it is only based on the posterior MCMC random samples drawn from the posterior distribution. Hence, it is only the by-product of the posterior outputs and very easy to compute. In addition, when the prior information is available, the finite sample theory is derived for the proposed test statistic. At last, the usefulness of the test is illustrated with several applications to latent variable models widely used in economics and finance.