一、主题：Balanced Predictive Regressions with Cointegrated Regressors

二、主讲人：易艳萍，上海财经大学经济学院常任副教授，美国纽约大学经济学博士。主要研究领域：时间序列、金融计量、计量理论等。在 Journal of Econometrics，Journal of Business & Economic Statistics等期刊上发表多篇论文。曾参加2017 Shanghai Econometrics Workshop、2017 China Meeting of the Econometric Society等会议。担任Review of Economics and Statistics、Journal of Econometrics、Journal of Business and Economic Statistics、Journal of Financial Econometrics、Journal of the Royal Statistical Society等期刊审稿人。

三、时间：2018年5月29日（周二），12：30-13：30

四、地点：学院南路校区主教学楼913会议室

五、主持人：黄志刚，中央财经大学金融学院副教授

论文摘要：In the predictive regression, a less persistent return series is regressed on the first lag of some highly persistent predictors. Therefore, predictability could often be missed due to the persistence imbalance. This paper aims to balance the predictive regression by augmenting the regression with an additional lag of the predictors. This second lag generally reduces the persistence level in the right-hand side of the equation to achieve balance. We then propose a simple test procedure for the univariate and the multivariate predictive regressions, based on least squares estimation. Empirically, we reexamine the popular predictors in the literature, and find quite different results.