Statistics Seminar（2013-16）

Topic:A New Approach for Testing Number of Common Stochastic Trends

Speaker:Bibo Jiang, Fudan University

Time:Friday,11 October, 10:30-12:00

Location:Room K01, Guanghua Building 2

Abstract：This paper considers a state space model with integrated latent variables. The model provides an effective framework to specify, identify and extract common stochastic trends for a set of integrated time series. The model can be readily estimated by the standard Kalman filter, whose asymptotics are fully developed in the paper. In particular, we establish the consistency and asymptotic mixed normality of the maximum likelihood estimator, which validates the use of conventional methods of inference for our model. Moreover, we show that the standard information criteria are consistent and can be used to determine the number of common stochastic trends in our model. Our simulation study clearly demonstrates the relevancy of our asymptotic theory in finite samples. For illustrations, we apply our methodology to analyze common stochastic trends in the fluctuations of macroeconomic aggregates across countries and in the prices of Dow Jones Industrial Average (DJIA) component stocks.

About the speaker：Bibo Jiang is assistant professor in the School of Economics at Fudan University since 2010. She got her bachelor degree from the School of Economics of Peking University at 2000 and her Ph.D. degree from the Economics Department of Rice University at 2008. She once worked at Bates White LLC (USA) as a senior consultant on antitrust practice. Her research interest is on econometrics theory and applied econometrics.