主题 Topic：Construction of Leading Economic Index for Recession Prediction using Vine Copulas
时间Time：3月25号（周五）｜ March 25th (Friday), 10:20 – 11:30 am
地点Venue：文波楼208室｜Room 208 , WENBO
主讲人Speaker：杨柳，南京大学产业经济学系助理教授，2014获美国纽约州立大学阿尔巴尼分校(SUNY at Albany, USA)经济学博士学位，其论文已发表在Journal of Business & Economic Statistics (SSCI), International Journal of Forecasting (SSCI), Studies in Nonlinear Dynamics & Econometrics (SSCI) 和Economics Letters (SSCI) 等国际知名经济期刊上。
研究领域:
计量经济学，经济预期，应用计量经济学
Dr. Liu Yang is an assistant professor of Department of Industrial Economics, Nanjing University. Dr. Yang earns his PhD degree in Economics at SUNY at Albany, USA, in 2014. He has published academic papers in Journal of Business & Economic Statistics (SSCI), International Journal of Forecasting (SSCI), Studies in Nonlinear Dynamics & Econometrics (SSCI) and Economics Letters (SSCI).
Research Area:
Econometrics, Economic Forecasting, Applied Econometrics
Abstract:
This paper constructs a composite leading index for business cycle prediction based on vine copulas that capture the complex pattern of dependence among individual predictors. This approach is optimal in the sense that the resulting index possesses the highest discriminatory power as measured by the receiver operating characteristic (ROC) curve. The model specification is semi-parametric in nature, suggesting a two-step estimation procedure, with the second-step finite dimensional parameter being estimated by QMLE given the first-step non-parametric estimate. To illustrate its usefulness, we apply this methodology to optimally aggregate the ten leading indicators selected by The Conference Board (TCB) to predict economic recessions in the United States. In terms of both the in-sample and out-of-sample performances, our method is significantly superior to the current Leading Economic Index proposed by TCB.
