首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Asymptotics for out of sample tests of Granger causality
Authors:Michael W McCracken  
Institution:aBoard of Governors of the Federal Reserve System, 20th and Constitution N.W., Washington, DC 20551, USA
Abstract:This paper presents analytical, Monte Carlo and empirical evidence concerning out-of-sample tests of Granger causality. The environment is one in which the relative predictive ability of two nested parametric regression models is of interest. Results are provided for three statistics: a regression-based statistic suggested by Granger and Newbold 1977. Forecasting Economic Time Series. Academic Press Inc., London], a t-type statistic comparable to those suggested by Diebold and Mariano 1995, Comparing Predictive Accuracy. Journal of Business and Economic Statistics, 13, 253–263] and West 1996. Asymptotic Inference About Predictive Ability, Econometrica, 64, 1067–1084], and an F-type statistic akin to Theil's U. Since the asymptotic distributions under the null are nonstandard, tables of asymptotically valid critical values are provided. Monte Carlo evidence supports the theoretical results. An empirical example evaluates the predictive content of the Chicago Fed National Activity Index for growth in Industrial Production and core PCE-based inflation.
Keywords:Granger causality  Forecast evaluation  Hypothesis testing  Model selection
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号