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Creator: Roberds, William Series: Business analysis committee meeting Abstract:
One of the more significant developments in econometric modeling over the past decade has been the invention of the forecasting technique known as Bayesian vector autoregression (BVAR). This paper provides a detailed description of the process of specifying a BVAR model of quarterly time series on the U.S. macroeconomy. The postsample forecasting performance of the model is evaluated at an informal level by comparing the model's performance to certain naive forecasting methods, and is evaluated at a formal level by means of efficiency tests. Although the null hypothesis of efficiency is rejected for the model's forecasts, the accuracy of the model exceeds that of naive forecasting methods, and seems comparable to that of commercial forecasting firms for early quarter forecasts.
Parola chiave: BVAR, Vector autoregression, and Bayesian analysis Soggetto: C11 - Bayesian Analysis: General and C53 - Forecasting Models; Simulation Methods
Creator: Todd, Richard M. Series: Business analysis committee meeting Descrizione:
Version without Software Appendix appears on the Federal Reserve Bank of Minneapolis Web site at http://www.minneapolisfed.org/publications_papers/pub_display.cfm?id=571
Parola chiave: BVAR, Vector autoregression, and Bayesian analysis Soggetto: C53 - Econometric modeling - Forecasting and other model applications