Automated Forecasts of Asia-Pacific Economic Activity
Peter Phillips
No 1103, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University
Abstract:
This paper reports quarterly ex ante forecasts of macroeconomic activity for the U.S.A., Japan and Australia for the period 1995-1997. The forecasts are based on automated time series models of vector autoregressions (VAR's), reduced rank regressions (RRR's), error correction models (ECM's) and Bayesian vector autoregressions (BVAR's). The models are automated by using an asymptotic predictive form of the model selection criterion PIC to determine autoregressive lag order, cointegrating rank and trend degree in the VAR's, RRR's, and ECM's. The same criterion is used to find optimal values of the hyperparameters in the BVAR's. The forecasts are graphed and tabulated. In the case of the U.S.A., the results are compared with forecasts from the Fair model, a structural econometric model of the U.S. economy.
Keywords: Automated time series model; cointegration; model selection; nonstationarity; posterior information criterion (PIC); PIC'ed model; stochastic trend; unit root (search for similar items in EconPapers)
JEL-codes: C32 (search for similar items in EconPapers)
Pages: 15 pages
Date: 1995-06
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)
Published in Asia Pacific Economic Review (1996), 1: 92-102
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