Optimizing Time-series Forecasts for Inflation and Interest Rates Using Simulation and Model Averaging
Motivated by economic-theory concepts—the Fisher hypothesis and the theory of the term structure—we consider a small set of simple bivariate closed-loop time-series models for the prediction of price inflation and of long- and short-term interest rates. The set includes vector autoregressions (VAR) in levels and in differences, a cointegrated VAR, and a non-linear VAR with threshold cointegration based on data from Germany, Japan, UK, and the U.S. Following a traditional comparative evaluation of predictive accuracy, we subject all structures to a mutual validation using parametric bootstrapping. Ultimately, we utilize the recently developed technique of Mallows model averaging to explore the potential of improving upon the predictions through combinations. While the simulations confirm the traded wisdom that VARs in differences optimize one-step prediction and that error correction helps at larger horizons, the model-averaging experiments point at problems in allotting an adequate penalty for the complexity of candidate models.
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- Adusei Jumah & Robert M. Kunst, 2008. "Seasonal prediction of European cereal prices: good forecasts using bad models?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(5), pages 391-406.
- Diebold, Francis X & Mariano, Roberto S, 2002.
"Comparing Predictive Accuracy,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 20(1), pages 134-144, January.
- Armstrong, J. Scott, 2007. "Significance tests harm progress in forecasting," International Journal of Forecasting, Elsevier, vol. 23(2), pages 321-327.
- Hall, Anthony D & Anderson, Heather M & Granger, Clive W J, 1992. "A Cointegration Analysis of Treasury Bill Yields," The Review of Economics and Statistics, MIT Press, vol. 74(1), pages 116-126, February.
- John Y. Campbell & Robert J. Shiller, 1986.
"Cointegration and Tests of Present Value Models,"
NBER Working Papers
1885, National Bureau of Economic Research, Inc.
- Campbell, John & Shiller, Robert, 1987. "Cointegration and Tests of Present Value Models," Scholarly Articles 3122490, Harvard University Department of Economics.
- John Y. Campbell & Robert J. Shiller, 1986. "Cointegration and Tests of Present Value Models," Cowles Foundation Discussion Papers 785, Cowles Foundation for Research in Economics, Yale University.
- Michael P. Clements & David F. Hendry, 2001. "Forecasting Non-Stationary Economic Time Series," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262531895.
- Balke, Nathan S & Fomby, Thomas B, 1997.
International Economic Review,
Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 38(3), pages 627-645, August.
- Tom Doan, "undated". "RATS programs to replicate Balke-Fomby threshold cointegration," Statistical Software Components RTZ00010, Boston College Department of Economics.
- Balke, Nathan S. & Fomby, Thomas B., 1992. "Threshold cointegration," Working Papers 9209, Federal Reserve Bank of Dallas.
- Malliaropulos, Dimitrios, 2000. "A note on nonstationarity, structural breaks, and the Fisher effect," Journal of Banking & Finance, Elsevier, vol. 24(5), pages 695-707, May.
- De Gooijer, Jan G. & Vidiella-i-Anguera, Antoni, 2004. "Forecasting threshold cointegrated systems," International Journal of Forecasting, Elsevier, vol. 20(2), pages 237-253.
- Frédérique Bec & Anders Rahbek & Neil Shephard, 2005. "The Autoregressive Conditional Root (ACR) Model," Working Papers 2005-26, Centre de Recherche en Economie et Statistique.
- Clive W. J. Granger, 2005. "Modeling, Evaluation, and Methodology in the New Century," Economic Inquiry, Western Economic Association International, vol. 43(1), pages 1-12, January.
- Anders Rahbek & Neil Shephard, 2001. "Autoregressive conditional root model," Economics Papers 2002-W7, Economics Group, Nuffield College, University of Oxford, revised 01 Feb 2002.
- Bruce E. Hansen, 2007. "Least Squares Model Averaging," Econometrica, Econometric Society, vol. 75(4), pages 1175-1189, 07.
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