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Forecast Comparisons in Unstable Environments

Listed author(s):
  • Giacomini, Raffaella
  • Rossi, Barbara

We propose new methods for comparing the relative out-of-sample forecasting performance of two competing models in the presence of possible instabilities. The main idea is to develop a measure of the relative ìlocal forecasting performanceî for the two models, and to investigate its stability over time by means of statistical tests. We propose two tests (the ìFluctuation testî and the test against a ìOne-time Reversalî) that analyze the evolution of the modelsí relative performance over historical samples. In contrast to previous approaches to forecast comparison, which are based on measures of ìglobal performanceî, we focus on the entire time path of the modelsí relative performance, which may contain useful information that is lost when looking for the model that forecasts best on average. We apply our tests to the analysis of the time variation in the out-of-sample forecasting performance of monetary models of exchange rate determination relative to the random walk.

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Paper provided by Duke University, Department of Economics in its series Working Papers with number 08-04.

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Length: 30 Pages
Date of creation: 2008
Handle: RePEc:duk:dukeec:08-4
Contact details of provider: Postal:
Department of Economics Duke University 213 Social Sciences Building Box 90097 Durham, NC 27708-0097

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Web page: http://econ.duke.edu/

References listed on IDEAS
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  1. Barbara Rossi, 2005. "Are Exchange Rates Really Random Walks? Some Evidence Robust to Parameter Instability," International Finance 0503006, EconWPA.
  2. Raffaella Giacomini & Barbara Rossi, 2014. "Model Comparisons in Unstable Environments," Working Papers 784, Barcelona Graduate School of Economics.
  3. West, K.D., 1994. "Asymptotic Inference About Predictive Ability," Working papers 9417, Wisconsin Madison - Social Systems.
  4. Todd E. Clark & Michael McCracken, 1999. "Tests of Equal Forecast Accuracy and Encompassing for Nested Models," Computing in Economics and Finance 1999 1241, Society for Computational Economics.
  5. Rossi, Barbara, 2005. "Optimal Tests For Nested Model Selection With Underlying Parameter Instability," Econometric Theory, Cambridge University Press, vol. 21(05), pages 962-990, October.
  6. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-263, July.
  7. Inoue, Atsushi & Kilian, Lutz, 2006. "On the selection of forecasting models," Journal of Econometrics, Elsevier, vol. 130(2), pages 273-306, February.
  8. Mc Cracken, Michael W., 2000. "Robust out-of-sample inference," Journal of Econometrics, Elsevier, vol. 99(2), pages 195-223, December.
  9. Lutz Kilian & Mark P. Taylor, 2001. "Why Is It So Difficult to Beat the Random Walk Forecast of Exchange Rates?," Working Papers 464, Research Seminar in International Economics, University of Michigan.
  10. Kenneth S. Rogoff & Vania Stavrakeva, 2008. "The Continuing Puzzle of Short Horizon Exchange Rate Forecasting," NBER Working Papers 14071, National Bureau of Economic Research, Inc.
  11. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-858, May.
  12. James H. Stock & Mark W. Watson, 2001. "Forecasting Output and Inflation: The Role of Asset Prices," NBER Working Papers 8180, National Bureau of Economic Research, Inc.
  13. Raffaella Giacomini & Halbert White, 2003. "Tests of conditional predictive ability," Boston College Working Papers in Economics 572, Boston College Department of Economics.
  14. Taylor, John B., 1993. "Discretion versus policy rules in practice," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 39(1), pages 195-214, December.
  15. Perron, P. & Bai, J., 1995. "Estimating and Testing Linear Models with Multiple Structural Changes," Cahiers de recherche 9552, Universite de Montreal, Departement de sciences economiques.
  16. Jushan Bai, 1997. "Estimation Of A Change Point In Multiple Regression Models," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 551-563, November.
  17. Chu, C.S.J. & Hornik, K. & Kuan, C.M., 1993. "Mosum Tests for Parameter Constancy," Papers 9319, Southern California - Department of Economics.
  18. Rossi, Barbara, 2002. "Testing Long-horizon Predictive Ability with High Persistence, and the Meese-Rogoff Puzzle," Working Papers 02-10, Duke University, Department of Economics.
  19. Ploberger, Werner & Kramer, Walter, 1992. "The CUSUM Test with OLS Residuals," Econometrica, Econometric Society, vol. 60(2), pages 271-285, March.
  20. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
  21. Timmermann, Allan, 2008. "Elusive return predictability," International Journal of Forecasting, Elsevier, vol. 24(1), pages 1-18.
  22. Todd E. Clark & Kenneth D. West, 2004. "Using out-of-sample mean squared prediction errors to test the Martingale difference hypothesis," Research Working Paper RWP 04-03, Federal Reserve Bank of Kansas City.
  23. Elliott, Graham & Timmermann, Allan G, 2004. "Optimal Forecast Combination Under Regime Switching," CEPR Discussion Papers 4649, C.E.P.R. Discussion Papers.
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