Can forecasting performance be improved by considering the steady state? An application to Swedish inflation and interest rate

Journal of Forecasting

Volumn 27, Issue 1, 2008, Pages 41-51

  Österholm, Pär ^a  

^a UPPSALA UNIVERSITY   (Sweden)

Author keywords

Out of sample forecasts; Steady state

Indexed keywords

BAYESIAN NETWORKS; FORECASTING; MATHEMATICAL MODELS; REGRESSION ANALYSIS; VECTORS;

BAYESIAN AUTOREGRESSIVE MODELS; VECTOR AUTOREGRESSIVE MODELS;

INDUSTRIAL ECONOMICS;

EID: 39349116800     PISSN: 02776693     EISSN: 1099131X     Source Type: Journal    
DOI: 10.1002/for.1041     Document Type: Article

References (26)

1. Atkeson A, Ohanian LE. 2001. Are Phillips curves useful for forecasting inflation? Federal Reserve Bank of Minneapolis Quarterly Review 25: 2-11.
2. Clark TE. 1999. Finite-sample properties of tests for equal forecast accuracy. Journal of Forecasting 18: 489-504.
3. Clements MP, Galvão AB. 2004. A comparison of tests of nonlinear cointegration with application to the predictability of US interest rates using the term structure. International Journal of Forecasting 20: 219-236.
4. Croushore D, Stark T. 2002. Forecasting with a real-time data set for macroeconomists. Journal of Macroeconomics 24: 473-484.
5. Diebold FX, Mariano RS. 1995. Comparing predictive accuracy. Journal of Business and Economic Statistics 13: 253-263.
6. Fama EF. 1975. Short-term interest rates as predictors of inflation. American Economic Review 65: 269-282.
7. Froot KA, Rogoff K. 1995. Perspectives on PPP and long-run real exchange rates. In Handbook of International Economics, Vol. 3, Grossman, G. and Rogoff, K. (eds). North-Holland: Amsterdam; 1647-1688.
8. Gelman A, Carlin JB, Stern HS, Rubin DB. 2003. Bayesian Data Analysis (2nd edn). Chapman & Hall: New York.
9. Granger CWJ, Jeon Y. 2003. Comparing forecasts of inflation using time distance. International Journal of Forecasting 19: 339-349.
10. Hannan EJ, Quinn BG. 1979. The determination of the order of an autoregression. Journal of the Royal Statistical Society 41: 190-195.
11. Hjalmarsson E. 2006. Should we expect significant out-of-sample results when predicting stock returns? International Finance Discussion Papers No. 855, Board of Governors of the Federal Reserve System.
12. Hubrich K. 2005. Forecasting euro area inflation: does aggregating forecasts by HICP component improve forecast accuracy? International Journal of Forecasting 21: 119-136.
13. Litterman RB. 1986. Forecasting with Bayesian vector autoregressions: five years of experience. Journal of Business and Economic Statistics 5: 25-38.
14. Luger R. 2004. Exact tests of equal forecast accuracy with an application to the term structure of interest rates, Working paper 2004-2, Bank of Canada.
15. Lütkepohl H. 1993. Introduction to Multiple Time Series Analysis (2nd edn). Springer: Berlin.
16. Mills TC, Stephenson MJ. 1985. An empirical analysis of the UK treasury bill market. Applied Economics 17: 689-703.
17. Mishkin FS. 1984. The real interest rate: a multicountry empirical study. Canadian Journal of Economics 17:283-311.
18. Perron P. 1989. The great crash, the oil price shock and the unit root hypothesis. Econometrica 57: 1361-1402.
19. Robertson JC, Tallman EW. 2001. Improving federal-funds rate forecasts in VAR models used for policy analysis. Journal of Business and Economic Statistics 19: 324-330.
20. Rose AK. 1988. Is the real interest rate stable? Journal of Finance 43: 1095-1112.
21. Said SE, Dickey DA. 1984. Testing for unit roots in autoregressive moving average models of unknown order. Biometrika 71: 599-607.
22. Shaman P, Stine RA. 1988. The bias of autoregressive coefficient estimators. Journal of the American Statistical Association 83: 842-848.
23. Stock JH, Watson MW. 1999. Forecasting inflation. Journal of Monetary Economics 44: 293-335.
24. Taylor JB. 1993. Discretion versus policy rules in practice. Carnegie-Rochester Conference Series on Public Policy 39: 195-214.
25. Tierny L. 1994. Markov chains for exploring posterior distributions. Annals of Statistics 22: 1701-1762.
26. Villani M. 2005. Inference in vector autoregressive models with an informative prior on the steady state. Working paper No. 181, Sveriges Riksbank.