Forecasting in the Presence of Structural Breaks and Policy Regime Shifts
The value of selecting the best forecasting model as the basis for empirical economic policy analysis is questioned. When no model coincides with the data generation process, non-causal statistical devices may provide the best available forecasts: examples from recent work include intercept corrections and differenced-data VARs. However, the resulting models need have no policy implications. A paradox may result if their forecasts induce policy changes which can be used to improve the statistical forecast. This suggests correcting statistical forecasts by using the econometric models estimate of the scenario change, and doing so yields reduced biases.
|Date of creation:||01 Sep 2001|
|Date of revision:|
|Contact details of provider:|| Postal: Manor Rd. Building, Oxford, OX1 3UQ|
Web page: http://www.economics.ox.ac.uk/
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Granger, Clive W. J. & Deutsch, Melinda, 1992.
"Comments on the evaluation of policy models,"
Journal of Policy Modeling,
Elsevier, vol. 14(4), pages 497-516, August.
- Clements, Michael P & Hendry, David F, 1996. "Intercept Corrections and Structural Change," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 475-94, Sept.-Oct.
- Christopher A. Sims, 1982. "Policy Analysis with Econometric Models," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 13(1), pages 107-164.
- Jurgen A. Doornik & David F. Hendry & Bent Nielsen, 1998.
"Inference in Cointegrating Models: UK M1 Revisited,"
Journal of Economic Surveys,
Wiley Blackwell, vol. 12(5), pages 533-572, December.
- Doornik, Jurgen A & Hendry, David F & Nielsen, Bent, 1998. " Inference in Cointegrating Models: UK M1 Revisited," Journal of Economic Surveys, Wiley Blackwell, vol. 12(5), pages 533-72, December.
- James H. Stock & Mark W. Watson, 1994.
"Evidence on structural instability in macroeconomic times series relations,"
Working Paper Series, Macroeconomic Issues
94-13, Federal Reserve Bank of Chicago.
- Stock, James H & Watson, Mark W, 1996. "Evidence on Structural Instability in Macroeconomic Time Series Relations," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 11-30, January.
- James H. Stock & Mark W. Watson, 1994. "Evidence on Structural Instability in Macroeconomic Time Series Relations," NBER Technical Working Papers 0164, National Bureau of Economic Research, Inc.
- Christopher A. Sims, 1986. "Are forecasting models usable for policy analysis?," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Win, pages 2-16.
- Clements,Michael & Hendry,David, 1998.
"Forecasting Economic Time Series,"
Cambridge University Press, number 9780521632423, 1.
- Lucas, Robert Jr, 1976. "Econometric policy evaluation: A critique," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 1(1), pages 19-46, January.
- Hendry, D.F. & Mizon, G.E., 1990. "Evaluating Dynamic Econometric Models By Encompassing The Var," Economics Series Working Papers 99102, University of Oxford, Department of Economics.
- Banerjee, Anindya & Hendry, David F & Mizon, Grayham E, 1996.
"The Econometric Analysis of Economic Policy,"
Oxford Bulletin of Economics and Statistics,
Department of Economics, University of Oxford, vol. 58(4), pages 573-600, November.
- Hendry, David F & Doornik, Jurgen A, 1997. "The Implications for Econometric Modelling of Forecast Failure," Scottish Journal of Political Economy, Scottish Economic Society, vol. 44(4), pages 437-61, September.
- Bontemps, Christophe & Mizon, Grayham E., 2001. "Congruence and encompassing," Discussion Paper Series In Economics And Econometrics 0107, Economics Division, School of Social Sciences, University of Southampton.
- Hendry, David F., 2000. "On detectable and non-detectable structural change," Structural Change and Economic Dynamics, Elsevier, vol. 11(1-2), pages 45-65, July.
- David F. Hendry & Neil R. Ericsson, 1990.
"Modeling the demand for narrow money in the United Kingdom and the United States,"
International Finance Discussion Papers
383, Board of Governors of the Federal Reserve System (U.S.).
- Hendry, David F. & Ericsson, Neil R., 1991. "Modeling the demand for narrow money in the United Kingdom and the United States," European Economic Review, Elsevier, vol. 35(4), pages 833-881, May.
- Clements, Michael P. & Hendry, David F., 2006. "Forecasting with Breaks," Handbook of Economic Forecasting, Elsevier.
- Clara Jørgensen & Hans Christian Kongsted & Anders Rahbek, 1996.
"Trend-Stationarity in the I(2) Cointegration Model,"
96-12, University of Copenhagen. Department of Economics.
- Rahbek, Anders & Christian Kongsted, Hans & Jorgensen, Clara, 1999. "Trend stationarity in the I(2) cointegration model," Journal of Econometrics, Elsevier, vol. 90(2), pages 265-289, June.
- Hendry, D.F. & Mizon, G.E., 1999. "On selecting policy analysis models by forecast accuracy," Discussion Paper Series In Economics And Econometrics 9918, Economics Division, School of Social Sciences, University of Southampton.
- Holly,Sean & Weale,Martin (ed.), 2000. "Econometric Modelling," Cambridge Books, Cambridge University Press, number 9780521650694, 1.
- Hendry, David F., 1995. "Dynamic Econometrics," OUP Catalogue, Oxford University Press, number 9780198283164, July.
- 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, June.
When requesting a correction, please mention this item's handle: RePEc:oxf:wpaper:2002-w12. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Monica Birds)
If references are entirely missing, you can add them using this form.