Multi-step Forecasting in Unstable Economies: Robustness Issues in the Presence of Location Shifts
AbstractTo forecast at several, say h, periods into the future, a modeller faces two techniques: iterating one-step ahead forecasts (the IMS technique) or directly modelling the relation between observations separated by an h-period interval and using it for forecasting (DMS forecasting). It is known that unit-root non-stationarity and residual autocorrelation benefit DMS accuracy in finite samples. We analyze here the effect of structural breaks as observed in unstable economies, and show that the benefits of DMS stem from its better appraisal of the dynamic relationships of interest for forecasting. It thus acts in between congruent modelling and intercept correction. We apply our results to forecasting the South African GDP over the last thirty years as this economy exhibits significant unstability. We analyze the forecasting properties of 31 competing models. We find that the GDP of South Africa is best forecast, 4 quarters ahead, using direct multi-step techniques, as with our theoretical results.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by University of Oxford, Department of Economics in its series Economics Series Working Papers with number 257.
Date of creation: 01 Feb 2006
Date of revision:
Multi-step Forecasting; Structural Breaks; South Africa;
Find related papers by JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
This paper has been announced in the following NEP Reports:
- NEP-ALL-2006-03-18 (All new papers)
- NEP-ECM-2006-03-18 (Econometrics)
- NEP-FOR-2006-03-18 (Forecasting)
- NEP-MAC-2006-03-18 (Macroeconomics)
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.:
- Pesaran, M Hashem & Timmermann, Allan G, 2004.
"Small Sample Properties of Forecasts From Autoregressive Models Under Structural Breaks,"
CEPR Discussion Papers
4401, C.E.P.R. Discussion Papers.
- Pesaran, M. Hashem & Timmermann, Allan, 2005. "Small sample properties of forecasts from autoregressive models under structural breaks," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 183-217.
- Pesaran, M.H. & Timmermann, A., 2003. "Small Sample Properties of Forecasts from Autoregressive Models under Structural Breaks," Cambridge Working Papers in Economics 0331, Faculty of Economics, University of Cambridge.
- Allan Timmermann & M. Hashem Pesaran, 2003. "Small Sample Properties of Forecasts from Autoregressive Models under Structural Breaks," CESifo Working Paper Series 990, CESifo Group Munich.
- Weiss, Andrew A., 1991. "Multi-step estimation and forecasting in dynamic models," Journal of Econometrics, Elsevier, vol. 48(1-2), pages 135-149.
- Jurgen A Doornik & Henrik Hansen, .
"An omnibus test for univariate and multivariate normalit,"
W4&91., Economics Group, Nuffield College, University of Oxford.
- Jurgen A. Doornik & Henrik Hansen, 2008. "An Omnibus Test for Univariate and Multivariate Normality," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 927-939, December.
- R. Bhansali, 1996. "Asymptotically efficient autoregressive model selection for multistep prediction," Annals of the Institute of Statistical Mathematics, Springer, vol. 48(3), pages 577-602, September.
- Johnston, H N, 1974. "A Note on the Estimation and Prediction Inefficiency of "Dynamic" Estimators," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 15(1), pages 251-55, February.
- Lin, Jin-Lung & Tsay, Ruey S, 1996. "Co-integration Constraint and Forecasting: An Empirical Examination," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 519-38, Sept.-Oct.
- Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
- Janine Aron & John Muellbauer, 2002.
"Interest Rate Effects on Output: Evidence from a GDP Forecasting Model for South Africa,"
IMF Staff Papers,
Palgrave Macmillan, vol. 49(Special i), pages 185-213.
- Aron, Janine & Muellbauer, John, 2002. "Interest Rate Effects on Output: Evidence from a GDP Forecasting Model for South Africa," CEPR Discussion Papers 3595, C.E.P.R. Discussion Papers.
- Janine Aron & John Muellbauer, 2002. "Interest rate effects on output: evidence from a GDP forecasting model for South Africa," CSAE Working Paper Series 2002-04, Centre for the Study of African Economies, University of Oxford.
- White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-38, May.
- Clements, Michael P & Hendry, David F, 1996.
"Multi-step Estimation for Forecasting,"
Oxford Bulletin of Economics and Statistics,
Department of Economics, University of Oxford, vol. 58(4), pages 657-84, November.
- Clements, Michael P. & Hendry, David F., 1996. "Multi-Step Estimation for Forecasting," The Warwick Economics Research Paper Series (TWERPS) 447, University of Warwick, Department of Economics.
- Marcellino, Massimiliano & Stock, James H & Watson, Mark W, 2005.
"A Comparison of Direct and Iterated Multistep AR Methods for Forecasting Macroeconomic Time Series,"
CEPR Discussion Papers
4976, C.E.P.R. Discussion Papers.
- Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2006. "A comparison of direct and iterated multistep AR methods for forecasting macroeconomic time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 499-526.
- Massimiliano Marcellino & James Stock & Mark Watson, 2005. "A Comparison of Direct and Iterated Multistep AR Methods for Forecasting Macroeconomic Time Series," Working Papers 285, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
- Diebold, Francis X & Mariano, Roberto S, 1995.
"Comparing Predictive Accuracy,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 13(3), pages 253-63, July.
- Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- Tom Doan, . "DMARIANO: RATS procedure to compute Diebold-Mariano Forecast Comparison Test," Statistical Software Components RTS00055, Boston College Department of Economics.
- Hendry, David F., 2006. "Robustifying forecasts from equilibrium-correction systems," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 399-426.
- Findley, David F. & Potscher, Benedikt M. & Wei, Ching-Zong, 2004. "Modeling of time series arrays by multistep prediction or likelihood methods," Journal of Econometrics, Elsevier, vol. 118(1-2), pages 151-187.
- 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.
- Jennifer Castle & David Hendry, 2007. "Forecasting UK Inflation: the Roles of Structural Breaks and Time Disaggregation," Economics Series Working Papers 309, University of Oxford, Department of Economics.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Caroline Wise).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.