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USING MACRO DATA TO OBTAIN BETTER MICRO FORECASTS

Published online by Cambridge University Press:  21 January 2008

Jan R. Magnus
Affiliation:
Tilburg University, The Netherlands
Andrey L. Vasnev
Affiliation:
Tilburg University, The Netherlands

Abstract

We consider the problem of combining forecasts from two different levels (called “macro” and “micro”), where we have access to the forecasts and their precisions but not to the full data set. We develop a theoretical framework and provide Monte Carlo evidence in the cases of both perfect and imperfect aggregation. Our proposed procedure is simple and robust. We also extend the procedure to time series and propose a forecast model for the European zero rates, combining quarterly and monthly observations. We show that forecast accuracy is improved at both levels.We are grateful to the editors of this special issue and to two referees for their constructive comments, which greatly helped improve the paper. Earlier versions of this paper were presented at the NAKE workshop in Amsterdam, at Tilburg University, and at ESEM 2006 in Vienna. We thank the participants for their useful comments. In addition, we thank Steffan Berridge, John Einmahl, and Hans Schumacher for their constructive comments.

Type
Research Article
Copyright
© 2008 Cambridge University Press

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References

REFERENCES

Barrett, W.B., T.F. Gosnell, & A.J. Heuson (2004) Term-structure factor shifts and economic news. Financial Analysts Journal 60, 8194.Google Scholar
Bates, J.M. & C.W.J. Granger (1969) The combination of forecasts. Operational Research Quarterly 20, 451468.Google Scholar
Batten, J.A. & T.A. Fetherston (2004) European Fixed Income Markets: Money, Bond, and Interest Rate Derivatives. Wiley.
Clemen, R.T. (1989) Combining forecasts: A review and annotated bibliography. International Journal of Forecasting 5, 559583.Google Scholar
Clements, M.P. & D.F. Hendry (1993) On the limitations of comparing mean square forecast errors. Journal of Forecasting 12, 617637.Google Scholar
Diebold, F.X. & L. Kilian (2001) Measuring predictability: Theory and macroeconomic applications. Journal of Applied Econometrics 16, 657669.Google Scholar
Diebold, F.X. & C. Li (2006) Forecasting the term structure of government bond yields. Journal of Econometrics 130, 337364.Google Scholar
Diebold, F.X. & J.A. Lopez (1996) Forecast evaluation and combination. In G.S. Maddala & C.R. Rao (eds.), Handbook of Statistics, pp. 214268. North-Holland.
Diebold, F.X., G.D. Rudebusch, & S.B. Aruoba (2006) The macroeconomy and the yield curve: A dynamic latent factor approach. Journal of Econometrics 131, 309338.Google Scholar
Hendry, D.F. & M.P. Clements (2004) Pooling of forecasts. Econometrics Journal 7, 131.Google Scholar
Hendry, D.F. & K. Hubrich (2005) Forecasting Aggregates by Disaggregates. Discussion paper, European Central Bank.
Hoeting, J.A., D. Madigan, A.E. Raftery, & C.T. Volinsky (1999) Bayesian model averaging: A tutorial. Statistical Science 14, 382401.Google Scholar
Imbens, G.W. & T. Lancaster (1994) Combining micro and macro data in microeconometric models. Review of Economic Studies 61, 655680.Google Scholar
Inoue, A. & L. Kilian (2006) On the selection of forecasting models. Journal of Econometrics 130, 273306.Google Scholar
Lancaster, T. (2004) An Introduction to Modern Bayesian Econometrics. Blackwell.
Leung, G. & A.R. Barron (2006) Information theory and mixing least-squares regressions. IEEE Transactions on Information Theory 52, 33963410.Google Scholar
Magnus, J.R., J.W. van Tongeren, & A.F. de Vos (2000) National accounts estimation using indicator ratios. Review of Income and Wealth 46, 329350.Google Scholar
Marcellino, M., J.H. Stock, & M.W. Watson (2003) Macroeconomic forecasting in the Euro area: Country specific versus area-wide information. European Economic Review 47, 118.Google Scholar
Pesaran, M.H., R.G. Pierse, & M.S. Kumar (1989) Econometric analysis of aggregation in the context of linear prediction models. Econometrica 57, 861888.Google Scholar
Piazzesi, M. & E. Swanson (2004) Futures Prices as Risk-Adjusted Forecast of Monetary Policy. NBER Working paper 10547.
Raftery, A.E., D. Madigan, & J.A. Hoeting (1997) Bayesian model averaging for linear regression models. Journal of the American Statistical Association 92, 179191.Google Scholar
Stock, J.H. & M.W. Watson (2002a) Macroeconomic forecasting using diffusion indexes. Journal of Business & Economic Statistics 20, 147162.Google Scholar
Stock, J.H. & M.W. Watson (2002b) Forecasting using principal components from a large number of predictors. Journal of the American Statistical Association 97, 11671179.Google Scholar
Theil, H. (1954) Linear Aggregation of Economic Relations. North-Holland.
Yang, Y. (2004) Combining forecasting procedures: Some theoretical results. Econometric Theory 20, 176222.Google Scholar