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Testing for Model Selection in Predicting Aggregate Variables

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  • Giacomo Sbrana

    ()
    (United Nations, Department of Economics and Social Affairs, Population Division)

Abstract

This paper focuses on the choice between aggregate and disaggregate models, consisting of both univariate and multivariate specifications, in predicting aggregate variables. A formal hypothesis testing procedure for in-sample model selection is suggested. The empirical size and power of the test are investigated via the use of Monte Carlo simulations. Empirical results show that the test has good performance not only when the competitive models are non-nested specifications, but also when considering nested competitors.

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File URL: ftp://ftp.gde.unibocconi.it/gde_articles/2007/GDE_V66_N1_P3-28.pdf
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Bibliographic Info

Article provided by GDE (Giornale degli Economisti e Annali di Economia), Bocconi University in its journal Giornale degli Economisti e Annali di Economia.

Volume (Year): 66 (2007)
Issue (Month): 1 (March)
Pages: 3-28

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Handle: RePEc:gde:journl:gde_v66_n1_p3-28

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Related research

Keywords: aggregation; model evaluation and selection; hypothesis testing; Monte Carlo simulation;

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References

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  1. Yan Shen & Cheng Hsiao & Hiroshi Fujiki, 2005. "Aggregate vs. disaggregate data analysis-a paradox in the estimation of a money demand function of Japan under the low interest rate policy," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(5), pages 579-601.
  2. van Garderen, Kees Jan & Lee, Kevin & Pesaran, M. Hashem, 2000. "Cross-sectional aggregation of non-linear models," Journal of Econometrics, Elsevier, vol. 95(2), pages 285-331, April.
  3. Luca Dedola & Eugenio Gaiotti & Luca Silipo, 2001. "Money demand in the euro area: do national differences matter?," Temi di discussione (Economic working papers) 405, Bank of Italy, Economic Research and International Relations Area.
  4. Frank Butter & Simon Dijken, 1997. "The Information Contents of Aggregated Money Demand in the EMU," Open Economies Review, Springer, vol. 8(3), pages 233-244, July.
  5. Hashem Pesaran, M., 2003. "Aggregation of linear dynamic models: an application to life-cycle consumption models under habit formation," Economic Modelling, Elsevier, vol. 20(2), pages 383-415, March.
  6. Aigner, Dennis J & Goldfeld, Stephen M, 1973. "Simulation and Aggregation: A Reconsideration," The Review of Economics and Statistics, MIT Press, vol. 55(1), pages 114-18, February.
  7. Kirstin Hubrich & David F. Hendry, 2005. "Forecasting Aggregates by Disaggregates," Computing in Economics and Finance 2005 270, Society for Computational Economics.
  8. Baffigi, Alberto & Golinelli, Roberto & Parigi, Giuseppe, 2004. "Bridge models to forecast the euro area GDP," International Journal of Forecasting, Elsevier, vol. 20(3), pages 447-460.
  9. Alberto Baffigi & Roberto Golinelli & Giuseppe Parigi, 2002. "Real-time GDP forecasting in the euro area," Temi di discussione (Economic working papers) 456, Bank of Italy, Economic Research and International Relations Area.
  10. Roberto Golinelli & Sergio Pastorello, 2002. "Modelling the demand for M3 in the Euro area," The European Journal of Finance, Taylor & Francis Journals, vol. 8(4), pages 371-401.
  11. Aigner, Dennis J & Goldfeld, Stephen M, 1974. "Estimation and Prediction from Aggregate Data when Aggregates are Measured More Accurately than Their Components," Econometrica, Econometric Society, vol. 42(1), pages 113-34, January.
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Cited by:
  1. Giacomo Sbrana, 2008. "On the use of area-wide models in the Euro-zone," Statistical Methods and Applications, Springer, vol. 17(4), pages 499-518, October.

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