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Optimal forecasting with heterogeneous panels: a Monte Carlo study

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  • Lorenzo Trapani
  • Giovanni Urga

Abstract

This paper reports the results of a series of Monte Carlo exercises to contrast the forecasting performance of several panel data esti- mators, divided into three main groups (homogeneous, heterogeneous and shrinkage/Bayesian). The comparison is done using di¤erent lev- els of heterogeneity, alternative panel structures in terms of T and N and using various error dynamics speci.cations. We also consider the presence of various degrees of cross sectional dependence among units. To assess the predictive performance, we use traditional measures of forecast accuracy (Theil.s U statistics, RMSE and MAE), the Diebold and Mariano.s (1995) test, and the Pesaran and Timmerman.s (1992) statistics on the capability of forecasting turning points. The main .nding of our analysis is that in presence of heterogeneous panels the Bayesian procedures have systematically the best predictive power in- dependently of the model.s features.

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Bibliographic Info

Paper provided by Department of Economics and Technology Management, University of Bergamo in its series Working Papers with number 0616.

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Date of creation: 2006
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Handle: RePEc:brh:wpaper:0616

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Keywords: Panel data; homogeneous; heterogeneous and shrinkage estimators; forecasting; cross dependence; Monte Carlo simulations.;

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  1. Baltagi, Badi H. & Li, Qi, 1992. "A Note on the Estimation of Simultaneous Equations with Error Components," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 8(01), pages 113-119, March.
  2. Baltagi, Badi H. & Bresson, Georges & Pirotte, Alain, 2002. "Comparison of forecast performance for homogeneous, heterogeneous and shrinkage estimators: Some empirical evidence from US electricity and natural-gas consumption," Economics Letters, Elsevier, Elsevier, vol. 76(3), pages 375-382, August.
  3. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, Econometric Society, vol. 49(6), pages 1417-26, November.
  4. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 13(3), pages 253-63, July.
  5. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, Elsevier, vol. 13(2), pages 281-291, June.
  6. Badi H. Baltagi & Georges Bresson & James M. Griffin & Alain Pirotte, 2002. "Homogeneous, heterogeneous or shrinkage estimators? Some empirical evidence from French regional gasoline consumption," 10th International Conference on Panel Data, Berlin, July 5-6, 2002, International Conferences on Panel Data A6-4, International Conferences on Panel Data.
  7. Francis X. Diebold & Jose A. Lopez, 1995. "Forecast evaluation and combination," Research Paper, Federal Reserve Bank of New York 9525, Federal Reserve Bank of New York.
  8. Herbert Brücker & Boriss Siliverstovs, 2006. "On the estimation and forecasting of international migration: how relevant is heterogeneity across countries?," Empirical Economics, Springer, Springer, vol. 31(3), pages 735-754, September.
  9. Arellano, Manuel, 2003. "Panel Data Econometrics," OUP Catalogue, Oxford University Press, Oxford University Press, number 9780199245291, October.
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  12. Pesaran, M Hashem & Timmermann, Allan, 1992. "A Simple Nonparametric Test of Predictive Performance," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 10(4), pages 561-65, October.
  13. Christoffersen & Diebold, . "Further Results on Forecasting and Model Selection Under Asymmetric Loss," Home Pages, University of Pennsylvania _059, University of Pennsylvania.
  14. Balestra, Pietro & Varadharajan-Krishnakumar, Jayalakshmi, 1987. "Full Information Estimations of a System of Simultaneous Equations with Error Component Structure," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 3(02), pages 223-246, April.
  15. Badi H. Baltagi & Georges Bresson & Alain Pirotte, 2004. "Tobin q: Forecast performance for hierarchical Bayes, shrinkage, heterogeneous and homogeneous panel data estimators," Empirical Economics, Springer, Springer, vol. 29(1), pages 107-113, January.
  16. Pesaran, M.H., 2003. "A Simple Panel Unit Root Test in the Presence of Cross Section Dependence," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge 0346, Faculty of Economics, University of Cambridge.
  17. Pesaran, M.H. & Smith, R., 1992. "Estimating Long-Run Relationships From Dynamic Heterogeneous Panels," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge 9215, Faculty of Economics, University of Cambridge.
  18. Keane, Michael P & Runkle, David E, 1992. "On the Estimation of Panel-Data Models with Serial Correlation When Instruments Are Not Strictly Exogenous: Reply," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 10(1), pages 26-29, January.
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  21. Leitch, Gordon & Tanner, J Ernest, 1991. "Economic Forecast Evaluation: Profits versus the Conventional Error Measures," American Economic Review, American Economic Association, American Economic Association, vol. 81(3), pages 580-90, June.
  22. Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, Elsevier, vol. 18(1), pages 47-82, January.
  23. Baltagi, Badi H. & Griffin, James M., 1997. "Pooled estimators vs. their heterogeneous counterparts in the context of dynamic demand for gasoline," Journal of Econometrics, Elsevier, Elsevier, vol. 77(2), pages 303-327, April.
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  26. Ciaran Driver & Giovanni Urga, 2004. "Transforming Qualitative Survey Data: Performance Comparisons for the UK," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, Department of Economics, University of Oxford, vol. 66(1), pages 71-89, 02.
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Citations

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Cited by:
  1. Massimiliano Mazzanti & Antonio Musolesi, 2012. "The heterogeneity of Carbon Kuznets Curves for advanced countries. Comparing homogeneous, heterogeneous and shrinkage/Bayesian estimators," Working Papers 201206, University of Ferrara, Department of Economics.
  2. Thomas Jobert & Fatih Karanfil & Anna Tykhonenko, 2014. "Estimating country-specific environmental Kuznets curves from panel data: a Bayesian shrinkage approach," Applied Economics, Taylor & Francis Journals, Taylor & Francis Journals, vol. 46(13), pages 1449-1464, May.
  3. Badi H. Baltagi & Bernard Fingleton & Alain Pirotte, 2011. "Estimating and Forecasting with a Dynamic Spatial Panel Data Model," SERC Discussion Papers, Spatial Economics Research Centre, LSE 0095, Spatial Economics Research Centre, LSE.
  4. Leonardo Morales-Arias & Alexander Dross, 2010. "Adaptive Forecasting of Exchange Rates with Panel Data," Research Paper Series, Quantitative Finance Research Centre, University of Technology, Sydney 285, Quantitative Finance Research Centre, University of Technology, Sydney.
  5. Leonardo Morales-Arias & Alexander Dross, 2010. "Adaptive Forecasting of Exchange Rates with Panel Data," Kiel Working Papers, Kiel Institute for the World Economy 1656, Kiel Institute for the World Economy.
  6. Trapani, Lorenzo, 2012. "On the asymptotic t-test for large nonstationary panel models," Computational Statistics & Data Analysis, Elsevier, Elsevier, vol. 56(11), pages 3286-3306.
  7. Reibling, Nadine, 2013. "The international performance of healthcare systems in population health: Capabilities of pooled cross-sectional time series methods," Health Policy, Elsevier, Elsevier, vol. 112(1), pages 122-132.
  8. Morales-Arias, Leonardo & Moura, Guilherme V., 2013. "Adaptive forecasting of exchange rates with panel data," International Journal of Forecasting, Elsevier, Elsevier, vol. 29(3), pages 493-509.
  9. Ernesto Aguayo-Téllez & José Martínez-Navarro, 2013. "Internal and international migration in Mexico: 1995--2000," Applied Economics, Taylor & Francis Journals, Taylor & Francis Journals, vol. 45(13), pages 1647-1661, May.

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