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Alternative methods for forecasting GDP

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  • Dominique Guegan

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, University of Ca’ Foscari [Venice, Italy])

  • Patrick Rakotomarolahy

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

Abstract

An empirical forecast accuracy comparison of the non-parametric method, known as multivariate Nearest Neighbor method, with parametric VAR modelling is conducted on the euro area GDP. Using both methods for nowcasting and forecasting the GDP, through the estimation of economic indicators plugged in the bridge equations, we get more accurate forecasts when using nearest neighbor method. We prove also the asymptotic normality of the multivariate k-nearest neighbor regression estimator for dependent time series, providing confidence intervals for point forecast in time series.

Suggested Citation

  • Dominique Guegan & Patrick Rakotomarolahy, 2010. "Alternative methods for forecasting GDP," Post-Print halshs-00505165, HAL.
    • Handle: RePEc:hal:journl:halshs-00505165
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00505165
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    References listed on IDEAS

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    1. Rangan Gupta, 2006. "FORECASTING THE SOUTH AFRICAN ECONOMY WITH VARs AND VECMs," South African Journal of Economics, Economic Society of South Africa, vol. 74(4), pages 611-628, December.
    2. Evan F. Koenig & Sheila Dolmas & Jeremy Piger, 2003. "The Use and Abuse of Real-Time Data in Economic Forecasting," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 618-628, August.
    3. Dominique Guegan & Patrick Rakotomarolahy, 2010. "A Short Note on the Nowcasting and the Forecasting of Euro-area GDP Using Non-Parametric Techniques," PSE-Ecole d'économie de Paris (Postprint) halshs-00460472, HAL.
    4. Desheng Ouyang & Dong Li & Qi Li, 2006. "Cross-validation and non-parametric k nearest-neighbour estimation," Econometrics Journal, Royal Economic Society, vol. 9(3), pages 448-471, November.
    5. Pagan,Adrian & Ullah,Aman, 1999. "Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521355643, October.
    6. Dominique Guégan & Nicolas Huck, 2005. "On the use of Nearest Neighbors in finance," Finance, Presses universitaires de Grenoble, vol. 26(2), pages 67-86.
    7. Dominique Guegan & Patrick Rakotomarolahy, 2010. "A Short Note on the Nowcasting and the Forecasting of Euro-area GDP Using Non-Parametric Techniques," Post-Print halshs-00460472, HAL.
    8. Laurent Ferrara & Dominique Guégan & Patrick Rakotomarolahy, 2010. "GDP nowcasting with ragged-edge data: a semi-parametric modeling," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 186-199.
    9. Michael P. Clements & Hans-Martin Krolzig, 1998. "A comparison of the forecast performance of Markov-switching and threshold autoregressive models of US GNP," Econometrics Journal, Royal Economic Society, vol. 1(Conferenc), pages 47-75.
    10. Dominique Guégan & Patrick Rakotomarolahy, 2010. "A Short Note on the Nowcasting and the Forecasting of Euro-area GDP Using Non-Parametric Techniques," Economics Bulletin, AccessEcon, vol. 30(1), pages 508-518.
    11. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    12. Bernanke, Ben S. & Boivin, Jean, 2003. "Monetary policy in a data-rich environment," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 525-546, April.
    13. Greg Tkacz & Sarah Hu, 1999. "Forecasting GDP Growth Using Artificial Neural Networks," Staff Working Papers 99-3, Bank of Canada.
    14. George Kapetanios & Massimiliano Marcellino, 2009. "A parametric estimation method for dynamic factor models of large dimensions," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(2), pages 208-238, March.
    15. Nowman, K. Ben & Saltoglu, Burak, 2003. "Continuous time and nonparametric modelling of U.S. interest rate models," International Review of Financial Analysis, Elsevier, vol. 12(1), pages 25-34.
    16. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    17. Dominique Guegan & Patrick Rakotomarolahy, 2010. "A short note on the nowcasting and the forecasting of Euro-area GDP using non-parametric techniques," Post-Print halshs-00461711, HAL.
    18. Frank Smets & Raf Wouters, 2004. "Forecasting with a Bayesian DSGE Model: An Application to the Euro Area," Journal of Common Market Studies, Wiley Blackwell, vol. 42(4), pages 841-867, November.
    19. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    20. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
    21. repec:ebl:ecbull:v:30:y:2010:i:1:p:508-518 is not listed on IDEAS
    22. Marie Diron, 2008. "Short-term forecasts of euro area real GDP growth: an assessment of real-time performance based on vintage data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(5), pages 371-390.
    23. 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.
    24. Adonis Yatchew, 1998. "Nonparametric Regression Techniques in Economics," Journal of Economic Literature, American Economic Association, vol. 36(2), pages 669-721, June.
    25. Laurent Ferrara & Dominique Guegan & Patrick Rakotomarolahy, 2010. "GDP nowcasting with ragged-edge data: a semi-parametric modeling," Post-Print halshs-00460461, HAL.
    26. Rünstler, Gerhard & Sédillot, Franck, 2003. "Short-term estimates of euro area real GDP by means of monthly data," Working Paper Series 276, European Central Bank.
    27. Litterman, Robert, 1986. "Forecasting with Bayesian vector autoregressions -- Five years of experience : Robert B. Litterman, Journal of Business and Economic Statistics 4 (1986) 25-38," International Journal of Forecasting, Elsevier, vol. 2(4), pages 497-498.
    28. Carrasco, Marine & Chen, Xiaohong, 2002. "Mixing And Moment Properties Of Various Garch And Stochastic Volatility Models," Econometric Theory, Cambridge University Press, vol. 18(1), pages 17-39, February.
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