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Comparing forecast accuracy: A Monte Carlo investigation

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  • Busetti, Fabio
  • Marcucci, Juri

Abstract

The size and power properties of several tests of equal Mean Square Prediction Errors (MSPE) and of Forecast Encompassing (FE) are evaluated, using Monte Carlo simulations, in the context of nested dynamic regression models. The highest size-adjusted power is achieved by the F-type test of forecast encompassing proposed by Clark and McCracken (2001); however, the test tends to be slightly oversized when the number of out-of sample observations is ‘small’ and in cases of (partial) misspecification. The relative performances of the various tests remain broadly unaltered for one- and multi-step-ahead predictions and when the predictive models are partially misspecified. Interestingly, the presence of highly persistent regressors leads to a loss of power of the tests, but their size properties remain nearly unaffected. An empirical example compares the performances of models for short term predictions of Italian GDP.

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  • Busetti, Fabio & Marcucci, Juri, 2013. "Comparing forecast accuracy: A Monte Carlo investigation," International Journal of Forecasting, Elsevier, vol. 29(1), pages 13-27.
  • Handle: RePEc:eee:intfor:v:29:y:2013:i:1:p:13-27
    DOI: 10.1016/j.ijforecast.2012.04.011
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    Cited by:

    1. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, Elsevier.
    2. Porqueddu Mario & Venditti Fabrizio, 2014. "Do food commodity prices have asymmetric effects on euro-area inflation?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(4), pages 1-25, September.
    3. D'Amuri, Francesco & Marcucci, Juri, 2009. "'Google it!' Forecasting the US unemployment rate with a Google job search index," ISER Working Paper Series 2009-32, Institute for Social and Economic Research.
    4. repec:eee:ecmode:v:69:y:2018:i:c:p:160-168 is not listed on IDEAS
    5. Guillén, Osmani Teixeira & Hecq, Alain & Issler, João Victor & Saraiva, Diogo, 2015. "Forecasting multivariate time series under present-value model short- and long-run co-movement restrictions," International Journal of Forecasting, Elsevier, vol. 31(3), pages 862-875.
    6. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, Elsevier.
    7. Pincheira, Pablo M. & West, Kenneth D., 2016. "A comparison of some out-of-sample tests of predictability in iterated multi-step-ahead forecasts," Research in Economics, Elsevier, vol. 70(2), pages 304-319.
    8. Naraidoo, Ruthira & Paya, Ivan, 2012. "Forecasting monetary policy rules in South Africa," International Journal of Forecasting, Elsevier, vol. 28(2), pages 446-455.
    9. Li Guo & Yubo Tao & Jun Tu, 2017. "Media Network and Return Predictability," Papers 1703.02715, arXiv.org, revised Dec 2017.
    10. Brooks, Chris & Burke, Simon P. & Stanescu, Silvia, 2016. "Finite sample weighting of recursive forecast errors," International Journal of Forecasting, Elsevier, vol. 32(2), pages 458-474.
    11. Francesco D'Amuri & Juri Marcucci, 2012. "The predictive power of Google searches in forecasting unemployment," Temi di discussione (Economic working papers) 891, Bank of Italy, Economic Research and International Relations Area.
    12. Ruthira Naraidoo & Ivan Paya, 2010. "Forecasting Monetary Rules in South Africa," Working Papers 201007, University of Pretoria, Department of Economics.
    13. Jack Fosten, 2016. "Forecast evaluation with factor-augmented models," University of East Anglia School of Economics Working Paper Series 2016-05, School of Economics, University of East Anglia, Norwich, UK..
    14. Busetti, Fabio & Marcucci, Juri, 2013. "Comparing forecast accuracy: A Monte Carlo investigation," International Journal of Forecasting, Elsevier, vol. 29(1), pages 13-27.
    15. Neri, Marcelo Côrtes, 2014. "Brazil's middle classes," FGV/EPGE Economics Working Papers (Ensaios Economicos da EPGE) 759, FGV/EPGE - Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil).
    16. Murat Midilic, 2016. "Estimation Of Star-Garch Models With Iteratively Weighted Least Squares," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 16/918, Ghent University, Faculty of Economics and Business Administration.
    17. Fabio Boschetti & Elizabeth A. Fulton & Nicola J. Grigg, 2014. "Citizens’ Views of Australia’s Future to 2050," Sustainability, MDPI, Open Access Journal, vol. 7(1), pages 1-26, December.
    18. E Pavlidis & I Paya & D Peel, 2009. "Forecasting the Real Exchange Rate using a Long Span of Data. A Rematch: Linear vs Nonlinear," Working Papers 601190, Lancaster University Management School, Economics Department.
    19. repec:eee:ecmode:v:68:y:2018:i:c:p:644-660 is not listed on IDEAS

    More about this item

    Keywords

    Forecast encompassing; Model evaluation; Nested models; Equal predictive ability; Forecast evaluation;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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