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Does the choice of estimator matter for forecasting? A revisit

Author

Listed:
  • Afees A. Salisu

    () (Centre for Econometric and Allied Research, University of Ibadan)

  • Ahamuefula Ephraim Ogbonna

    () (Centre for Econometric and Allied Research, University of Ibadan Department of Statistics, University of Ibadan, Ibadan, Nigeria)

  • Paul Adeoye Omosebi

    () (Centre for Econometric and Allied Research, University of Ibadan. Department of Computer Sciences, University of Lagos, Akoka, Nigeria.)

Abstract

In this study, we further examine whether the choice of estimator matters for forecasting based on the conclusion of Westerlund and Narayan [WN, hereafter] (2012, 2015). A similar but small simulation study was conducted by WN (2012, 2015) to validate the need to account for salient features of predictors such as persistence, endogeneity and conditional heteroscedasticity in a forecast model. In addition to considering a more representative number of observations for high frequency, extensive replications and four competing estimators, we offer alternative functions for these effects and thereafter, we test whether the conclusion of WN (2012, 2015) will still hold. Our results further lend support to the WN (2012, 2015) findings and thus suggest that the choice of estimator matters for forecasting notwithstanding the alternative functions and scenarios considered in our study. Thus, pre-testing the predictors in a forecast model for the mentioned features is required to identify the appropriate estimator to apply.

Suggested Citation

  • Afees A. Salisu & Ahamuefula Ephraim Ogbonna & Paul Adeoye Omosebi, 2018. "Does the choice of estimator matter for forecasting? A revisit," Working Papers 053, Centre for Econometric and Allied Research, University of Ibadan.
  • Handle: RePEc:cui:wpaper:0053
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    References listed on IDEAS

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    1. Salisu, Afees A. & Isah, Kazeem O., 2018. "Predicting US inflation: Evidence from a new approach," Economic Modelling, Elsevier, vol. 71(C), pages 134-158.
    2. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Narayan, Paresh Kumar, 2015. "Stock return forecasting: Some new evidence," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 38-51.
    3. Bannigidadmath, Deepa & Narayan, Paresh Kumar, 2015. "Are Indian stock returns predictable?," Working Papers fe_2015_07, Deakin University, Department of Economics.
    4. Deepa & Paresh K Narayan, "undated". "Are Indian Stock Returns Predictable?," Financial Econometics Series 2015_07, Deakin University, Faculty of Business and Law, School of Accounting, Economics and Finance.
    5. Sharma, Susan Sunila, 2016. "Can consumer price index predict gold price returns?," Economic Modelling, Elsevier, vol. 55(C), pages 269-278.
    6. Salisu, Afees A. & Ademuyiwa, Idris & Isah, Kazeem O., 2018. "Revisiting the forecasting accuracy of Phillips curve: The role of oil price," Energy Economics, Elsevier, vol. 70(C), pages 334-356.
    7. Narayan, Paresh Kumar & Gupta, Rangan, 2015. "Has oil price predicted stock returns for over a century?," Energy Economics, Elsevier, vol. 48(C), pages 18-23.
    8. Narayan, Paresh Kumar & Bannigidadmath, Deepa, 2015. "Are Indian stock returns predictable?," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 506-531.
    9. Bannigidadmath, Deepa & Narayan, Paresh Kumar, 2016. "Stock return predictability and determinants of predictability and profits," Emerging Markets Review, Elsevier, vol. 26(C), pages 153-173.
    10. Makin, Anthony J. & Narayan, Paresh Kumar & Narayan, Seema, 2014. "What expenditure does Anglosphere foreign borrowing fund?," Journal of International Money and Finance, Elsevier, vol. 40(C), pages 63-78.
    11. Westerlund, Joakim & Narayan, Paresh Kumar, 2012. "Does the choice of estimator matter when forecasting returns?," Journal of Banking & Finance, Elsevier, vol. 36(9), pages 2632-2640.
    12. Lewellen, Jonathan, 2004. "Predicting returns with financial ratios," Journal of Financial Economics, Elsevier, vol. 74(2), pages 209-235, November.
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    More about this item

    Keywords

    Endogeneity; Heteroscedasticity; Persistence; Forecast evaluation;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: 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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