Does the choice of estimator matter for forecasting? A revisit

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.