This paper aims to investigate whether a forecast is optimal, given the information available when it is made. Going beyond the papers that study forecast errors based on the model of Nordhaus (1987), we use a time-varying procedure to forecast revisions and to account for the possibility that the duration of the state may also affect the bias. Three testable hypotheses are presented to help researchers test the optimality of forecasts, with the ultimate aim of determining whether these biases depend on the underlying economic state and whether they are persistent for the duration of the state. Corresponding bias-corrected forecasts can then be made based on these results. The empirical study finds that the one-quarter-ahead official forecast of GDP growth in Taiwan does indeed suffer from state-dependent biases: a persistent under-estimation bias in the relatively good state, and an under-reaction bias that decays with duration in the relatively bad one. Eliminating these biases in the forecast can remove over 44.0% of the variation in forecast errors, and pseudo out-of-sample experiments further support the fact that the resulting bias-corrected forecasts are markedly better than those made by Taiwan’s government or using other competing models.
International Journal of Forecasting, Vol.32, No.3, pp.716-725