This paper is aimed at investigating whether the forecast is optimal given the available information when the forecast is made. Going beyond the papers that study forecast errors based on the model of Nordhaus (1987), we apply a time varying procedure to forecast revisions and further 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 goal of determining whether these biases depend on the underlying economic state and whether they are persistent with duration of the state. The 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 indeed suffers from state-dependent biases-persistent under-estimation bias at the relatively good state and under-reaction bias which decays with duration at the relatively bad one. Eliminating these biases in the forecast can reduce over 44.0% variation of forecast errors, and pseudo out-of-sample experiments further support the fact that the resulting bias-corrected forecast is markedly better than that made by Taiwan’s government and those made using other competing models.