MULTI‐STEP ESTIMATION FOR FORECASTING
分析了多步估计（动态估计）在多步预测中的适用条件，通过解析例子和蒙特卡洛模拟表明，在模型设定错误时动态估计可能改善预测，但在正确设定模型中减少有限样本偏差不足以证明其合理性。
We delineate conditions which favour multi‐step, or dynamic, estimation for multi‐step forecasting. An analytical example shows how dynamic estimation (DE) may accommodate incorrectly‐specified models as the forecast lead alters, improving forecast performance for some misspecifications. However, in correctly‐specified models, reducing finite‐sample biases does not justify DE. In a Monte Carlo forecasting study for integrated processes, estimating a unit root in the presence of a neglected negative moving‐average error may favour DE, though other solutions exist to that scenario. A second Monte Carlo study obtains the estimator biases and explains these using asymptotic approximations.