Indirect Inference, Nuisance Parameter, and Threshold Moving Average Models
分析了当冗余参数在原假设下无法识别时，间接推断方法需要做的调整，并开发了适用于检测阈值移动平均模型中阈值效应的检验程序，最后用该模型测度美国产出冲击的持续性。
AbstractWe analyze the modifications that occur in indirect inference when a nuisance parameter is not identified under the null hypothesis. We develop a testing procedure adapted to this simulation-based estimation method, and detail its use for detecting the threshold effect in threshold moving average models with contemporaneous and lagged asymmetries. In contrast to existing threshold models, these models allow taking into account the presence of asymmetric effects of current and lagged random shocks. We use them to measure the persistence of shocks to U.S. output.KEY WORDS: Asymmetric time seriesGNP analysisp-value transformationShock persistenceSimulation-based inference