Robust Inference on Average Economic Growth*
提出一种估计平均经济增长置信区间的方法，该方法对时间序列的单位根性质误设具有稳健性，并通过子抽样方法实现，模拟和实证均支持其有效性。
Abstract We discuss a method to estimate the confidence bounds for average economic growth, which is robust to misspecification of the unit root property of a given time series. We derive asymptotic theory for the consequences of such misspecification. Our empirical method amounts to an implementation of the subsampling procedure advocated in Romano and Wolf ( Econometrica , 2001, Vol. 69, p. 1283). Simulation evidence supports the theory and it also indicates the practical relevance of the subsampling method. We use quarterly postwar US industrial production for illustration and we show that non‐robust approaches rather lead to different conclusions on average economic growth than our robust approach.