Measuring the Difference (X — Y) of Simulated Distributions: A Convolutions Approach
指出常用的重抽样分布差异显著性检验（如正态假设或置信区间重叠法）往往不适用，并提出一种基于卷积方法的经验检验，用于评估重抽样产生的近似经验分布之间的统计显著性，并通过二分选择条件估值数据案例进行说明。
Abstract Resampling or simulation techniques are now frequently used in applied economic analyses. However, significance tests for differences between empirical distributions have either invoked normality assumptions or have used nonoverlapping confidence interval criteria. We demonstrate that such methods generally will not be appropriate, and we present an empirical test, based on the method of convolutions, for assessing the statistical significance between approximate empirical distributions created by resampling techniques. The proposed convolutions approach is illustrated in a case study involving empirical distributions from dichotomous choice contingent valuation data.