Cross-Sectional Dependence and Problems in Inference in Market-Based Accounting Research
评估了股票收益研究中横截面依赖对统计推断的严重性，帮助研究者识别何时忽略这种依赖会导致显著性水平严重失真。
This paper provides a framework and some empirical evidence to evaluate the seriousness of problems in inference that arise in stockreturn-based studies when the data are cross-sectionally dependent. The study is motivated on the grounds that statistical procedures designed to address such problems are often infeasible, and even when they can be implemented they sometimes introduce other more serious difficulties. Thus, researchers have frequently adopted an approach that ignores the cross-sectional dependence (e.g., ordinary least squares [OLS]). The objective of this paper is to help identify the contexts in which ignoring the dependence would lead to serious misstatement of significance levels. Cross-sectional dependence in stock returns data is likely to exist when at least some of the returns are sampled from common time periods. This would be the case in all studies of the reaction of stock prices to a