In empirical work, researchers frequently test hypotheses of parallel form in several regressions, which raises concerns about multiple testing. One way to address the multiple-testing issue is to jointly test the hypotheses (for example, Pei, Pischke, and Schwandt [2019, Journal of Business & Economic Statistics 37: 205–216] and Lee and Lemieux [2010, Journal of Economic Literature 48: 281–355]). While the existing commands suest (Weesie, 1999, Stata Technical Bulletin Reprints 9: 231–248) and mvreg enable Stata users to follow this approach, both are limited in several dimensions. For instance, mvreg assumes homoskedasticity and uncorrelatedness across sampling units, and neither command is designed to be used with panel data. In this article, we introduce the new community-contributed command stackreg, which overcomes the aforementioned limitations and allows for some settings and features that go beyond the capabilities of the existing commands. To achieve this, stackreg runs an ordinary least-squares regression in which the regression equations are stacked as described, for instance, in Wooldridge (2010, Econometric Analysis of Cross Section and Panel Data, p. 166–173, MIT Press) and applies cluster–robust variance–covariance estimation.

在实证工作中，研究人员经常在多个回归中测试平行形式的假设，这引起了对多重测试的担忧。解决多重检验问题的一种方法是联合检验假设（例如，Pei、Pischke 和 Schwandt [2019, Journal of Business & Economic Statistics 37: 205–216] 和 Lee and Lemieux [2010, Journal of Economic文献48：281–355]）。虽然现有命令suest（Weesie，1999，Stata Technical Bulletin Reprints 9: 231–248）和mvreg使 Stata 用户能够遵循这种方法，但两者都在几个方面受到限制。例如，mvreg假设采样单元之间具有同方差性和不相关性，并且这两个命令均不设计用于面板数据。在本文中，我们介绍了社区贡献的新命令stackreg，它克服了上述限制并允许一些超出现有命令功能的设置和功能。为了实现这一点，stackreg运行了一个普通的最小二乘回归，其中回归方程按照 Wooldridge（2010，横截面和面板数据的计量经济学分析，第 166-173 页，麻省理工学院出版社）中的描述进行堆叠并应用聚类稳健方差协方差估计。