Testing the Presence of Outliers in Regression Models*
提出两组检验回归模型中异常值整体存在性的统计检验方法，并应用于北美首个大型碳税对交通二氧化碳排放影响的差分模型，发现未征税对照组存在显著异常值导致政策效果被高估。
We propose two sets of tests for the overall presence of outliers in regression models. First, ‘simple’ tests on whether the proportion and the number of detected outliers deviate from their expected values. Second, ‘scaling’ tests on whether the proportion of outliers decreases with the cut‐off used to detect outliers. We apply our tests to a panel difference‐in‐differences model of transport CO 2 emissions in response to the introduction of North America's first major carbon tax. Our tests show the presence of significant outliers in the un‐taxed control group, which results in an overestimation of the estimated impacts of the tax.