Publication | Closed Access
Pretest with Caution: Event-Study Estimates after Testing for Parallel Trends
653
Citations
32
References
2022
Year
EngineeringRare Event EstimationApplied EconometricsParallel TrendsTime Series EconometricsData ScienceEconomic AnalysisParallel ComputingStatisticsEconomicsEconomic TrendCommon PracticeEconometric MethodPerformance Analysis ToolFinanceRegression TestingLow PowerFinancial EconomicsSoftware TestingParallel Performance EvaluationBusinessEconometricsParallel ProgrammingTrend AnalysisConventional Pre-trends Tests
This paper discusses two important limitations of the common practice of testing for preexisting differences in trends (“ pre-trends”) when using difference-in-differences and related methods. First, conventional pre-trends tests may have low power. Second, conditioning the analysis on the result of a pretest can distort estimation and inference, potentially exacerbating the bias of point estimates and under-coverage of confidence intervals. I analyze these issues both in theory and in simulations calibrated to a survey of recent papers in leading economics journals, which suggest that these limitations are important in practice. I conclude with practical recommendations for mitigating these issues. (JEL A14, C23, C51)
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