Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
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.