Methodological analysis reveals negative weights in two-way fixed effects regressions under heterogeneous treatment effects, highlighting substantial bias in standard empirical estimates.
Linear regressions with period and group fixed effects are widely used to estimate treatment effects. We show that they estimate weighted sums of the average treatment effects (ATE ) in each group and period, with weights that may be negative. Due to the negative weights, the linear regression coefficient may for instance be negative while all the ATEs are positive. We propose another estimator that solves this issue. In the two applications we revisit, it is significantly different from the linear regression estimator. (JEL C21, C23, D72, J31, J51, L82)
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Chaisemartin et al. (2020) studied this question.
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