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The Impact of the #MeToo Movement on Language at Court -- A text-based causal inference approach
The causal effect of the #MeToo movement is estimated by means of a Difference-in-Differences approach comparing the development of the language in opinions on sexual offenses and other crimes against persons as well as a Panel Event Study approach.
Detecting Grouped Local Average Treatment Effects and Selecting True Instruments
Under an endogenous binary treatment with heterogeneous effects and multiple instruments, we propose a two-step procedure for identifying complier groups with identical local average treatment effects (LATE) despite relying on distinct instruments, even if several instruments violate the identifying assumptions.
How causal machine learning can leverage marketing strategies: Assessing and improving the performance of a coupon campaign
We apply causal machine learning algorithms to assess the causal effect of a marketing intervention, namely a coupon campaign, on the sales of a retailer.
