Using did_multiplegt_dyn to Estimate Event-Study Effects in Complex Designs: Overview, and Four Examples Based on Real Datasets

TL;DR

This paper introduces the did_multiplegt_dyn command for estimating event-study effects in complex treatment designs, demonstrating its properties through simulations and four real-data examples with diverse treatment types.

Contribution

It provides an overview of the estimators, explores their properties via simulations, and applies the command to real datasets with various complex treatment scenarios.

Findings

Estimators perform well across different complex treatment designs.

The command effectively captures dynamic effects in non-binary treatments.

Applications demonstrate versatility in real-world datasets.

Abstract

The command did_multiplegt_dyn can be used to estimate event-study effects in complex designs with a potentially non-binary and/or non-absorbing treatment. This paper starts by providing an overview of the estimators computed by the command. Then, simulations based on three real datasets are used to demonstrate the estimators' properties. Finally, the command is used on four real datasets to estimate event-study effects in complex designs. The first example has a binary treatment that can turn on an off. The second example has a continuous absorbing treatment. The third example has a discrete multivalued treatment that can increase or decrease multiple times over time. The fourth example has two, binary and absorbing treatments, where the second treatment always happens after the first.