Doulo Sow | Searcharxiv

arXiv2025

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

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.

econ.EM↗

arXiv2022

Difference-in-Differences Estimators for Treatments Continuously Distributed at Every Period

When studying the effects of taxes, tariffs, or prices using panel data, the treatment is often continuously distributed in every period. We develop difference-in-differences (DID) estimators for such settings. We partition units into switchers, whose treatment changes between consecutive periods, and stayers, whose treatment remains constant. Under a parallel-trends assumption, we show that the slopes of switchers' potential outcomes with respect to the treatment are nonparametrically identified by DID comparisons between switchers and stayers sharing the same baseline treatment level. Conditioning on the baseline treatment is key, as it ensures that the underlying parallel-trends assumption accommodates time-varying treatment effects. We then study two weighted averages of these slopes, discuss their respective advantages, and propose for each a doubly robust, semiparametrically efficient, and $\sqrt{n}$-consistent estimator. Finally, we extend our framework to instrumental variables and illustrate it by estimating the effects of gasoline taxes on prices and fuel consumption.

econ.EM↗