Recognizing that cross-sectional data are often insufficient to address the identification problems associated with estimating the effect of government taxation or spending, economists engaged in public finance research often utilize longitudinal data that span the period over which a policy change occurred. As economic data have proliferated over the last decade, uses of the difference-in-differences design and its variations have become more numerous. Nevertheless, published research that invokes difference-in-differences commonly fails to present evidence and reasoning that enable the reader to properly evaluate the causal claims under investigation. In this paper, we examine the threats to internal validity that exist when using difference-in-differences for causal inference and review variations of the design that can be used to address these threats. Next, we survey the public finance literature in order to examine the ways that these threats are addressed in practice. We conclude by proposing a number of recommendations for researchers to consider as they implement difference-in-differences as an empirical strategy.
|Original language||English (US)|
|Journal||National Tax Journal|
|State||Published - Jun 2015|