Regression discontinuity design could be a valuable tool for identifying causal effects of a given party holding a legislative majority. However, the variable “number of seats” takes a finite number of values rather than a continuum and, hence, it is not suited as a running variable. Recent econometric advances suggest the necessary assumptions and empirical tests that allow us to interpret small intervals around the cut-off as local randomized experiments. These permit us to bypass the assumption that the running variable must be continuous. Herein, we implement these tests for US state legislatures and propose another: whether a slim-majority of one seat had at least one state-level district result that was itself a close race won by the majority party.

Facebook ads are increasingly used by political scientists as a method of survey recruitment. A key advantage is said to be the ability to recruit targeted audiences defined by demographics, political beliefs, location, and numerous other attributes. The same feature has been decried by non-researchers concerned about potential racial discrimination and foreign influence in elections. The extent to which these ads actually reach their targets, however, is unknown. Using a series of six surveys and 20 targeted ads, I show these ads regularly fail to reach their targets. The success rate ranges from 23 to 99 percent, and ads targeted toward groups defined by self-reported data and broader geographic locations are generally more successful.