Replication Data for: The Accuracy of Identifying Constituencies with Geographic Assignment Within State Legislative Districts

Identifying the geographic constituencies of representatives is among the most crucial, yet challenging, aspects of state and local politics research. Regularly changing district lines, incomplete data, and computational obstacles can present barriers to matching individuals to their respective districts. Geocoding residential addresses is the ideal method for matching purposes. However, cost constraints can limit its applicability for many researchers, leading to geographic assignment methods that use polygonal units, like ZIP Codes, to estimate constituency membership. In this letter, we quantify the trade-offs between three geographic assignment matching methods--centroid, geographic overlap, and population overlap matching--on the assignment of individual voters to state legislative districts. We confirm that population overlap matching produces the highest accuracy in assigning voters to their state legislative districts when polygonal location data are all that is available. We validate this finding by improving model estimates of lobbying influence through a replication analysis of Bishop and Dudley (2017). Our replication suggests that distinguishing between out-of-district and in-district donations reveals a greater impact for in-district lobbying efforts. We make evident that population overlap assignment can confidently be used to identify constituencies when precise location data is not available.