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The Accuracy of Identifying Constituencies with Geographic Assignment Within State Legislative Districts

Published online by Cambridge University Press:  03 February 2023

Tyler Steelman Open the ORCID record for Tyler Steelman [Opens in a new window]  and
John A. Curiel Open the ORCID record for John A. Curiel [Opens in a new window]
Tyler Steelman*
Affiliation:
Office of Institutional Research and Assessment, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
John A. Curiel
Affiliation:
Political Science, Ohio Northern University, Ada, OH, USA
*
Corresponding author: Tyler Steelman, email: tsteelman@unc.edu
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Abstract

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, such as ZIP codes, to estimate constituency membership. In this study, 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), “The Role of Constituency, Party, and Industry in Pennsylvania’s Act 13,” State Politics and Policy Quarterly 17 (2): 154–79. 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.

Keywords

GIS/Spatial AnalysisLobbyingRedistrictingRoll Call Voting
Type
Original Article
Information
State Politics & Policy Quarterly , Volume 23 , Issue 2 , June 2023 , pp. 218 - 232
Copyright
© The Author(s), 2023. Published by Cambridge University Press and State Politics & Policy Quarterly

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Supplementary material: Link

Steelman and Curiel Dataset

Dataset

https://doi.org/10.15139/S3/WIN7SM
Link