New Area- and Population-based Geographic Crosswalks for U.S. Counties and Congressional Districts, 1790-2020

Principal Investigator(s): View help for Principal Investigator(s) Andreas Ferrara, University of Pittsburgh; Patrick A. Testa, Tulane University; Liyang Zhou, University of Pittsburgh

Version: View help for Version V4

Name	File Type	Size	Last Modified
1790			10/19/2022 10:40:PM
1800			10/19/2022 10:41:PM
1810			10/19/2022 10:41:PM
1820			10/19/2022 10:42:PM
1830			10/19/2022 10:43:PM
1840			10/19/2022 10:43:PM
1850			10/19/2022 10:44:PM
1860			10/19/2022 10:44:PM
1870			10/19/2022 10:45:PM
1880			10/19/2022 10:45:PM

Citation:

Ferrara, Andreas, Testa, Patrick A., and Zhou, Liyang. New Area- and Population-based Geographic Crosswalks for U.S. Counties and Congressional Districts, 1790-2020: crosswalks: CountyToCounty. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2022-10-19. https://doi.org/10.3886/E150101V4-157901

To view the citation for the overall project, see http://doi.org/10.3886/E150101V4.

Project Description

Summary: A common problem in applied research involves harmonizing geographic units across time or different levels of aggregation. We provide crosswalks that allow researchers i) to harmonize U.S. county boundaries over time across Census decades and ii) to generate congressional district level variables from county-level data. The crosswalks include an area-based approach as in Hornbeck (2010), as well as the new population-based methods from Ferrara, Testa, and Zhou (2021), which are based on granular sub-county population information. We also provide teaching material to demonstrate the utility of these new crosswalks.

Reference:
Ferrara, A., Testa, P.A., and Zhou, L. (2022) "New Area- and Population-based Geographic Crosswalks for U.S. Counties and Congressional Districts, 1790-2020", SSRN working paper: https://dx.doi.org/10.2139/ssrn.4019521

Scope of Project

Geographic Coverage: USA

Universe: U.S. counties and congressional districts

Data Type(s): geographic information system (GIS) data

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