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 |
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| crosswalks | 02/09/2022 11:43:AM | ||
| replication-files | 10/19/2022 10:15:PM | ||
| teaching-material | 10/18/2021 09:26:AM | ||
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Unknown | 56.8 KB | 10/19/2022 07:03:PM |
Project 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. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2022-10-19. https://doi.org/10.3886/E150101V4
Project Description
Summary:
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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
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:
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USA
Time Period(s):
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1790 – 2020
Universe:
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U.S. counties and congressional districts
Data Type(s):
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geographic information system (GIS) data
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