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A Data-Driven Algorithm to Redefine the U.S. Rural Landscape: Affinity Propagation as a Mixed-Data/Mixed-Method Tool

Author

Listed:
  • Benjamin W. Heumann
  • Marcello Graziano
  • Maurizio Fiaschetti

Abstract

This study demonstrates the application of affinity propagation as a data-driven approach to identifying and mapping typologies of place along the urban-rural continuum. The authors characterize Zip Code Tabulation Areas using demographic, economic, land cover, and accessibility to transportation infrastructure, which results in 22 clusters, 15 of which have a major rural component. The spatial pattern of these clusters varies, reflecting the heterogeneity in U.S. rurality. Rural is not a single concept that can be simply defined by population density. By comparing three economic indicators before and after the global financial crisis of 2007 to 2012, the authors find that the degree of economic recovery is captured by rural typologies. They compare both the methodological results and analysis of socioeconomic resilience to two of the most used threshold-based regional typologies, one developed by the U.S. Department of Agriculture Economic Research Service and one used by the American Communities Project.

Suggested Citation

  • Benjamin W. Heumann & Marcello Graziano & Maurizio Fiaschetti, 2022. "A Data-Driven Algorithm to Redefine the U.S. Rural Landscape: Affinity Propagation as a Mixed-Data/Mixed-Method Tool," Economic Development Quarterly, , vol. 36(3), pages 294-316, August.
    • Handle: RePEc:sae:ecdequ:v:36:y:2022:i:3:p:294-316
    DOI: 10.1177/08912424221103556
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    1. Liu, Yaqin & Zhao, Guohao & Zhao, Yushan, 2016. "An analysis of Chinese provincial carbon dioxide emission efficiencies based on energy consumption structure," Energy Policy, Elsevier, vol. 96(C), pages 524-533.
    2. Justin R. Pierce & Peter K. Schott, 2020. "Trade Liberalization and Mortality: Evidence from US Counties," American Economic Review: Insights, American Economic Association, vol. 2(1), pages 47-64, March.
    3. Lewis Dijkstra & Hugo Poelman & Andrés Rodríguez-Pose, 2020. "The geography of EU discontent," Regional Studies, Taylor & Francis Journals, vol. 54(6), pages 737-753, June.
    4. Mallory L. Rahe & Bruce Weber & Xiurou Wu & Monica Fisher, 2019. "Income Inequality and County Economic Resistance to Job Loss during the Great Recession," The Review of Regional Studies, Southern Regional Science Association, vol. 49(1), pages 129-147.
    5. Angelos Mimis & Thomas Georgiadis, 2013. "Economic clustering of countries in the Asia-Pacific region," International Journal of Social Economics, Emerald Group Publishing, vol. 40(4), pages 355-366, April.
    6. Rafael Boix & Joan Trullén, 2007. "Knowledge, networks of cities and growth in regional urban systems," Papers in Regional Science, Wiley Blackwell, vol. 86(4), pages 551-574, November.
    7. C. Kirabo Jackson & Rucker C. Johnson & Claudia Persico, 2016. "The Effects of School Spending on Educational and Economic Outcomes: Evidence from School Finance Reforms," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(1), pages 157-218.
    8. repec:rre:publsh:v49:y:2019:i:1 is not listed on IDEAS
    9. John B. Parr, 2014. "The Regional Economy, Spatial Structure and Regional Urban Systems," Regional Studies, Taylor & Francis Journals, vol. 48(12), pages 1926-1938, December.
    10. Andrew M. Isserman & Edward Feser & Drake E. Warren, 2009. "Why Some Rural Places Prosper and Others Do Not," International Regional Science Review, , vol. 32(3), pages 300-342, July.
    11. Susan Athey & Guido W. Imbens, 2019. "Machine Learning Methods That Economists Should Know About," Annual Review of Economics, Annual Reviews, vol. 11(1), pages 685-725, August.
    12. Athey, Susan & Imbens, Guido W., 2019. "Machine Learning Methods Economists Should Know About," Research Papers 3776, Stanford University, Graduate School of Business.
    13. Angelos Mimis & Thomas Georgiadis, 2013. "Economic clustering of countries in the Asia‐Pacific region," International Journal of Social Economics, Emerald Group Publishing Limited, vol. 40(4), pages 355-366, March.
    14. John A. Hird, 1993. "Environmental policy and equity: The case of superfund," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 12(2), pages 323-343.
    15. Arnoud Lagendijk, 2003. "Towards Conceptual Quality in Regional Studies: The Need for Subtle Critique - A Response to Markusen," Regional Studies, Taylor & Francis Journals, vol. 37(6-7), pages 719-727.
    16. Waldorf, Brigitte S., 2006. "A Continuous Multi-dimensional Measure of Rurality: Moving Beyond Threshold Measures," 2006 Annual meeting, July 23-26, Long Beach, CA 21383, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    17. Theodore M. Crone, 2005. "An Alternative Definition of Economic Regions in the United States Based on Similarities in State Business Cycles," The Review of Economics and Statistics, MIT Press, vol. 87(4), pages 617-626, November.
    18. Angelos Mimis & Thomas Georgiadis, 2013. "Economic clustering of countries in the Asia‐Pacific region," International Journal of Social Economics, Emerald Group Publishing Limited, vol. 40(4), pages 355-366, March.
    19. Xu, Chuanbo & Wu, Yunna & Dai, Shuyu, 2020. "What are the critical barriers to the development of hydrogen refueling stations in China? A modified fuzzy DEMATEL approach," Energy Policy, Elsevier, vol. 142(C).
    20. Paul E. Green & Ronald E. Frank & Patrick J. Robinson, 1967. "Cluster Analysis in Test Market Selection," Management Science, INFORMS, vol. 13(8), pages 387-400, April.
    21. Luisa Gagliardi & Marco Percoco, 2017. "The impact of European Cohesion Policy in urban and rural regions," Regional Studies, Taylor & Francis Journals, vol. 51(6), pages 857-868, June.
    22. Janetta Nestorová Dická & Alena Gessert & Ivo Sninčák, 2019. "Rural and non-rural municipalities in the Slovak Republic," Journal of Maps, Taylor & Francis Journals, vol. 15(1), pages 84-93, January.
    23. Benjamin W. Heumann & Matthew E. Liesch & Nicholas R. Bogen & Ryan A. Meier & Marcello Graziano, 2020. "The contiguous United States in eleven zip codes: identifying and mapping socio-economic census data clusters and exemplars using affinity propagation," Journal of Maps, Taylor & Francis Journals, vol. 16(1), pages 57-67, January.
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