Toward a New Rural Typology: Mapping Resources, Opportunities, and Challenges

Christelle Khalaf, Gilbert Michaud and G. Jason Jolley

Economic Development Quarterly, 2022, vol. 36, issue 3, 276-293

Abstract: While the concept of rurality has been debated in academic and professional literature for decades, less research has been done on a practical typology that can guide localized economic development strategies. This paper adds to the growing body of literature in search of a more nuanced definition of rural by applying unsupervised machine learning (ML) to the abundance of existing county-level data in the United States. The authors illustrate how this method can lead to a new county typology, named after economic development strategies, that accounts for idiosyncrasies in resources, opportunities, and challenges. This research serves as a practical step toward tractable, heterogeneous classifications that can inform the work of federal, state, and local policy makers, economic development practitioners, and many others.

Keywords: unsupervised machine learning; economic development; county typology; rurality (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:sae:ecdequ:v:36:y:2022:i:3:p:276-293

DOI: 10.1177/08912424211069122

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