Toward a New Rural Typology: Mapping Resources, Opportunities, and Challenges. Issue 3 (August 2022)

• Record Type: Journal Article
• Authors: Khalaf, Christelle; Michaud, Gilbert; Jolley, G. Jason
• Is Part Of: Economic development quarterly. Volume 36:Issue 3(2022)
• Page Start: 276
• Page End: 293
• Publication Date: 2022-08
• Subjects: unsupervised machine learning -- economic development -- county typology -- rurality; Economic development -- Periodicals; Economics -- Periodicals; United States -- Economic conditions -- Periodicals; 330.973
• DOI: 10.1177/08912424211069122
• Languages: English
• ISSNs: 0891-2424

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.