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Prosperity Across the United States: Revisiting the Isserman, Feser, and Warren Prosperity Index Using Sequence Analysis

Danielle Schmidt et al.

International Regional Science Review2025https://doi.org/10.1177/01600176251377424article
ABDC B
Weight
0.37

Abstract

Why do some places prosper while others do not? Measuring community-level prosperity is of widespread academic concern and public interest. While quality of life research on urban places is well established, insights into the prosperity of rural places are less developed. Further, much of the rural-oriented literature focuses on economic growth, which has the potential to mask non-growth prosperity characteristics. We follow Isserman et al. (2009) in their efforts to measure community-level prosperity outside the growth-paradigm for U.S. counties. We use geographic sequence analysis to build on their “prosperity index” by extending it longitudinally to measure prosperity at four (approximated) points in time (1990, 2000, 2008–2012, 2018–2022). Sequence analysis allows us to organize multivariate, longitudinal data into prosperity sequence sets – what we term “prosperity pathways” – thus highlighting the importance of time and history into a spatially-informed analysis of prosperity. Our findings enable us to confirm what is ostensibly true in that prosperity is a dynamic and evolutionary process with significant geographic variation.

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https://doi.org/https://doi.org/10.1177/01600176251377424

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@article{danielle2025,
  title        = {{Prosperity Across the United States: Revisiting the Isserman, Feser, and Warren Prosperity Index Using Sequence Analysis}},
  author       = {Danielle Schmidt et al.},
  journal      = {International Regional Science Review},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1177/01600176251377424},
}

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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