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The Community Explorer How to Inform Effectively Policy on U.S. Diversity with County Level Data

Author

Listed:
  • Lopez, Claude
  • Roh, Hyeongyul
  • Switek, Maggie

Abstract

The Community Explorer provides novel insightintoon the different characteristics of the U.S. population that can be used in policy design and impact assessment. More broadly, it increases the understanding of socio-economic gaps and potential markets in the U.S.. More specifically, it synthesizes the information of 751 variables across 3142 counties from the Census Bureau’s American Community Survey using machine learning methods, into 17 communities. Each one of these communities has a distinctive profile that combines demographic, economic, and many other behavior determinants while not being geographically bounded.

Suggested Citation

  • Lopez, Claude & Roh, Hyeongyul & Switek, Maggie, 2022. "The Community Explorer How to Inform Effectively Policy on U.S. Diversity with County Level Data," MPRA Paper 114020, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:114020
    as

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    File URL: https://mpra.ub.uni-muenchen.de/114020/1/MPRA_paper_114020.pdf
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    References listed on IDEAS

    as
    1. Robert Tibshirani & Guenther Walther & Trevor Hastie, 2001. "Estimating the number of clusters in a data set via the gap statistic," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(2), pages 411-423.
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    More about this item

    Keywords

    US diversity; equity; machine learning; clusters; census; county level data; data viz; interactive map;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • R0 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General
    • R1 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics
    • Y1 - Miscellaneous Categories - - Data: Tables and Charts

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