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Three Models of US State-Level Charity Regulation

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  • Mitchell George E.

    (Austin W. Marxe School of Public and International Affairs, Baruch College, CUNY, One Bernard Baruch Way, Box D-0901, New York, NY, 10010-5585, USA)

Abstract

The existence of federal oversight of charitable organizations in the United States implies a degree of uniformity to US charity regulation. However, charity regulation is far from uniform across the country. States differ significantly in their adoption or non-adoption of various state-level regulatory requirements, creating not one but many different regulatory environments for charities. The complexity and diversity of these regulations has made it difficult for sector stakeholders, such as researchers, regulators, practitioners, information intermediaries, and donors, to understand the nature and significance of state-level charity regulation from a comparative perspective. To address this problem, this article employs latent class analysis to identify three distinct models of state-level charity regulation: broad regulation, limited regulation, and asset oversight. Subsequent analysis identifies relationships between a state’s economic, social, and political characteristics and its model of charity regulation, suggesting new avenues of research for understanding regulatory model emergence. Many additional practical applications of the typology are also discussed.

Suggested Citation

  • Mitchell George E., 2024. "Three Models of US State-Level Charity Regulation," Nonprofit Policy Forum, De Gruyter, vol. 15(1), pages 1-25, January.
  • Handle: RePEc:bpj:nonpfo:v:15:y:2024:i:1:p:1-25:n:2
    DOI: 10.1515/npf-2022-0051
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    References listed on IDEAS

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    1. George E. Mitchell & Sarah S. Stroup, 2020. "Domestic constraints on the global impact of US development transnational NGOs," Development in Practice, Taylor & Francis Journals, vol. 30(6), pages 774-783, August.
    2. Carolyn Cordery & Masayuki Deguchi, 2018. "Charity registration and reporting: a cross-jurisdictional and theoretical analysis of regulatory impact," Public Management Review, Taylor & Francis Journals, vol. 20(9), pages 1332-1352, September.
    3. Bakk, Zsuzsa & Oberski, Daniel L. & Vermunt, Jeroen K., 2014. "Relating Latent Class Assignments to External Variables: Standard Errors for Correct Inference," Political Analysis, Cambridge University Press, vol. 22(4), pages 520-540.
    4. Vermunt, Jeroen K., 2010. "Latent Class Modeling with Covariates: Two Improved Three-Step Approaches," Political Analysis, Cambridge University Press, vol. 18(4), pages 450-469.
    5. Bolck, Annabel & Croon, Marcel & Hagenaars, Jacques, 2004. "Estimating Latent Structure Models with Categorical Variables: One-Step Versus Three-Step Estimators," Political Analysis, Cambridge University Press, vol. 12(1), pages 3-27, January.
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