JOURNAL ARTICLE

"Logics of Redistribution" Under Welfare Reform: The Case of Welfare for Families with Children.

  • Published In: Journal of Sociology & Social Welfare, 2023, v. 50, n. 2. P. 4 1 of 3

  • Database: Sociology Source Ultimate 2 of 3

  • Authored By: Huaqui, Anthony 3 of 3

Abstract

This article builds upon the "logics of redistribution" approach to welfare state theory, which argues that different theoretical explanations, referred to as "logics", apply to different programs based on context and constituencies. I argue that individual programs' can have their logics change over time as well via institutional restructuring in policymaking. To demonstrate this, I use Aid to Families with Dependent Children (AFDC), later renamed Temporary Assistance for Needy Families (TANF), as a case. This program underwent institutional restructuring in 1996 by way of the Personal Responsibility and Work Opportunity Reconciliation Act (PRWORA). I use yearly state-level data from 1984 to 2015 to assess how three sets of theories (racial, political, and economic) influence benefit levels before and after PRWORA. Data is drawn from Michigan State University's Correlates of State Policy, the University of Kentucky's National Welfare Data, and Hirsch and MacPherson's Union Membership and Coverage datasets. Two-way fixed effects models find that how political and economic 'logics' apply to benefit levels change after institutional restructuring in 1996. Racial "logics" remain fairly consistent in both time periods. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Sociology & Social Welfare. 2023/06, Vol. 50, Issue 2, p4
  • Document Type:Article
  • Subject Area:Law
  • Publication Date:2023
  • ISSN:0191-5096
  • DOI:10.15453/0191-5096.4495
  • Accession Number:173006818
  • Copyright Statement:Copyright of Journal of Sociology & Social Welfare is the property of Western Michigan University and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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