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Federal Institutions, State Agency Bias, and Unequal Bureaucratic Responsiveness in the U.S. OSHA Enforcement

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  • Doo-Rae Kim

Abstract

This research demonstrates the importance of the mediating role of agency preference distributions that differentiate the influence of political institutions on bureaucratic agencies. A spatial model is developed in the context of U.S. regulatory federalism to posit that the responsiveness of state agencies to federal institutions will be greater as state agencies exhibit a stronger policy bias by enforcing regulatory rules at an either extremely low or high level. The results of Quantile Regression analysis of state enforcement of the U.S. Occupational Safety and Health Act show that bureaucratic responsiveness to the preferences of the federal institutions is unequal across different state agencies.

Suggested Citation

  • Doo-Rae Kim, 2007. "Federal Institutions, State Agency Bias, and Unequal Bureaucratic Responsiveness in the U.S. OSHA Enforcement," International Review of Public Administration, Taylor & Francis Journals, vol. 12(2), pages 21-32, January.
  • Handle: RePEc:taf:rrpaxx:v:12:y:2007:i:2:p:21-32
    DOI: 10.1080/12294659.2008.10805102
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    References listed on IDEAS

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    1. Roger Koenker & Vasco d'Orey, 1994. "A Remark on Algorithm as 229: Computing Dual Regression Quantiles and Regression Rank Scores," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 43(2), pages 410-414, June.
    2. Scholz, John T. & Wei, Feng Heng, 1986. "Regulatory Enforcement in a Federalist System," American Political Science Review, Cambridge University Press, vol. 80(4), pages 1249-1270, December.
    3. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    4. Carpenter, Daniel P., 1996. "Adaptive Signal Processing, Hierarchy, and Budgetary Control in Federal Regulation," American Political Science Review, Cambridge University Press, vol. 90(2), pages 283-302, June.
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