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Principal-Agent Models of Political Control of Bureaucracy

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  • Cook, Brian J.
  • Wood, B. Dan

Abstract

In the March 1988 issue of this Review, B. Dan Wood invoked a principal-agent perspective to establish the importance of democratic hierarchies in shaping the outputs of public bureaucracies. He tested the model with air pollution enforcements of the Environmental Protection Agency (EPA) between 1977 and 1985. His results suggested some limitations on bureaucracies' responsiveness to elected political institutions, consistent with a principal-agent perspective with emphasis on the agent. Brian J. Cook challenges features of the design and empirical testing of Wood's hierarchical model. He questions the accuracy of Wood's characterization of the extent of EPA autonomy and power. Cook argues that a proper model requires recognition of the multiple principal nature of the U.S. system, and he advocates consideration of the normative foundations of principal-agent theory. Wood responds to both the substantive and methodological issues raised and suggests an eclectic approach in future research.

Suggested Citation

  • Cook, Brian J. & Wood, B. Dan, 1989. "Principal-Agent Models of Political Control of Bureaucracy," American Political Science Review, Cambridge University Press, vol. 83(3), pages 965-978, September.
    • Handle: RePEc:cup:apsrev:v:83:y:1989:i:03:p:965-978_08
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    Cited by:

    1. Matthew Amengual & Janice Fine, 2017. "Co‐enforcing Labor standards: the unique contributions of state and worker organizations in Argentina and the United States," Regulation & Governance, John Wiley & Sons, vol. 11(2), pages 129-142, June.
    2. Inkyu Kang, 2023. "How does technology‐based monitoring affect street‐level bureaucrats' behavior? An analysis of body‐worn cameras and police actions," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 42(4), pages 971-991, September.
    3. James Lawson, 2022. "Mounting Turbulence in Neoliberal Globalization: Political Economy, Populist Discourse, and Policy in Alberta, Canada," Social Sciences, MDPI, vol. 11(5), pages 1-30, May.
    4. Kim, Eun-Sung, 2020. "Deep learning and principal–agent problems of algorithmic governance: The new materialism perspective," Technology in Society, Elsevier, vol. 63(C).
    5. Xueying Yu, 2016. "Central–local conflicts in China’s environmental policy implementation: the case of the sloping land conversion program," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 84(1), pages 77-96, November.

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