Compliance Under Pressure: Strategic Bureaucratic Control and Policy Implementation in China

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2025-09-14

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2023

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Scholars contend that in weak institutional contexts, political leaders rely on informal networks or ad hoc campaigns to push through policies that challenge powerful local interests. My dissertation challenges this conventional view by arguing that top leaders in authoritarian regimes can effectively enhance local policy compliance by improving and adapting formal institutions to different local conditions, with the support of advanced technology and strong political commitment at the top. With a special focus on the central directives of differentiated work priorities and performance evaluation standards in the context of air pollution control in China, I find that a place-based performance evaluation system enables the central government to exert flexible political control over different regions by assigning them varying work priorities that cater to their specific local conditions and changing environment. In addition to the high-powered promotion incentive, I show that disclosing performance rankings creates an additional incentive for local officials to exert effort on future performance improvement, particularly those who appear at the bottom of the rankings. Finally, I argue that aligning local officials’ interests through formal institutions does not always yield desired outcomes, especially during times of political uncertainty. Informal institutions are, however, more effective in motivating local officials to carry out policy tasks because they can provide protection and assurance to officials. I substantiate this claim by examining how patronage networks shape China's local COVID-19 responses. In sum, a combination of formal and informal institutions remains at work in ensuring policy implementation and bureaucratic compliance in authoritarian countries.

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Gui, Xiaoshu (2023). Compliance Under Pressure: Strategic Bureaucratic Control and Policy Implementation in China. Dissertation, Duke University. Retrieved from https://hdl.handle.net/10161/29195.

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