A Window of Opportunity: Anti‐Corruption and Performance Data Quality Enhancement

ABSTRACT Data manipulation plagues principals for providing noisy performance data. Yet, it also has pitfalls for agents, which receive relatively little attention in the literature. Due to the performance data manipulated by previous agents, incumbent agents fall into the dilemma regarding whether to continue or curb data manipulation. We argue that to navigate the dilemma, political agents leverage the anti‐corruption opportunity window to curb data manipulation. Using panel data from China's local governments spanning 2001–2018, we find evidence supporting this claim. Local government leaders reduce data manipulation when their predecessors are expelled. Furthermore, leaders reduce data manipulation to a greater extent in response to the negative performance feedback. It is also more likely for leaders promoted from outside of the jurisdiction to reduce data manipulation during the opportunity window. These results advance the literature on data manipulation and have implications for performance management.

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Publication Details

Journal
Public Administration Review
Published
2025-09-22
DOI
https://doi.org/10.1111/puar.70044
Primary Topic
Data Quality and Management
Type
article
Field-Weighted Citation Impact
0.00
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article

A Window of Opportunity: Anti‐Corruption and Performance Data Quality Enhancement

Xiao Tang, Jingyu Zhang, Yuxin Pan
Public Administration Review
Data Quality and Management
article

A Window of Opportunity: Anti‐Corruption and Performance Data Quality Enhancement

Xiao Tang, Jingyu Zhang, Yuxin Pan
article en

Abstract

ABSTRACT Data manipulation plagues principals for providing noisy performance data. Yet, it also has pitfalls for agents, which receive relatively little attention in the literature. Due to the performance data manipulated by previous agents, incumbent agents fall into the dilemma regarding whether to continue or curb data manipulation. We argue that to navigate the dilemma, political agents leverage the anti‐corruption opportunity window to curb data manipulation. Using panel data from China's local governments spanning 2001–2018, we find evidence supporting this claim. Local government leaders reduce data manipulation when their predecessors are expelled. Furthermore, leaders reduce data manipulation to a greater extent in response to the negative performance feedback. It is also more likely for leaders promoted from outside of the jurisdiction to reduce data manipulation during the opportunity window. These results advance the literature on data manipulation and have implications for performance management.

Public Administration Review
Tsinghua University (CN)
Openalex Percentile: Top 70%
Data Quality and Management
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