Abstract
We investigate the impact of gubernatorial re-election incentive and political factors on US public pension funds from 1990 to 2022. Our empirical analysis finds no significant overall relationship between gubernatorial re-election incentives and local bias in the full sample. However, the effect of gubernatorial re-election incentives on local bias is influenced by a state's level of corruption. Specifically, in states within the lowest corruption quantile, governors eligible for re-election tend to prioritize local investments to gain consistent support. In contrast, in states within the highest corruption quantile, heightened scrutiny may encourage re-election-eligible governors to adopt conservative investment policies that do not significantly influence local bias. Although re-election incentives may encourage politically motivated local investments in low-corruption states, they do not necessarily lead to negative outcomes. Instead, in these states, governors seeking re-election appear to positively influence pension fund performance and investment expenses, suggesting that electoral accountability may help align political incentives with prudent investment management. Additionally, we find that a change in the state governor's party affiliation is negatively associated with local bias, and Democratic governors appear to mitigate the impact of re-election incentives on local investment across both high- and low-corruption states. Other political variables do not exhibit statistically significant relationships with local bias.
Recommended Citation
Zhang, H., Guo, L., Hao, J., & Liu, Y. (2026). Gubernatorial Re-Election Incentives, Local Investment Bias, and Pension Fund Performance. Journal of Corporate Accounting and Finance Wiley.
The definitive version is available at https://doi.org/10.1002/jcaf.70039
Department(s)
Business and Information Technology
Publication Status
Open Access
Keywords and Phrases
corruption; local bias; political economy; public pension funds; re-election incentives
International Standard Serial Number (ISSN)
1097-0053; 1044-8136
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2026 Wiley, All rights reserved.
Publication Date
01 Jan 2026
