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Reelection Incentives and Corruption: Revisiting the Evidence with LLM-Classified Audit Reports

Author

Listed:
  • Ricardo Dahis

    (Department of Economics, Monash University)

  • Martin Mattsson

    (Department of Economics, National University of Singapore)

  • Nathalia Sales

    (Department of Economics, PUC-Rio)

Abstract

We revisit the literature about the impact of reelection incentives on corruption with an extended dataset of corruption audit reports classified with Large Language Model (LLM). We first show that correlations between the LLM-generated corruption measures and manually coded assessments are comparable to correlations among the manual datasets themselves. Our results support previous findings in the literature, although the result is only statistically significant for one out of three measures of corruption. We document significant heterogeneity in the effect over time and investigate several explanations for these empirical patterns, including changing composition of politicians and increasing probability of legal penalties.

Suggested Citation

  • Ricardo Dahis & Martin Mattsson & Nathalia Sales, 2025. "Reelection Incentives and Corruption: Revisiting the Evidence with LLM-Classified Audit Reports," Monash Economics Working Papers 2025-08, Monash University, Department of Economics.
    • Handle: RePEc:mos:moswps:2025-08
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    References listed on IDEAS

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    More about this item

    Keywords

    reelection incentives; corruption; LLM;
    All these keywords.

    JEL classification:

    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law
    • O17 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Formal and Informal Sectors; Shadow Economy; Institutional Arrangements

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