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Partisan bias and performance improvement efforts in program administration: evidence from unemployment insurance programs in the American states

George Krause & Ji Wan Hong

Journal of Public Administration Research and Theory2026https://doi.org/10.1093/jopart/muag005article
AJG 4ABDC A
Weight
0.50

Abstract

One critical way that public agencies can improve administrative performance is through its discretionary efforts at detecting program errors. This requires an alignment between political and administrative objectives within executive branch governance. Specifically, we hypothesize that agency efforts for detecting benefit overpayment errors from state unemployment insurance (UI) programs will be higher under Republican partisan gubernatorial control of state UI agency heads compared to Democratic counterparts. Based on panel data consisting of 999 observations covering fifty state UI agencies between 2002 and 2021, our lognormal maximum likelihood estimates reveal a partisan differential between Republican and Democratic governors with direct appointment control over UIP agency heads are associated with a within-state average of $ 2.647 million higher correction of benefit overpayments to unemployed claimants (i.e., a per claimant overpayment case partisan differential of $ 618.68). State UIP agencies investments in performance improvement that identify program waste reflect the importance of partisan incentives, coupled with unity in executive branch governance.

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https://doi.org/https://doi.org/10.1093/jopart/muag005

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@article{george2026,
  title        = {{Partisan bias and performance improvement efforts in program administration: evidence from unemployment insurance programs in the American states}},
  author       = {George Krause & Ji Wan Hong},
  journal      = {Journal of Public Administration Research and Theory},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1093/jopart/muag005},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.