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Local government transparency across the election cycle: Do text and numbers tell the same story?

Pierre Donatella & Emmeli Runesson

International Review of Administrative Sciences2026https://doi.org/10.1177/00208523261417827article
AJG 3ABDC B
Weight
0.50

Abstract

This study examines how political pressure, as proxied by the election cycle, influences the alignment between textual sentiment and financial performance in municipal annual reports. Based on nearly 4000 reports prepared by Swedish municipalities (2010–2023), we apply sentiment analysis and fixed effects regression models. We find that textual sentiment is generally associated with financial performance. However, we also document a clear election cycle effect: reports for pre-election years − issued during election years, when political pressure is presumably at its peak­­ − exhibit more positive sentiment regardless of financial performance. This effect is partly driven by municipalities with relatively poor performance, suggesting that textual disclosures are used to downplay negative outcomes when political stakes are high. By documenting how the reliability of textual information shifts under political pressure, our study contributes to research on government financial transparency and highlights the need for stakeholder caution when interpreting textual information during election periods.

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https://doi.org/https://doi.org/10.1177/00208523261417827

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@article{pierre2026,
  title        = {{Local government transparency across the election cycle: Do text and numbers tell the same story?}},
  author       = {Pierre Donatella & Emmeli Runesson},
  journal      = {International Review of Administrative Sciences},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/00208523261417827},
}

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Local government transparency across the election cycle: Do text and numbers tell the same story?

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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.