The Influence of Mayors’ Characteristics and Elections on the Composition of Brazilian Municipalities’ Expenditures
Bibliographic record
Abstract
This paper disentangles the main factors conditioning the levels and composition of public expenditures on a large panel of Brazilian municipalities. Using the IMF’s classification of expense by functions of government, it is possible to analyze how personal characteristics of Brazilian mayors influence the fiscal policy. Empirical results suggest that expenditures increase during the year before election years. During local election years, there is no evidence of an opportunistic manipulation of expenditure composition. However, in the year before local election, mayors favor items highly visible and appreciated by the electorate, such as housing and community amenities, and recreation, culture, and religion. Political alignment with matters both for the level and weights of expenditures by function. Mayors’ ideology is associated with lower weight of recreation, culture, and religion. Ideology, gender, university education and party similarity with higher levels of government are relevant at local election years. We also find demographic and socioeconomic characteristics of municipalities influence the level of expenditures.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".