Public Expenditure Management and Political Budget Cycles: The Case of Colima City Council 2009-2018
Bibliographic record
Abstract
The political budget cycles (PBC), as an evolutionary part of the economic political cycle (EPC), demonstrate the existence of opportunistic practices of economic variables, electoral, and budgetary that the politicians in power operate in their management to continue in office. In this sense, the literature suggests a pattern of opportunistic behavior on voters’ myopia, showing that there is little retrospective memory for voters, allowing the party in power to execute public policies successfully. Thus, the objective of the research is to analyze the existence of political budgetary cycles in the management of investment spending by the City of Colima from the years 2009 to 2018. Thus, the objective of the research is to analyze the existence of political budgetary cycles in the management of investment spending by the City of Colima from the years 2009 to 2018. This was analyzed using the panel data methodology (MCO; EF; EA), to estimate the variables dependent on investment and current expenditure, a dummy variable was introduced to identify the year before the election and to be able to control the influence of the electoral period on each regression. The results show that investment spending is related to election periods, population growth, and the federal social aid budget sector. Current expenditure was only related to population growth. This allows us to explain that spending is a resource that finances public works in the states of Mexico. Thus, this research shows that public works is a public expenditure that the states of Mexico apply more in times of elections.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".