Political machines and the curse of public resources in subnational democracies
Bibliographic record
Abstract
Purpose This paper argues that decentralization reforms in Colombia, implemented since the 1980s, have led to the decentralization of political clientelism rather than its demise. Clientelism is a system of political and economic institutions that turns every local democracy into an extractive political institution. The authors theoretically demonstrate that an increase in public resources will increase corruption. Design/methodology/approach The authors develop and test a subnational public choice model, where clientelism in elections and corruption in public administration constitute a stable long-term institutional equilibrium. The model comprises two linked subgames: electoral tournament and corruption in public policy. The model makes two predictions that currently oppose predominant approaches: (1) increasing the severity of jail sentences to electoral crimes increases their price and the predominance of machine politics, instead of improving the quality of electoral tournaments and (2) increasing local governments' public finance increases clientelism in elections and corruption in public administration. Findings The authors find evidence in favor of the theoretical model of curse of public resources, using difference-in-differences estimation with a database 2016–17 of Colombia's 1,034 municipalities. This country is well-suited for our analysis because it has a long-term commitment to formal democratic processes (since 1958), while plagued by endemic corruption and clientelism problems. Originality/value (1) The theoretical approach is innovative and disruptive of current models on the problem, (2) the model builds upon the Colombian situation, a country with prominent corruption and political violence problems regardless of its relatively long-term commitment with free elections (since 1958) and (3) the theoretical discussion is tested using a comprehensive set of difference-in-differences estimations.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".