The Impact of the Mechanism for Aligning Horizontal Fiscal Imbalances on the Stability of the Financial System
Bibliographic record
Abstract
The growth of state transfers to offset disparities in regional development affects the stability of the country’s financial system. This article delves into this outcome, empirically analyzing whether the transfer system for horizontal fiscal alignment leads to decreased financial system stability through increased borrowing at municipal and national levels. To test this hypothesis, we employ a quasi-experimental analysis strategy, examining potential scenarios of configuring transfers to Ukrainian municipalities for addressing horizontal fiscal imbalance. Across various transfer calculation scenarios involving changes in the calculation period, the number of budgets in consideration, and the alignment subject, we find that a suboptimal system of horizontal fiscal alignment, transferring funds from financially secure municipalities to insecure ones, leads to a rise in the public finance debt, subsequently decreasing financial system stability. Additionally, we discover that the current mechanism in Ukraine for horizontal fiscal alignment, designed to mitigate inequalities in socio-economic development among communities and regions, paradoxically exacerbates these disparities, artificially inflates indicators of decentralization reform success, and undermines public finance stability.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".