Improving inter-budgetary relations as a financial basis for regional development
Bibliographic record
Abstract
Currently, the development of Russia's regions is uneven, due to low tax revenues to regional budgets, as well as inefficient allocation of federal budget funds between individual regions. It is necessary to improve inter-budgetary relations in Russia in order to increase the financial independence of the regions and stimulate their economic development, which is currently difficult due to uneven tax revenues to regional budgets, as well as due to the priorities of state policy on financing the territories. The purpose of the study is to analyze Russian and foreign experience in reducing the gap between regions and creating more sustainable incentives for economic development. The objectives of the study are to identify problems based on the analysis and identify the ways to improve inter–budgetary relations in Russia. Materials and methods. The research used scientific publications, analytical reviews, articles, as well as data from open Internet sources. The study period is 2022–2024. In the course of the research, such methods as observation, statistical analysis, comparative analysis, and expert methods were used. Results. The article presents the results of a study of inter-budgetary relations in Russia, highlighting their role in balancing budgets at the federal, regional and local levels. Despite ensuring balanced regional development, this system has a high dependence of subjects on transfers, uneven tax potential and budget deficits, which limits their socio-economic activity. From the statistics for 2022-2024, it follows that the decrease in regional incomes amid rising costs is due, among other things, to a reduction in income tax and redistribution of funds in favor of national projects. Reforms were proposed to solve the problems, including expanding the tax powers of subjects, stimulating transfers, digitalization of processes, and adapting the foreign experience of Germany and Canada. The measures are aimed at increasing the financial independence of the regions, transparency and efficiency of budget regulation. Conclusions. Reforming inter-budgetary relations requires a combination of incentive mechanisms, a differentiated approach to regions, and introduction of digital tools. The use of international experience, including horizontal alignment and tax incentives for investments, will help to reduce dependence on transfers and stimulate economic growth. As a result, regions will be able to meet social obligations more effectively and overcome budget deficits.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".