Effects of fiscal decentralization on economic growth and human development index in the Indonesian local governments
Bibliographic record
Abstract
The implementation of regional autonomy has implications for the transfer of authority between the center and the regions in various fields.The existence of regional autonomy will result in decentralization which involves the management of regional finances, economic planning, including arranging regional development programs and other plans delegated from the center to the regions.The purpose of this study was to examine the effect of fiscal decentralization on economic growth and the index of human development in districts and cities in North Maluku Province.The population of this study consisted of 7 districts and 2 cities.The data is secondary data for the period 2011 to 2015, sourced from the Central Statistics Agency (BPS) Jakarta, districts and cities in North Maluku Province, published.The collected data were analyzed using path analysis techniques using the SPSS program package.The results of the study indicate that the effect of fiscal decentralization on economic growth had a positive path coefficient with a level of probability which was not significant.This shows that hypothesis one which states that fiscal decentralization has a significant effect on the economic growth of districts and cities in North Maluku Province.These results suggest that the higher the fiscal decentralization, the higher the economic growth.The effect of fiscal decentralization on the human development index has a positive path coefficient with a significant level of probability.This implies that the higher the fiscal decentralization, the higher the human development index.The effect of economic growth on the human development index has a positive coefficient with a significant level of probability.These results indicate that the higher the economic growth, the higher the index of human development.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".