Has the growth of Islamic banking had impact to economic growth in Indonesia?
Bibliographic record
Abstract
Islamic banking development is rife in many countries, including Indonesia. The first Islamic bank in Indonesia was established in 1992. Having experience for almost a quarter decade, there is a question whether the growth of Islamic banking has had impact to the economic growth in Indonesia or not. We choose 3 (three) indicators of the growth of Islamic banking, which are TPF (Third Party Funds), the assets, and total funding. The indicators of economic growth in Indonesia used in this research are GDP (Gross Domestic Product), the growth rate of GDP by Bank Industry and Inflation. The data is taken for period 2003-2013 from public domain in Indonesian Financial Services Authority's website and other resources. The relationship among those variables is made using Time Series model. The results show that the Islamic Banking growth has not given significant impact to economic growth. Using the some simplified assumptions, we do the analysis again using the estimated model of growth whether this condition will happen in 10 and 15 years ahead. If the defined assumption is fulfilled, we conclude that the existence of Islamic Banking in Indonesia would fully give significant impact on economic growth in 2028.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".