Assessing Fiscal Sustainability in Indonesia: Error Correction Mechanism Diagnostic
Bibliographic record
Abstract
Indonesia's debt is increasing and is not controlled properly, which will result in a fiscal budget deficit. This study aims to determine the condition of fiscal sustainability in Indonesia by looking at the factors that affect the debt-to-GDP ratio in 2012 Quarter I to 2022 Quarter II. Fiscal sustainability can be seen from the debt-to-GDP ratio proxy variable and the independent variables used are the previous quarter's debt ratio, economic growth, inflation, and the exchange rate. This research is a qualitative type with a brief descriptive about the state of the debt ratio and the variables that influence it and quantitatively using the Error Correction Mechanism (ECM) using statistical software called EViews. The results show that in the long term the debt-to-GDP ratio in Indonesia is significantly influenced by the previous quarter's debt ratio, economic growth, inflation, and the exchange rate. Meanwhile, in the short term, changes in the debt to GDP ratio are significantly influenced by changes in the debt ratio in the previous quarter, changes in economic growth, and changes in inflation.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".