Indonesia's Non-Oil Export Performance During the Economic Crisis: Distinguishing Price Trends from Quantity Trends
Bibliographic record
Abstract
Despite an enormous currency depreciation, the growth rate of Indonesia's non-oil exports, measured in dollars, did not accelerate during the first two years of the Asian crisis. In fact, during the second year of the crisis non-oil export value dropped sharply. This paper demonstrates that the main reason for the decline in the dollar value of non-oil exports was a collapse of export prices. Non-oil export dollar prices fell 26% between the second quarter of 1997 and the second quarter of 1999. Measured at constant prices, non-oil exports grew 24% and manufactured exports 31% during this period. Non-oil import prices fell by roughly the same amount as non-oil export prices during the crisis, with little change in the non-oil terms of trade. The decline in the price of traded goods significantly reduced the magnitude of the real exchange rate depreciation experienced by Indonesia.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; both teacher heads agree on what is shown here.
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".