Effects of exchange rate volatility on export volume and prices of forest products
Bibliographic record
Abstract
The relative value of currencies varies considerably over time. These fluctuations bring uncertainty to international traders. As a result, the volatility in exchange rate movements may influence the volume and the price of traded commodities. The volatility of exchange rates was measured by the variance of residuals in a GARCH(1,1) model of the exchange rate. We estimated the effect of this exchange rate volatility on export quantity and price with autoregressive distributed lag models based on monthly data of US exports and prices to 14 countries for eight commodity groups. The most general and statistically significant results were obtained by pooling the time series data across destination countries and products. They suggested that an increase in exchange rate variability of 1% led to a short-run decrease in export quantity of 0.3%–0.4% and to a short-run decrease in export price of 0.1%. Both the quantity and the price effect faded away over time. The effects were less systematic and statistically significant for specific export destinations or individual products. Thus, in contrast with exchange rate level, exchange rate volatility may not be a major policy issue for US forest product exports.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".