Understanding the Time Variation in Exchange Rate Pass-Through to Import Prices
Bibliographic record
Abstract
In this paper, we analyze the presence of time variation in the pass-through from the nominal effective exchange rate to import prices for 24 advanced economies over the period 1995–2015. In line with earlier studies in the literature, we find substantial heterogeneity in the level of exchange rate pass-through across countries. But, in addition, we show that the dynamics of exchange rate pass-through also differ across countries. Potential explanations for this observation could be of a country-specific nature or could relate to differences in the composition or transmission of global shocks across countries. We then investigate the role of global demand shocks as potential determinants of exchange rate pass-through dynamics in seven advanced economies. We conduct this analysis by running a set of instrumental variable regressions to quantify the contemporaneous exchange rate pass-through that arises from different shocks. Out of the global demand shocks that we examine, we find that oil demand shocks, in particular, are associated with a relatively higher exchange rate pass-through to import prices, while US fiscal policy shocks appear to have the lowest impact.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| 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".