Exchange rate passthrough at the micro and macro levels in a small open economy: Evidence from several million unit values
Bibliographic record
Abstract
Abstract Using a large dataset of import volumes and values for goods imports from around 50 trading partners, and 3,000 goods types, this paper finds that, at the micro level, passthrough is non‐linear in the exchange rate. Passthrough of larger bilateral exchange rate movements (i.e., greater than 8% year‐on‐year change) is just over 0.8, whereas smaller changes have a passthrough of around 0.3. However, regressions using aggregate data indicate that passthrough at the macro level is much closer to 0.8 than to 0.3. The resolution to this apparent puzzle lies in the fact that larger bilateral movements account for the vast majority of variation in the exchange rate index, and hence the non‐linearity at the micro level largely disappears at the macro level. This suggests the care should be taken in inferring macro implications from micro‐based passthrough estimates, and vice versa. Résumé Transmission des variations de taux de change au niveau microéconomique et macroéconomique dans une petite économie ouverte : étude basée sur plusieurs millions de valeurs unitaires. En s’appuyant sur un vaste ensemble de données relatives aux volumes d’importation, à la valeur des importations de biens de 50 partenaires commerciaux et à 3 000 types de produits, cet article montre que la transmission des variations de taux de change est non‐linéaire au niveau microéconomique. Le coefficient de transmission des mouvements de taux de change bilatéraux les plus importants (supérieurs à 8 % d’une année à l’autre) n’est que légèrement supérieur à 0,8 tandis qu’il avoisine 0,3 pour les mouvements plus faibles. Néanmoins, les régressions réalisées à l’aide de macrodonnées montrent que le coefficient de transmission au niveau macroéconomique est plus proche de 0,8 que de 0,3. La solution à cette énigme réside dans le fait que les mouvements bilatéraux les plus importants représentent l’essentiel de la variation de l’indice de taux de change ; ainsi, la non‐linéarité au niveau microéconomique s’estompe considérablement au niveau macroéconomique. Cela suggère qu’il faudrait tirer les conséquences des implications macroéconomiques découlant des estimations microéconomiques du coefficient de transmission, et inversement.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".