Understanding Movements in Aggregate and Product-Level Real-Exchange Rates ∗
Bibliographic record
Abstract
We document new facts on international relative price movements using wholesale price data for common products sold in Canada and United States over the period 2004-2006, and information on the country of production for individual products. We find that international relative prices at the level of individual products are roughly three to four times as volatile as the Canada-US nominal exchange rate at quarterly frequencies. Aggregate real-exchange rates, constructed by averaging movements in international relative prices for individual goods, closely follow the appreciation of the Canadian dollar over this period. These patterns hold both for matched products that are locally produced in each country, as well as for goods that are produced in one country and traded to other countries. The large movements in international relative prices for traded goods are in conflict with the hypothesis of relative purchasing power parity, but instead point to the practice of pricing-to-market by exporters. In light of these findings, we construct a model of international trade and pricingto-market that can account for the observed movements in product- and aggregate real-exchange rates for both traded and non-traded products. The international border plays a key role in accounting for our pricing facts by segmenting competitors across countries.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".