The Sensitivity of Producer Prices to Exchange Rates: Insights from Micro Data
Bibliographic record
Abstract
This paper studies the sensitivity of Canadian producer prices to the Canada-U.S. exchange rate. Using a unique product-level price data set, we estimate and analyze the impact of movements in the exchange rate on both domestic and export producer prices. First, we find that both domestic and export prices are sensitive to movements in the exchange rate. A one percent depreciation in Canadian dollar is associated with a 0.18 (0.25 conditional on price changes in the currency of pricing) percent increase in domestic prices, and a 0.39 (0.60 conditional on price changes in the currency of pricing) percent increase in export prices (once prices are converted into a single currency). Next, we find that there is an important difference in export price sensitivity to the exchange rate depending on the currency of pricing. Those Canadian producers that invoice their exported products in Canadian dollars do not adjust prices to movements in the exchange rate. Meanwhile, those invoicing in U.S. dollars increase their Canadian dollar prices when the Canadian dollar depreciates. Finally, for the same good sold in both the domestic and U.S. markets, the currency of pricing appears to play an important role in determining mark-up adjustment and the degree of pricing to market. These findings shed light on understanding the sources of incomplete exchange rate pass-through into import prices, as well as the indirect effect of the exchange rates on domestic prices through import competition and the use of imported inputs.
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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 | 0.002 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".