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Record W6909004942 · doi:10.34989/swp-2012-20

The Sensitivity of Producer Prices to Exchange Rates: Insights from Micro Data

2021· article· en· W6909004942 on OpenAlexaffabout

Bibliographic record

VenueEconstor (Econstor) · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsBank of Canada
Fundersnot available
KeywordsExchange rateDepreciation (economics)Liberian dollarCurrencyExchange-rate pass-throughInvoiceRelative priceCompetition (biology)Foreign exchange riskUs dollar

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.436
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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.

Opus teacher head0.076
GPT teacher head0.250
Teacher spread0.173 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2021
Admission routes2
Has abstractyes

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