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Record W1890825591 · doi:10.3386/w21413

Exchange Rate Pass-Through, Currency of Invoicing and Market Share

2015· report· en· W1890825591 on OpenAlexaffabout
Michael Devereux, Ben Tomlin, Wei Dong

Bibliographic record

VenueNational Bureau of Economic Research · 2015
Typereport
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsBank of CanadaGovernment of CanadaUniversity of British Columbia
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

This paper investigates the impact of market structure on the joint determination of exchange rate passthrough and currency of invoicing in international trade.A novel feature of the study is the focus on market share of firms on both sides of the market-that is, exporting firms and importing firms.A model of monopolistic competition with heterogeneous firms has the following set of predictions: a) exchange rate pass-through should be non-monotonic and U-shaped in the market share of exporting firms, but monotonically declining in the market share of importers; b) exchange rate pass-through should be lower, the higher is local currency invoicing of imports; and c) producer currency invoicing should be related non-monotonically and U-shaped to exporter market share, and monotonically declining in importing firms' market share.We test these predictions using a new and large micro data set covering the universe of Canadian imports over a six-year period.The data strongly support all three predictions.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.672
GPT teacher head0.495
Teacher spread0.177 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations35
Published2015
Admission routes2
Has abstractyes

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