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Record W3123159923 · doi:10.22004/ag.econ.274677

Exchange Rates, Cross-Border Travel, and Retailers: Theory and Empirics

2015· preprint· en· W3123159923 on OpenAlexaffabout
Jen Baggs, Loretta Fung, Beverly Lapham

Bibliographic record

VenueAgEcon Search (University of Minnesota, USA) · 2015
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsQueen's UniversityUniversity of Victoria
Fundersnot available
KeywordsCounterfactual thinkingShock (circulatory)Exchange rateLiberian dollarDestinationsDemand shockBusinessMonetary economicsTRIPS architectureEconomicsTourismFinance

Abstract

fetched live from OpenAlex

This paper provides a theoretical and empirical analysis of the effects of nominal exchange rate movements on cross-border travel by consumers and on retail firms' sales. We develop a search-theoretic model of price-setting heterogeneous retailers and traveling consumers who face nominal exchange rate shocks. These exchange rate shocks act as both a supply side shock for retailers though imported input prices and a demand side shock though their effect on the propensity for consumers to cross the border and shop at foreign retail stores. The model provides predictions regarding relationships between rm and regional characteristics and the magnitude of the effects of nominal exchange rate fuctuations and resulting cross-border travel activity on retailers' sales. We use our theoretical framework to motivate an empirical methodology applied to Canadian rm and consumer level data from 1987 to 2007. Our findings indicate that an appreciation of the Canadian dollar substantially increases cross border travel which in turn has a significant negative effect on the sales of Canadian retailers. These effects diminish with the distance of the retailer from the border and with the shopping opportunities available at relevant US destinations. Using counterfactual experiments, we quantify the effects of more restrictive border controls after September 2001 which discouraged cross-border trips and reduced retailer losses from cross-border shopping as well as the effects of increased duty free allowances which raised cross-border trips and reduced retailer sales.

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)0.012
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.003
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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.

Opus teacher head0.116
GPT teacher head0.307
Teacher spread0.191 · 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

Citations0
Published2015
Admission routes2
Has abstractyes

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