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Record W2052771075 · doi:10.1080/08865655.2007.9695667

Exported retail sales along the Texas‐Mexico border

2007· article· en· W2052771075 on OpenAlexvenueno aff
Roberto Coronado, Keith R. Phillips

Bibliographic record

VenueJournal of Borderlands Studies · 2007
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsLiberian dollarRetail salesRetail tradeCashBusinessConsumption (sociology)International tradeFree trade agreementCommerceEconomicsFree tradeMarketingFinance

Abstract

fetched live from OpenAlex

Abstract Trade between the U.S. and Mexico has boomed over the past 10 years due partly to the significant reduction in tariffs from the North American Free Trade Agreement (NAFTA) and the strong growth in the maquiladora industry. While commercial trade between the countries is well documented, less is known about the size of the cross‐border retail trade that occurs. Though the size of this activity is small in comparison to commercial trade, it is a significant part of the economies of many border cities. In 2005 alone, there were more than 45 million non‐commercial crossings at the bridges along the Texas‐Mexico border. Many of these individuals were coming to purchase goods to take back to their home country. Since most of the retail trade conducted on the U.S. side of the border is done in cash, it is difficult to document the share of retail spending accounted for by Mexican nationals. In this article we use several techniques based on a simple consumption function to estimate the size of retail spending that is essentially exported to Mexico via cross‐border shoppers. We then check our estimates of the proportion of retail sales going to Mexican nationals in the Texas border metros to see if they are consistent with the impacts to retail sales of movements in the real peso‐dollar exchange rate.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.462
Threshold uncertainty score0.549

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.081
GPT teacher head0.279
Teacher spread0.199 · 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 teacher head, 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

Citations22
Published2007
Admission routes1
Has abstractyes

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