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Record W1512790424 · doi:10.3386/w16273

Foreign Affiliate Sales and Trade in Both Goods and Services

2010· report· en· W1512790424 on OpenAlexaff
Chunding Li, John Whalley, Yan Chen

Bibliographic record

VenueNational Bureau of Economic Research · 2010
Typereport
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsWestern University
Fundersnot available
KeywordsBusinessCommerceGoods and servicesInternational tradeAdvertisingMarketingEconomicsEconomy

Abstract

fetched live from OpenAlex

Because of the differing forms that international agreements on trade in goods and trade in services take in the GATT (1994) and the GATS there is an incompatibility between measures of world trade in goods and services.Measures of goods trade reflecting GATT (1994) are restricted to trade that crosses borders.Service trade, however, under GATS mode 3 (commercial presence) includes both cross border delivery and foreign affiliate sales within borders.As a result, present comparisons of services and goods trade, as in WTO (2007), are unsatisfactory.One can further argue that our perceptions of the degree of integration in the global economy are likely ill formed, and for comparability the trade component of affiliate sales in goods should be included in goods trade or affiliate sales should be removed from service trade data.Here, we make modifications to reported goods and services trade for specific countries where this is possible by using data on affiliate sales in both goods and services to produce more consistently measured cross country estimates of trade flows.This allows us to compare combined total goods and services trade both over time and across countries, as well as growth rates of trade, trade imbalances and the relative size of trade in goods and services.We use three different statistical bases for measures.One of them is the present mixed GATT and GATS basis; another is trade including foreign affiliate sales, and a final one excludes foreign affiliate sales.Perceptions both on the combined size of country goods and services trade as well as their relative size change a lot using these three measures.We finally draw conclusions and offer policy implications.

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)0.000
metaresearch head score (Gemma)0.003
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 score0.029
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.006
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0290.005

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 head0.371
GPT teacher head0.433
Teacher spread0.062 · 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

Citations3
Published2010
Admission routes1
Has abstractyes

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