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Record W1985401237 · doi:10.1111/1467-9396.00258

International Cross‐Ownership and Strategic Trade Policies

2001· article· en· W1985401237 on OpenAlexaff
Ngo Van Long, Antoine Soubeyran

Bibliographic record

VenueReview of International Economics · 2001
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsMcGill University
Fundersnot available
KeywordsSubsidyEconomicsMicroeconomicsWelfareNash equilibriumNeutralityValue (mathematics)Distribution (mathematics)Market economy

Abstract

fetched live from OpenAlex

The paper analyzes a model of strategic trade policies in the presence of international cross‐ownership of firms that are heterogenous both in terms of costs and in terms of extent of foreign ownership. The equilibrium pattern of taxes and subsidies is characterized for any arbitrary cross‐ownership profile, and any number of heterogenous firms. The equilibrium subsidy (or tax) given to any firm is shown to depend, in a separable manner, on the firm’s characteristics and on the covariance of the distribution of cost and foreign ownership across firms. A neutrality theorem is proved concerning the Nash equilibrium of the game between governments: in equilibrium, the pattern of trade, the value of each firm, and world welfare are independent of the ownership pattern.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0030.004
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.104
GPT teacher head0.284
Teacher spread0.180 · 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

Citations14
Published2001
Admission routes1
Has abstractyes

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