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Record W2763351311 · doi:10.1093/restud/rdaa062

Trade and Domestic Production Networks

2020· article· en· W2763351311 on OpenAlexaff
Emmanuël Dhyne, Ayumu Ken Kikkawa, Magne Mogstad, Felix Tintelnot

Bibliographic record

VenueThe Review of Economic Studies · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsRevenueProduction (economics)BusinessEconomicsInternational tradeInternational economicsMonetary economicsFinanceMicroeconomics

Abstract

fetched live from OpenAlex

Abstract We examine how many and what kind of firms ultimately rely on foreign inputs, sell to foreign markets, and are affected by trade shocks. To capture that firms can trade indirectly by buying from or selling to domestic firms that import or export, we use Belgian data with information on both domestic firm-to-firm sales and foreign trade transactions. We find that most firms use a lot of foreign inputs, but only a small number of firms show that dependence through direct imports. While direct exporters are rare, a majority of firms are indirectly exporting. In most firms, however, indirect export is quantitatively modest, and sales at home are the key source of revenue. We show that what matters for the transmission of foreign demand shocks to a firm’s revenue is how much the firm ultimately sells to foreign markets, not whether these sales are from direct or indirect export.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.006
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0160.001

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 head0.121
GPT teacher head0.275
Teacher spread0.153 · 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

Citations188
Published2020
Admission routes1
Has abstractyes

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