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Record W2565162542 · doi:10.1111/caje.12452

Multinationals, intra‐firm trade and employment volatility

2020· preprint· en· W2565162542 on OpenAlexvenueno aff
Kozo Kiyota, Toshiyuki Matsuura, Yoshio Higuchi

Bibliographic record

VenueCanadian Journal of Economics/Revue canadienne d économique · 2020
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
FundersJapan Society for the Promotion of ScienceResearch Institute of Economy, Trade and IndustryMinistry of Economy, Trade and Industry
KeywordsVolatility (finance)Multinational corporationBusinessInternational economicsEconomicsMonetary economics

Abstract

fetched live from OpenAlex

Abstract This paper examines the theoretically ambiguous relationship between the volatility of employment growth and the foreign exposure of firms. We employ unique Japanese firm‐level data during the period of 1994 to 2012. This allows us to investigate any differences in this relationship across multinational firms and trading and non‐trading firms, manufacturing and wholesale trade and intra‐firm and inter‐firm trade. One major finding is that, in manufacturing, employment volatility increases as the share of intra‐firm exports to total sales increases. In contrast, in wholesale trade, employment volatility declines as the share of intra‐firm imports to total imports increases. One possible interpretation of these results is that the transmission of foreign supply and demand shocks could be through not only manufacturing but also wholesale trade firms. Further, a higher share of intra‐firm trade could magnify foreign demand shocks in manufacturing and could mitigate foreign supply shocks in wholesale trade. Résumé Multinationales, commerce intra‐entreprise et volatilité de l’emploi. Cet article analyse le rapport en théorie ambigu entre la volatilité de la croissance de l’emploi et l’exposition des entreprises à l’étranger. Grâce à des données spécifiques recueillies au niveau des entreprises japonaises entre 1994 et 2012, nous pouvons étudier les différences relatives à cette relation pour les entreprises multinationales et les entreprises commerciales et non‐commerciales, le commerce manufacturier et le commerce de gros ainsi que le commerce intra‐entreprise et le commerce inter‐entreprise. L’une des conclusions majeures est que dans le secteur manufacturier, la volatilité de l’emploi diminue à mesure que la part des exportations intra‐entreprise augmente par rapport aux ventes totales. À l’inverse, dans le commerce de gros, la volatilité de l’emploi diminue à mesure que la part des importations intra‐entreprise augmente par rapport aux importations totales. L’une des interprétations possibles de ces résultats est que la transmission des chocs en matière d’offre et de demande étrangère ne passe pas uniquement par les entreprises du secteur manufacturier, mais également par les entreprises du commerce de gros. En outre, une plus grande part de commerce intra‐entreprise pourrait amplifier les chocs en matière de demande étrangère dans le secteur manufacturier, et pourrait atténuer les chocs en matière d’offre étrangère pour le commerce de gros.

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)0.003
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 score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.281
GPT teacher head0.197
Teacher spread0.084 · 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
Published2020
Admission routes1
Has abstractyes

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