The importance of firm level multinationality in the country versus industry debate
Bibliographic record
Abstract
Abstract We conduct the most comprehensive empirical analysis that exists to date of the effect multinationality has on the explanatory power of country and industry factors in international diversification. We investigate the impact the size, scope, and location of a company's international sales has on country versus industry factors, analysing 1,276 firms from Belgium, Canada, France, Germany, Italy, Japan, the Netherlands, Spain, the UK, and the US over the 15‐year period, 1998–2012. We find that the magnitude of the country factor is greater than the magnitude of the industry factor for the period as a whole but that a company's level of international sales has a greater impact on the magnitude of its industry factor than the magnitude of its country factor. Counter‐intuitively, we find stocks with lower sales exposure to their country of origin have a higher country factor, and we show the existence of both a strong local and international industry factor. Our results suggest country‐of‐origin diversification may no longer be sufficient to exploit country‐specific risk and the country factor has become a “country classification” factor.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".