Determinants of R&D activities of multinational firms abroad
Bibliographic record
Abstract
In recent years, firms have considerably decentralized their research and development (R&D) activities. Subsidiaries of foreign multinational enterprises (MNEs) are now among the top performers of R&D in many EU and non-EU countries. Specifically, MNE affiliates account for around 20% of total business R&D in France, Germany and Italy; between 30% and 50% in Canada, Portugal, the Slovak Republic, Sweden and the United Kingdom; and more than 50% in Austria, Belgium, the Czech Republic, Hungary and Ireland. Against that backdrop, the paper uses a novel and unique data base on R&D expenditure of foreign-owned firms for a set of OECD countries and identifies and analyzes factors that drive the scale of R&D expenditure across countries and sectors. The empirical analysis employs a gravity approach which demonstrates that geography plays a pivotal role as distance between host and home country of a foreign-owned firm, a common language spoken in both home and host countries, or common borders are key drivers of cross-border R&D investments. Moreover, results reveal that additional determinants such as larger host and home country markets or superior host country human capital bases are conducive to R&D expenditure of foreign-owned firms while stronger human capital bases in home countries deter R&D efforts of foreign-owned firms abroad. Keywords: internationalisation of research and development, multinational firms, gravity model JEL-codes: F23, O32, O33
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".