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Record W4411907371 · doi:10.1017/s0022109024000735

Cross-Border Property Rights and the Globalization of Innovation

2025· article· en· W4411907371 on OpenAlexaff
Bo Bian, Jean‐Marie Meier, Ting Xu

Bibliographic record

VenueJournal of Financial and Quantitative Analysis · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Property and Patents
Canadian institutionsUniversity of TorontoUniversity of British Columbia
FundersDeutsche Forschungsgemeinschaft
KeywordsGlobalizationProperty (philosophy)Property rightsBusinessEconomic geographyInternational tradeEconomic systemEconomicsMarket economyMicroeconomics

Abstract

fetched live from OpenAlex

Abstract We identify strong cross-border property rights as a driver for the globalization of innovation. Using 67 million patents from over 100 patent offices, we construct novel measures of the three stages of innovation diffusion: adoption, sourcing, and collaboration. Exploiting staggered bilateral investment treaties (BITs) as shocks to cross-border property rights, we show that signatory countries increase technology adoption and sourcing from each other; they also increase R&D collaborations. The results are particularly strong for countries with weak domestic institutions and technologies with high imitation risks. Increases in R&D-related foreign investments explain most of the results.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.723
Threshold uncertainty score0.142

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.048
GPT teacher head0.320
Teacher spread0.273 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations3
Published2025
Admission routes1
Has abstractyes

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