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Record W2613997517

Policy Forum: Patent Box Regimes--A Vehicle for Innovation and Sustainable Economic Growth

2017· preprint· en· W2613997517 on OpenAlexaboutno aff
Joanne Hausch, Albert De Luca

Bibliographic record

VenueRePEc: Research Papers in Economics · 2017
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicInnovation Policy and R&D
Canadian institutionsnot available
Fundersnot available
KeywordsBase erosion and profit shiftingIncentiveProsperityBusinessSustainable growth rateInvestment (military)Profit (economics)Industrial organizationSustainable developmentAction planEconomicsEconomic growthFinanceMarket economyPolitical scienceManagementDouble taxation
DOInot available

Abstract

fetched live from OpenAlex

Innovation is widely recognized as the key to sustainable economic growth. Because people and projects are mobile in this global marketplace, companies have many investment options, and countries must compete for business investment. Research and development incentives are therefore very important, and patent box regimes are becoming more and more popular. However, there are also international concerns about harmful tax practices and base erosion and profit shifting (BEPS). Patent box regimes are addressed by the Organisation for Economic Co-operation and Development in action 5 of its BEPS action plan. In this article, the authors review the concept of the patent box and consider the effectiveness of this type of incentive in driving innovation and prosperity. A review of patent box regimes around the world is provided, with summaries of new regimes enacted or proposed in a number of key jurisdictions. Finally, Canadian developments in this area--existing and potential--are considered.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.387
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.070
GPT teacher head0.325
Teacher spread0.255 · 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.

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

Citations1
Published2017
Admission routes1
Has abstractyes

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