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Record W1597683655

IMPACT OF GOVERNMENT SUPPORT PROGRAMS ON INNOVATION BY CANADIAN MANUFACTURING FIRMS

2003· preprint· en· W1597683655 on OpenAlex
Petr Hanel

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueÉrudit documents and data repository (Érudit Consortium, University of Montreal) · 2003
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicInnovation Policy and R&D
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsOriginalityGovernment (linguistics)SubsidyBusinessContingencyPublic supportPrincipal (computer security)Public sectorIndustrial organizationMarketingPublic economicsEconomicsPolitical scienceMarket economyEconomy
DOInot available

Abstract

fetched live from OpenAlex

The report presents results of the Statistics Canada Innovation Survey, 1999 regarding the use of government programs supporting R&D and innovation by Canadian manufacturing firms and the relationship between the support received and the R&D and innovation performance. The percentage of firms using the two principal instruments supporting R&D activities (R&D tax credits and R&D subsidies) and the other four more general programs, is increasing from the low to high technology sectors and from small to large firms. With minor exceptions, the same is also true for the collaboration with federal and provincial laboratories and universities. Significant regional differences in the use of government programs persist even when the sector, the size of firm and their R&D activities are controlled for. Firms conducting R&D activities are more likely to use most of the government programs. These firms are also more likely to innovate. There is a positive association between the use of public support and the originality of the most profitable innovation. However, some of the positive association between the use of public support and the originality of innovatio n and its commercial impact observed in contingency tables disappears in regression analysis. The probability of introduction of a more rather than less original innovation is analyzed under two alternative set of assumptions. 1. First it is assumed that receiving public support and introducing innovation of certain originality are two independent exogenous decisions. Under this assumption the probability of introducing a more rather than a less original innovation is estimated by single equation logit regression models. The probability of introducing a more original innovation is increased when the innovating firm uses tax credits and technology assistance & support program. Firms that received R&D subsidies are more likely to have a larger share of product innovations in firm's total 1999 sales than other firms are. The use of other government programs is not correlated in any systematic way with the probability of an innovation, let alone a more original one. 2. When it is assumed that the use (and/or selection) and the effect of government policies on innovation performance may be interdependent, results of a series of simultaneous two-stage logit models are less robust and less reassuring than single equation estimates. The positive effect of the use of tax credits on the originality of innovation appears less statistically significant in the simultaneous dummy variable ordered logit model but remains as strong as before in the simultaneous logit model predicting the probability of a world-first innovation versus a Canada -first one. However, none of the policy variables appears as a statistically significant determinant of the probability of introducing a “Canada-first” versus a “firm-first” or a “firm-first” versus “not involved in innovation” estimated in the other two simultaneous models. Collaboration with federal R&D laboratories appears to increase the probability of introducing the most original world innovation. Firms collaborating with colleges and universities are more likely to contribute to transfer of technology to Canada through a Canada-first innovation. The results of the simultaneous equation approach are at this stage experimental and should be interpreted as such. The presented results are in agreement with the most recent studies evaluating the effect of government support to R&D and innovation abroad. They show that obtaining (or using) government support and the effect of the support on R&D or innovation should be treated as interdependent relations.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.311
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.026
GPT teacher head0.232
Teacher spread0.206 · 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