IMPACT OF GOVERNMENT SUPPORT PROGRAMS ON INNOVATION BY CANADIAN MANUFACTURING FIRMS
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Bibliographic record
Abstract
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.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it