Evaluating the Impact of R&D Tax Credits on Innovation: A Microeconometric Study on Canadian Firms
Why this work is in the frame
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Bibliographic record
Abstract
This study examines the effect of R&D tax credits on innovation activities of Canadian manufacturing firms. Over the 1997-1999 period the Federal and Provincial R&D tax credit programs were used by more than one third of all manufacturing firms and by close to two thirds of firms in high-technology sectors. We investigate the average effect of R&D tax credits on a series of innovation indicators such as number of new products, sales with new products, originality of innovation etc. using a non-parametric matching approach. Compared to a hypothetical situation in the absence of R&D tax credits, recipients of tax credits show significantly better scores on most but not all performance indicators. We therefore conclude that tax credits increase the R&D engagement at the firm level and that the R&D activities induced by fiscal incentives lead to additional innovation output.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it