Comparing the Innovative Performance of Canadian Firms and Those of Selected European Countries: An Econometric Analysis
Bibliographic record
Abstract
This paper follows on Therrien and Mohnen (2001). Here, we compare the innovation performance of manufacturing firms in Canada and four European countries ' Germany, France, Ireland, and Spain - on the basis of an econometric model that identifies some of the determinants of the probability to innovate and of the intensity of innovation. We estimate jointly a probit for the incidence of innovation and a censored ordered probit for the intensity of innovation. The analysis is performed on the data from Statistics Canada''s 1999 Innovation Survey and Eurostat''s second Community Innovation Survey. Due to administrative constraints, data from Europe and Canada cannot be pooled together. From the estimates we compare and disentangle the observed and the expected innovation intensities in Canada and in Europe, using the framework developed by Mairesse and Mohnen (2002). Canada has a higher proportion of innovating firms but a lower share of innovative sales for its innovating firms. From the two effects combined we expect a typical Canadian firm to have a slightly higher share of innovative sales. The effects of firm size, cooperation in innovation, and government support make Canadian firms slightly more innovative than European firms, whereas the sectoral composition of output, the pressure of competition, the scope of innovation activities, and the novelty of innovation confer a slight advantage to Europe.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.819 | 0.873 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".