The Dynamic Effects of Entrepreneurship on Regional Economic Growth: Evidence from <scp>C</scp>anada
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Facilitating entrepreneurship to address regional income disparity continues to be a major concern of policy makers across the globe. This study explores the temporal pattern of income disparity for C anadian provinces in two estimation steps. First, an econometric growth regression model is applied to identify the impact of entrepreneurship on regional economic growth. The estimation results suggest that entrepreneurship, measured in terms of the self‐employment rate, plays a pivotal role in determining regional development in C anada. Second, a dynamic vector autoregression model is employed to simulate long‐run regional growth effects that result from policy shocks affecting entrepreneurship. Compared to other growth drivers, entrepreneurship is found to have more pronounced and long‐term stimulative effects on regional development for the period of 1987–2007.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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