The Economic Impact of Entrepreneurship: Comparing International Datasets
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Bibliographic record
Abstract
Abstract Manuscript Type Empirical Research Question/Issue What is the impact of entrepreneurship on GDP /capita, unemployment, exports/ GDP , and patents per population across countries? Is the impact of entrepreneurship mitigated by legal and cultural differences across countries? Do different international datasets provide different answers to these questions? We empirically compare the impact of entrepreneurship on GDP /capita, unemployment, exports/ GDP , and patents per population across countries by examining three datasets from the W orld B ank, the OECD , and C ompendia. Research Findings/Insights Based on a comprehensive sample of all available countries and years, with the W orld B ank data being the most comprehensive, we find entrepreneurship has a significantly positive impact on GDP /capita, exports/ GDP , and patents per population, and a negative impact on unemployment. Inferences from the C ompendia data are very consistent. By contrast, inferences from the OECD data are not supportive of any of these propositions. Theoretical/Academic Implications Our findings point to institutional and cultural impediments to the effectiveness of entrepreneurship. Most notably, the impact of entrepreneurship is significantly mitigated by excessively strong creditor rights that limit entrepreneurial risk‐taking. Furthermore, the data indicate that cultural attitudes associated with low risk‐taking limit the effectiveness of entrepreneurship. By contrast, the impact of entrepreneurship on exports/ GDP does not appear to be directly tied to costs of exporting, which is perhaps best explained by the new economy goods and services created by entrepreneurs that depend less on such costs. For some subsets of the data we find evidence consistent with the view that top tier venture capital funds enhance the impact of entrepreneurship on GDP /capita. Finally, our results show how different definitions of new business entry matter for empirical analysis of entrepreneurship across countries. Practitioner/Policy Implications The data highlight the importance of access to finance without downside costs so that entrepreneurs are encouraged to take risk. Further, the data highlight institutional differences in risk attitudes that more generally inhibit risk‐taking and thereby limit the effectiveness of entrepreneurship. Moreover, the data highlight a central role for careful measurement of entrepreneurial activities and for inclusion of as many countries and years as possible in order to effectively analyze the impact of entrepreneurship.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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