Country-level determinants and consequences of overconfidence in the ambitious entrepreneurship segment
Bibliographic record
Abstract
Countries vary widely and systematically in the extent to which the ambitions of their entrepreneurs differ from their realisations. We label this discrepancy entrepreneurial overconfidence (EOC). Although a certain level of EOC may be beneficial for an economy, we provide empirical support for the argument that if entrepreneurial ambitions substantially and systematically exceed realisations, this may be at the cost of economic and societal prosperity. Therefore, we need to know more about country levels of EOC and their determinants, particularly with respect to the growth-oriented segment of entrepreneurship. Combining data on entrepreneurial ambitions from Global Entrepreneurship Monitor and data on realisations from Eurostat, we construct a measure of EOC at the country level and correlate its variation across 23 European Union (EU) countries over the period 2004–2015 with a set of economic and cultural factors. Among other findings, our results show that ambitions exceed realisations in almost all countries, but that this discrepancy is significantly greater for new member countries entering the EU since 2004. Policy implications of our results are discussed, particularly for promoting ambitious entrepreneurship in countries at the intermediate development stage.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".