The geography of business angel investments in the UK: does local bias (still) matter?
Bibliographic record
Abstract
Business angels (BAs) - high net worth individuals who provide informal risk capital to firms - are seen as important providers of entrepreneurial finance. Theory and conventional wisdom suggest that the need for face-to-face interaction will ensure angels will have a strong predilection for local investments. We empirically test this assumption using a large representative survey of UK BAs. Our results show local bias is less common than previously thought with only one quarter of total investments made locally. However, we also show pronounced regional disparities, with investment activity dominated by BAs in London and Southern England. In these locations there is a stronger propensity for localised investment patterns mediated by the “thick” nature of the informal risk capital market. Together these trends further reinforce and exacerbate the disparities evident in the UK’s financial system. The findings make an important contribution to the literature and public policy debates on the uneven nature of financial markets for sources of entrepreneurial finance.
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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 | 0.008 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.011 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".