The local bias in equity crowdfunding: Behavioral anomaly or rational preference?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract We use data on individual investment decisions to analyze whether investors in equity crowdfunding direct their investments to local firms and whether specific investor types can explain this behavior. We then examine whether investments exhibiting a local bias are more or less likely to fail. We show that investors exhibit a local bias, even when we control for those with personal ties to the entrepreneur. In particular, we find that angel‐like investors and investors with personal ties to the entrepreneur exhibit a larger local bias than regular crowd investors. Well‐diversified investors are less likely to suffer from this behavioral anomaly than investors with personal ties to the entrepreneur. Overall, we show that investors who direct their investments to local firms more often pick start‐ups that run into insolvency, which indicates that some local investments in equity crowdfunding constitute a behavioral anomaly rather than a rational preference. Moreover, our results reveal that platform design is an important factor determining the scope of the behavior anomaly.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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