Entrepreneurial finance and sustainability: Do institutional investors impact the ESG performance of SMEs?
Bibliographic record
Abstract
Institutional investors improve the environmental, social, and governance (ESG) performance of small- and medium-sized enterprises (SMEs). Our difference-in-differences framework shows that the backing from private equity and venture capital funds leads to an increase in SMEs’ externally validated ESG scores compared to their matched non-investor-backed peers. Consistent with “ESG-as-insurance” theory, the ESG performance of SMEs with a higher probability of failure is more likely to benefit from the backing of institutional investors. This positive effect is heterogeneous; while SMEs with high ex-ante ESG performance further improve their ESG performance following institutional investor backing, SMEs with low ex-ante ESG performance are unlikely to implement any improvements. Entrepreneurial finance seems to help sustainable entrepreneurs transform into “sustainability champions,” while neglecting the betterment of non-sustainable SMEs. • We employ a difference-in-differences framework to identify the causal effect of institutional investors on portfolio firms' ESG performance. • Venture capital and private equity funds improve small and medium-sized enterprises' (SMEs)’ ESG performance, consistent with delegated philanthropy theory. • Institutional investors improve ESG performance more in SMEs with a higher risk of failure, consistent with sustainability-as-insurance theory. • The positive effect of institutional investor backing on ESG performance is mainly driven by SMEs with pronounced pre-backing ESG orientation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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 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".