Investment–cash flow sensitivity and investor protection
Bibliographic record
Abstract
Abstract We examine the role of country‐level legal investor protection (i.e., shareholder and creditor protection) on firm investment–cash flow sensitivity (ICFS). Using underexplored research data on investor protection across 21 countries and working with a conservative empirical design, we extend prior literature on the relation between investor protection and ICFS and provide new evidence on how these country‐level attributes interact to explain a firm's ICFS. We find that either the strong legal protection of minority shareholders or the strong legal protection of creditors reduces the sensitivity of investment to internal cash flow. However, in countries with strong levels of both minority shareholder and creditor protection, ICFS increases. Our results remain robust after controlling for several alternative explanations. The results support the argument that overregulation arises when policymakers increase investor protection at levels that lead firms to avoid external sources of finance, hampering firm investment. Our findings suggest that countries face a regulatory trade‐off such that increasing investor protection (either shareholder or creditors protection) enhances financial markets efficiency, but excessive regulation can indeed lead to financial markets inefficiencies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| 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".