Coming full circle on cash holdings and firm value: A comment on Kim and Bettis (2014), Theissen et al. (2023), and Souder et al. (2024)
Bibliographic record
Abstract
In their recent article, Theissen et al. (2023) re-examined the seminal study of Kim and Bettis (2014) on the positive relationship between firms’ cash holdings and firm value. Theissen et al. (2023) improved on the original Tobin's q measure used to capture firm value and found that—in contrast to the results of Kim and Bettis (2014) –there are not decreasing but increasing returns to holding cash. Separately, Souder et al. (2024) made various methodological improvements and developed a new measure of forward-looking firm value, ultimately finding no relationship between cash holding and value at all. In this article, we combine all methodological refinements made after the original study of Kim and Bettis (2014) into a single analysis. We find that Kim and Bettis’ (2014) original results are correct, despite the numerous limitations of their method.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.064 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.008 | 0.018 |
| Open science | 0.013 | 0.005 |
| Research integrity | 0.041 | 0.055 |
| Insufficient payload (model declined to judge) | 0.007 | 0.008 |
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 source (direct Gemma or distilled Codex), 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".