CFO Gaps: Determinants and Impact on the Corporate Information Environment
Bibliographic record
Abstract
ABSTRACT A CFO gap arises when the CFO position is left vacant for a period between the departure of the old CFO and the appointment of a new CFO. We find that CFO gaps are fairly common; over the sample period 2004–2016, approximately one-third of CFO turnovers are associated with a CFO gap, lasting, on average, two quarters and two months. CFO gaps are more likely for firms that face more labor market search frictions and with financial reporting and performance issues, and are less likely for firms with succession plans and with greater growth opportunities. While CFO gaps are not associated with significant changes in firms' financial reporting quality, they are associated with significantly negative changes in firms' voluntary disclosure frequency and analysts' forecast quality. Our findings shed light on the factors that influence top executive gaps and the impact of such gaps on firms' information environment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".