CFOs’ Caste-Based Social Ties with Owners and Earnings Management in Family Firms
Bibliographic record
Abstract
Financial misconduct and earnings management persist in the corporate world and despite a large body of work, our understanding is still limited work in the context of family firms (FF). The limited work on antecedents of earnings management in FF focuses on family owners/CEOs with little focus on non-family managers such as the CFOs despite their growing significance. CFO is often the first non-family position appointed by family owners. We argue that there can be heterogeneity in FF’s earnings management based on the degree of cultural compatibility and social proximity of the CFOs with the family owners. Building on social identity theory and social exchange theory, we theorize that ‘CFO caste similarity with family owners’ and the ‘tenure of the CFO in FF’ are associated with lower earnings management, but this relationship weakens in the last year of CFO tenure. We test our hypotheses using a longitudinal (2005-2020), hand-coded panel data set of 229 listed Indian family firms and find support for them. Our findings highlight interesting and previously ignored CFO characteristics such as caste similarity and tenure in the context of family businesses.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".