Dividend policy in India: new survey evidence
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose – The purpose of this paper is to survey managers of dividend-paying firms listed on the National Stock Exchange (NSE) in India to learn their views about the factors influencing dividend policy, dividend issues, and explanations for paying cash dividends and repurchasing shares. The authors compare the results to other dividend surveys based on firms in Indonesia, Canada, and the USA. Design/methodology/approach – The authors use questionnaire to gather primary data from a sample of 500 firms listed on the NSE. Findings – The most important determinants of dividends involve earnings (the stability of earnings as well as the level of current and expected future earnings) and the pattern of past dividends. Comparing the overall rankings of the 21 factors by respondents from Indian firms to those of Indonesian, Canadian, and US firms reveals statistically significant correlations. Respondents also perceive that dividend policy affects firm value. Respondents also view maintaining an uninterrupted record of dividends as important. The most highly supported explanations for paying cash dividends concern signaling, the firm life cycle, and catering. Although none of the theories of repurchasing shares is dominant, respondents provide little support for the agency explanation. Research limitations/implications – Although the tests suggest that the sample does not suffer from non-response bias, the findings should be viewed as suggestive rather than definitive because of the relatively low response rate. Originality/value – The paper presents new evidence about dividend policy of Indian firms. To the knowledge, this is the most comprehensive survey of Indian firms to date that captures managerial perceptions on both cash dividends and share repurchases.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it