Investor Protection, Income Smoothing, and Earnings Informativeness
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
This study investigates whether investor protection affects the efficient communication of private information about future prospects through income smoothing. While prior research suggests that the level of earnings management differs between high and low investor protection countries, we examine whether the underlying motive for earnings management differs between high and low investor protection countries. Using firm-level data from 44 countries for 1993 to 2002 and Tucker and Zarowin's (2006) method to measure earnings informativeness, we find that earnings informativeness is more positively associated with income smoothing in countries with strong investor protection than it is in countries with weak investor protection. Our findings suggest that managers in weak investor protection countries are more likely to use income smoothing for opportunistic reasons while managers in strong investor protection countries are more likely to use income smoothing to convey their private information about future earnings. The results are robust through various additional analyses. More broadly, our results suggest that the role of accounting discretion is affected by a country's institutional infrastructure, specifically, its ability to provide protection for outside shareholders.
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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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.005 |
| Open science | 0.001 | 0.001 |
| 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 it