The Economic Consequences of Accounting Standards: Evidence from Risk-Taking in Pension Plans
Bibliographic record
Abstract
ABSTRACT Experts have long conjectured that pension accounting rules, by which pension expense depends on a managerial estimate that is directly tied to the riskiness of plan assets (i.e., the expected rate of return, or ERR, on plan assets), encourage risk-taking with pension investments. The recent passage of IAS 19, Employee Benefits (Revised) (hereafter, IAS 19R) eliminates the ERR and replaces it with a managerial estimate unrelated to plan asset riskiness (the discount rate). We demonstrate that a sample of Canadian firms affected by IAS 19R reduces risk-taking in pension investments post-IAS 19R, compared to a control sample of U.S. firms unaffected by IAS 19R. Therefore, removing firms' ability to recognize immediately in net income the expected higher returns from risk-taking (via a higher ERR) reduces their propensity for that risk-taking—providing some of the first empirical evidence on the economic consequences of eliminating the ERR-based pension accounting model.
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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 | 0.009 | 0.073 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.003 | 0.001 |
| 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".