Differences in government accounting conservatism across jurisdictions, their determinants, and consequences: the case of Canada and the United States
Bibliographic record
Abstract
Abstract We use the year-end adjustments to the provisions for student loan losses of state and provincial governments in the United States and Canada to study government accounting conservatism and how it varies between these adjacent and highly integrated countries. Building on Canada’s more conservative cultural attributes, we hypothesize and find that Canadian provincial governments report more conservative provisions for student loan losses than U.S. state governments. Moreover, the year-end adjustments to the provisions in Canada are excessively conservative; they are larger than the audit materiality threshold. We further find that the political ideology of the government, government reporting incentives, government debt, and political competition are important determinants of government accounting conservatism. Finally, we find a negative association between the year-end adjustment to the provision and future student lending. This result suggests that government accounting conservatism leads to credit rationing and significant societal consequences for students. Overall, our study highlights important aspects of the determinants and consequences of government accounting conservatism. To the best of our knowledge, this study is the first to examine government unconditional accounting conservatism.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".