Maintaining maintenance: The real effects of financial reporting for infrastructure
Bibliographic record
Abstract
Abstract We use the adoption of General Accounting Standards Board Statement No. 34 (GASB 34) to examine whether disclosing information in states' financial reports influences their investment decisions. GASB 34 requires governments to report on general infrastructure assets and permits either the standard depreciation approach or the modified approach. The modified approach requires additional disclosures, a step which we argue promotes greater transparency about a government's infrastructure and can potentially facilitate infrastructure investment decisions. We find a robust positive association between the modified approach and investment in infrastructure maintenance. Additional evidence demonstrates a more pronounced effect when external monitoring is likely higher and government officials are likely better informed as a result of the increased disclosure. We further find that states using the modified approach are less likely to cut or divert funds intended for infrastructure maintenance. Our study suggests that disclosing information in governments' financial reports can have real effects, such as mitigating underinvestment in infrastructure maintenance, which governments often defer to future periods in violation of the interperiod equity principle and to the detriment of society.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.106 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".