Evaluating Constructive Lease Capitalization and Off‐Balance‐Sheet Financing: An Instructional Case with FedEx and <scp>UPS</scp>
Bibliographic record
Abstract
Abstract This case illustrates the effects of the proposed new lease standard by the Financial Accounting Standards Board and the International Accounting Standards Board on existing outstanding operating leases. Specifically, the case examines the effects of the proposal that all firms report existing operating leases as capital leases upon the initial adoption of the proposed standard. By applying a constructive capitalization model to two firms who rely on operating leases for financing, FedEx and UPS, we found that both companies would have to record billions of dollars of liabilities that had only appeared in the footnotes of their financial statements under the current lease standards. In addition, the firms would experience a decline in retained earnings and key financial ratios, such as the debt‐to‐equity, return‐on‐assets, and interest coverage ratios, by reporting operating leases as capital leases under the new proposed standard. Furthermore, the magnitude of the lease capitalization impact is much smaller for UPS than for FedEx.
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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 | 0.011 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".