Second Quarter 2015: Hotel Deals Are Getting Harder to Pencil Out
Bibliographic record
Abstract
Hotel Investment based on operating performance has turned red. Our Economic Value Added (EVA) indicator shown in Exhibit 1 has turned negative, declining from -.6% (near zero; breakeven) to -1.8% in 2014Q1. What is more alarming is that the hotel cap rate (5.7%) is approximately equal to the cost of debt financing (5.6%) for hotels financed by large life insurance companies, as shown in Exhibit 2. Intuitively, the cap rate represents the return on hotel properties assuming all-equity financing. The use of debt financing is used to magnify the return to hotel properties. For positive leverage (return magnification) to occur, the cap rate should exceed the cost of debt financing, meaning that your return should be greater than your borrowing cost. We will show that the current situation arises because of cap rate compression (a decline in the cap rate) due to a rise in hotel prices. In summary, what these two exhibits suggest is that financial feasibility is becoming more tenuous and investors are having a harder time getting a potential hotel investment to ?pencil out.?
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.038 | 0.008 |
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".