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Record W7126506005

Higher Interest Rates Hinder Hotel Price Momentum

2023· article· W7126506005 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueeCommons (Cornell University) · 2023
Typearticle
Language
FieldBusiness, Management and Accounting
TopicFranchising Strategies and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)FellDatabase transactionMomentum (technical analysis)Interest ratePrice index
DOInot available

Abstract

fetched live from OpenAlex

The price performance of hotels by region was mixed in the third quarter of 2023. The Midwest, Mid-Atlantic, Mountain, and West South Central posted positive quarterly and year-over-year results. In contrast, New England and the South Atlantic regions struggled, and the Pacific region recorded only slight year-over-year gains. Hotels in non-gateway cities continued to outperform those in gateway cities. Transaction volume fell year-over- year and quarter-over-quarter. However, volume is up this quarter for large hotels and hotels in gateway cities. Based on moving averages, a “hold” signal is indicated for large hotels, with a “buy” signal for small properties. That said, the situation calls for keeping your gunpowder dry, given that the standardized prices of both large and small hotels have softened. Hotel interest rates for both Class A and Class B and C hotels rose about 3.6 percent this quarter and approximately 4 percent year over year, even as credit spreads tightened and the delinquency rate on hotel loans fell this quarter. Looking at commercial property categories, the delinquency rate on hotels is now lower than both retail and office properties. As in the prior period, the borrowing costs still exceed the return on hotels. Expect to see an uptick in the price of large hotels in the next quarter, while prices for small hotels falter, based on our leading indicators of hotel price performance. This is volume 12, number 3 of the hotel indices series.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.213
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0010.000
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.009

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.

Opus teacher head0.058
GPT teacher head0.209
Teacher spread0.151 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it