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Record W3124769772

Commercial Property Rent Dynamics in U.S. Metropolitan Areas: An Examination of Office, Industrial, Flex and Retail Space

2013· article· en· W3124769772 on OpenAlexaboutno aff
Maria R. Ibanez, Anthony Pennington‐Cross

Bibliographic record

Venuee-Publications@Marquette (Marquette University) · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsRentingMetropolitan areaQuarter (Canadian coin)BusinessFLEXSpace (punctuation)Industrial organizationQuality (philosophy)DebtEconomicsFinanceEngineeringComputer scienceTelecommunicationsGeography
DOInot available

Abstract

fetched live from OpenAlex

This paper is concerned with the market rental rate for space offered by commercial property and how that rental rate evolves over time. Rental rates reflect the value of the services provided by the property and can have a significant impact on the ability of its owners to make monthly debt obligations. We investigate commercial property rent dynamics for 34 large metropolitan areas in the U.S. The dynamics are studied from the second quarter of 1990 through the second quarter of 2009 and the results are compared across four property types or uses (office, industrial, flex, and retail). There is substantial heterogeneity in both the long and short run responses to changing demand and supply conditions. In general, the office market is the slowest to adjust back towards equilibrium while industrial and flex markets adjust back to the long run equilibrium very quickly. For industrial and office types, the speed of adjustment is substantially faster within quality segments and is strongest for grade A properties.

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.

How this classification was reachedexpand

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.559
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.041
GPT teacher head0.197
Teacher spread0.156 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2013
Admission routes1
Has abstractyes

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