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Record W3035323560 · doi:10.1093/rapstu/raaa014

A First Look at the Impact of COVID-19 on Commercial Real Estate Prices: Asset-Level Evidence

2020· article· en· W3035323560 on OpenAlex
David C. Ling, Chongyu Wang, Tingyu Zhou

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Review of Asset Pricing Studies · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsConcordia University
Fundersnot available
KeywordsReal estateCoronavirus disease 2019 (COVID-19)Asset (computer security)EconomicsShock (circulatory)Monetary economicsPercentage pointCapitalization rateReal estate investment trustFinancial economicsEconometricsBusinessFinanceInternal medicineMedicine

Abstract

fetched live from OpenAlex

Abstract This is the first paper to examine how the COVID-19 shock transmitted from the asset markets to capital markets. Using a novel measure of the exposure of commercial real estate (CRE) portfolios to the increase in the number of COVID-19 cases (GeoCOVID), we find a one-standard-deviation increase in GeoCOVID on day t-1 is associated with a 0.24 to 0.93 percentage points decrease in abnormal returns over 1- to 3-day windows. There is substantial variation across property types. Local and state policy interventions helped to moderate the negative return impact of GeoCOVID. However, there is little evidence that reopenings affected the performance of CRE markets.

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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.440
Threshold uncertainty score0.618

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.240
GPT teacher head0.375
Teacher spread0.135 · 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