MétaCan
Menu
Back to cohort
Record W3122603346

REIT Institutional Ownership Dynamics and the Financial Crisis

2013· article· en· W3122603346 on OpenAlexaff
Erik Devos, Seow Eng Ong, Andrew C. Spieler, Desmond Tsang

Bibliographic record

VenueSSRN Electronic Journal · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBanking stability, regulation, efficiency
Canadian institutionsMcGill University
Fundersnot available
KeywordsReal estate investment trustInstitutional investorBusinessFinancial crisisFinancial systemInvestment (military)FinanceReal estateEconomicsCorporate governance
DOInot available

Abstract

fetched live from OpenAlex

Collectively, institutional investors hold large ownership stakes in REITs. The traditional view is that institutions are both long-term and passive investors. The financial crisis beginning in 2007 provides an opportunity to analyze the investment choices of institutional investors before, during, and after the crisis. Our results indicate that institutional ownership increased prior to the financial crisis, decline significantly during the period of market stress, but rebounded after. These results hold for four institutional investor subtypes: mutual funds/investment advisors, bank trusts, insurance companies, and other institutions, with mutual funds/investment advisors and bank trusts most clearly exhibiting this pattern. We also find evidence that institutions actively manage their REIT portfolios, displaying a light to quality after he market downturn by reducing beta and individual risk exposure, and by increasing ownership in larger REITs.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.009
GPT teacher head0.197
Teacher spread0.188 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueSSRN Electronic JournalSame topicBanking stability, regulation, efficiencyFrench-language works237,207