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Record W2953502045 · doi:10.5430/afr.v8n3p27

REIT-Specific and Macroeconomic Determinants of REIT Returns: Evidence from Singapore

2019· article· en· W2953502045 on OpenAlexaffvenue
Parvinder Arora, Robert N. Killins, Prameela Gangineni

Bibliographic record

VenueAccounting and Finance Research · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsSeneca Polytechnic
Fundersnot available
KeywordsReal estate investment trustEconomicsEquity (law)Monetary economicsDividend yieldReal estateEarningsExchange rateDebtDividendFinancial economicsFinanceDividend policy

Abstract

fetched live from OpenAlex

We examine the determinants of REIT returns in a highly developed trade-oriented market economy - Singapore. For the period from 2004 to 2013, we conduct panel data analyses on the impacts of REIT characteristics and macroeconomic factors on the returns of Singapore Real Estate Investment Trusts (S-REITs). Our results indicate that the returns of S-REITs are affected by the book-to-market value but not earnings per share, the debt-to-equity ratio, or the dividend yield. From the macroeconomic perspective, both local and international economic conditions, including the gross domestic product, inflation rate, exchange rate, and money supply are significantly related to the returns of S-REITs, indicating that the market of S-REITs is an imperfectly integrated one.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.096
Threshold uncertainty score0.859

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.089
GPT teacher head0.302
Teacher spread0.213 · 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.

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

Citations4
Published2019
Admission routes2
Has abstractyes

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