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Record W4248558957 · doi:10.53383/100181

International Real Estate Review

2014· article· en· W4248558957 on OpenAlexaboutno aff
Marsha Courchane, Cynthia Holmes

Bibliographic record

VenueInternational Real Estate Review · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsReal estateHouse priceInflation (cosmology)EconomicsQuarter (Canadian coin)CrashFinancial crisisPopulationFinancial marketMonetary economicsFinancial economicsFinanceMacroeconomicsGeographyDemography

Abstract

fetched live from OpenAlex

Canadian and U.S. real estate markets have compared similarly along dimensions such as inflation, mortgage interest rates, population and income growth and other measures. With respect to house prices, however, the series have moved in similar ways at some times, but then significantly diverged by the second quarter of 2007. For example, Canadian and U.S. house price indices reached essentially identical levels in 1987Q2, 1995Q1 and 2007Q2. As a consequence of the U.S. financial crisis and precipitous decline in house prices, the U.S. and Canadian indices have sharply diverged. Our paper examines whether or not the house price indices were driven by fundamentals during these time periods, or whether they diverged from fundamentals. We find that the U.S. house prices closely aligned with fundamentals until the mortgage markets crashed in 2008. We find that Canadian house prices continue to align with fundamentals. However, there have been some significant market changes between the two countries and key housing market measures indicate that Canadian markets are now moving along some paths similar to those taken by the U.S. prior to the crash.

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)0.002
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.993
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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)0.0020.003

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 head0.032
GPT teacher head0.276
Teacher spread0.244 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations0
Published2014
Admission routes1
Has abstractyes

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