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Record W1515573417 · doi:10.34989/swp-2010-19

A Model of Housing Stock for Canada

2021· preprint· en· W1515573417 on OpenAlexaffabout
David Dupuis, Yi Zheng

Bibliographic record

VenueEconstor (Econstor) · 2021
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsBank of Canada
Fundersnot available
KeywordsHumanitiesStock (firearms)Political scienceGeographyArtArchaeology

Abstract

fetched live from OpenAlex

Using an error-correction model (ECM) framework, the authors attempt to quantify the degree of disequilibrium in Canadian housing stock over the period 1961–2008 for the national aggregate and over 1981–2008 for the provinces. They find that, based on quarterly data, the level of housing stock in the long run is associated with population, real per capita disposable income, and real house prices. Population growth (net migration, particularly for the western provinces) is also an important determinant of the short-run dynamics of housing stock, after controlling for serial correlation in the dependent variable. Real mortgage rates, consumer confidence, and a number of other variables identified in the literature are found to play a small role in the short run. The authors’ model suggests that the Canadian housing stock was 2 per cent above its equilibrium level at the end of 2008. There was likely overbuilding, to varying degrees, in Saskatchewan, New Brunswick, British Columbia, Ontario, and Quebec.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.059
Threshold uncertainty score0.152

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0040.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0170.002

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 head0.042
GPT teacher head0.219
Teacher spread0.177 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations2
Published2021
Admission routes2
Has abstractyes

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