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Record W1590840244

Demographic Changes and Real Housing Prices in Canada

2000· preprint· en· W1590840244 on OpenAlexaboutno aff
Mario Fortin, André Leclerc

Bibliographic record

VenueRePEc: Research Papers in Economics · 2000
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsAsset (computer security)Per capita incomePopulationPopulation growthDemographic economicsReal gross domestic productPer capitaLabour economicsMonetary economicsDemography
DOInot available

Abstract

fetched live from OpenAlex

This paper seeks to determine how demographic and non-demographic factors have contributed to past changes in Canada’s real housing prices as well as their possible impact over the next twenty years. To this goal, we estimate with annual data from 1956 to1997 a structural model of the Canadian housing market. This model possesses two important long-run properties, that is, the longrun supply curve is perfectly elastic while real housing price is cointegrated with real per-capita income. These two conditions imply that housing price shows a tendency to return to a stable longrun growth path dictated by the trend growth rate in real income. Although real income has been the dominant factor behind the fluctuations in the real asset price of housing since 1956, the growth rate of the population between 25 and 54 years of age has also played an important role. In the future, even if aging will continue to be a negative factor on housing demand, the continuation of past trends in real income is likely to be sufficient to counterbalance this negative impact. Consequently, real housing prices should continue to rise over the next twenty years, with possible exceptions in the Atlantic provinces and in Manitoba which will suffer a more substantial population decline.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.295
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
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 head0.035
GPT teacher head0.253
Teacher spread0.217 · 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.

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

Citations11
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueRePEc: Research Papers in EconomicsSame topicHousing Market and EconomicsFrench-language works237,207