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Record W4402423448 · doi:10.24908/iqurcp18041

Capping Study Permits: Evaluating the Impact of International Students on Real Rent Growth in Canada

2024· article· en· W4402423448 on OpenAlexaffvenueabout
Hayden Royds

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Learning Practices
Canadian institutionsQueen's University
Fundersnot available
KeywordsEconomics

Abstract

fetched live from OpenAlex

Housing affordability has become a critical policy issue in Canada as shelter costs have dramatically increased. This study examines the impact of international students on the growth of real rents in Canadian census metropolitan areas (CMAs) from 2004 to 2018. Using study permit data as a proxy for international student numbers, we establish a causal link between the influx of international students and real rent growth. To address endogeneity and control for CMA-specific factors, we employ an Ordinary Least Squares (OLS) model and a shift-share instrument. Our OLS estimates suggest that international student growth accounts for 1.15 percent of real rent growth. Further, using a two-stage least-squares (2SLS) model for robustness, we find that a 1 percent increase in per capita study permit growth (“dppr”) leads to a 1.31 percent increase in real rent growth (“grr”). These findings are significant for policy discussions on housing affordability and the potential impact of the 2024 study permit cap.

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)0.006
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 score0.034
Threshold uncertainty score0.247

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.216
GPT teacher head0.548
Teacher spread0.332 · 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

Citations0
Published2024
Admission routes3
Has abstractyes

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