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Record W2899917893 · doi:10.1111/1540-6229.12267

Immigration, Capital Flows and Housing Prices

2018· article· en· W2899917893 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueReal Estate Economics · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsUniversity of British ColumbiaSimon Fraser University
Fundersnot available
KeywordsEconomicsCapital flowsCapital (architecture)ImmigrationMonetary economicsMacroeconomicsNeoclassical economicsGeography

Abstract

fetched live from OpenAlex

Abstract Research on immigration and real estate has found that immigrants lower house prices in immigrant destination neighborhoods. In this article, we find that this latter result is not globally true. Rather, we show that immigrants can raise neighborhood house prices, at least in the case of the wealthy immigrants that we study. We exploit a surprise suspension and subsequent closure of a popular investor immigration program in Canada to use a difference‐in‐differences methodology comparing wealthy immigrant destination census tracts to nondestination tracts. We find that the unexpected suspension of the program had a negative impact on house prices of 1.7–2.6% in the neighborhoods and market segments most favored by the investor immigrants. This leads to an approximate lower bound on the effect of capital inflows of 5%.

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.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.455
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.001

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 head0.016
GPT teacher head0.201
Teacher spread0.186 · 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