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Record W3197934142 · doi:10.3390/jrfm14090412

Testing Housing Markets for Episodes of Exuberance: Evidence from Different Polish Cities

2021· article· en· W3197934142 on OpenAlexvenueno aff
Janusz Sobieraj, Dominik Metelski

Bibliographic record

VenueJournal of risk and financial management · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Unit rootEconomicsUnit (ring theory)Explosive materialUnit root testMonetary economicsDemographic economicsEconometricsCointegrationGeography

Abstract

fetched live from OpenAlex

In the study we use the right-tail unit root test to analyse the presence of mild explosive dynamics (exuberance) in housing prices of the 17 largest Polish cities in the period 2006–2021 (for quarterly data). In terms of real prices from the secondary market, we were able to demonstrate the existence of episodes of mild explosive dynamics for 13 of the 17 cities studied. When we changed the context of the study and performed the same tests for the price-to-income ratio, we found that episodes of price exuberance could be indicated only in the case of two cities. The overall conclusion is that rising average incomes tend to mitigate the explosive dynamics and change the context in which the whole issue of housing bubbles is viewed. The answer to the question of whether there is indeed already a situation of price bubbles in local housing markets in Poland is of course crucial for those interested in buying or selling a housing unit (i.e., the participants of this market), but it must also remain important for the monetary authorities implementing monetary and macroprudential policies in Poland.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.317
Threshold uncertainty score0.583

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0000.000
Research integrity0.0000.000
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 head0.034
GPT teacher head0.219
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, 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

Citations24
Published2021
Admission routes1
Has abstractyes

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