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Record W1546204329

A Cross-Country Quarterly Database of Real House Prices: A Methodological Note

2011· preprint· en· W1546204329 on OpenAlexaboutno aff
Adrienne Mack, Enrique Martínez‐García

Bibliographic record

VenueRePEc: Research Papers in Economics · 2011
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsGDP deflatorEconomicsPrice indexPurchasing power parityPer capitaIndex (typography)Purchasing powerReal gross domestic productEconometricsPersonal consumption expenditures price indexConsumption (sociology)PopulationConsumer price index (South Africa)Quarter (Canadian coin)Price levelDatabaseMacroeconomicsPersonal incomeMonetary policyGeographyComputer science
DOInot available

Abstract

fetched live from OpenAlex

We build from publicly-available national sources a database of (nominal and real) house prices— complemented with data on personal disposable income (PDI)—for a selection of countries at a quarterly frequency, starting in the first quarter of 1975. We select a house price index for each country that is consistent with the U.S. FHFA quarterly nationwide house price index for existing single-family houses (formerly called OFHEO house price index), and extend the country series back to 1975 with available historical data/proxies whenever necessary. Each house price index is seasonally-adjusted and then rebased to 2005=100. The house price indexes are expressed in nominal terms, and also in real terms using the personal consumption expenditure (PCE) deflator of the corresponding country with the same base year of 2005=100. PDIs are always quoted in per capita terms using working age population of the corresponding country and similarly expressed in nominal and real terms (the latter with the PCE deflator). We aggregate all countries in the database, weighted by their IMF purchasing power parity-adjusted GDP shares in 2005, to compute an average (nominal and real) house price series and an average (nominal and real) per capita PDI series.

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)0.010
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.451
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.151
GPT teacher head0.367
Teacher spread0.216 · 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 designTheoretical or conceptual
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

Citations51
Published2011
Admission routes1
Has abstractyes

Explore more

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