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Record W2160894440 · doi:10.6000/1929-7092.2014.03.25

A Comparative Analysis on Subsidy Policies of China’s Public Housing Programmes: Evidence Based on Micro Surveys in Baoji

2014· article· en· W2160894440 on OpenAlexvenueno aff
Nannan Yuan

Bibliographic record

VenueJournal of Reviews on Global Economics · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsnot available
FundersNihon University
KeywordsSubsidyChinaConsumption (sociology)Public economicsBusinessPublic policyPolicy analysisEconomicsEconomic growthPublic administrationPolitical science

Abstract

fetched live from OpenAlex

To understand the effects of the public housing programme and measure the feasibility of subsidy policies, this study conducts a comparative analysis on the wealth effects of two of the main subsidy policies which are the selloriented policy 1 (SOP) and rent-oriented policy 2 (ROP), implemented in the city of Baoji, China.The data in this study come from a survey conducted in 2010 in Baoji.We apply a Cobb-Douglas utility function to measure the extra benefits for households that fall under the SOP and households that fall under the ROP.Our results indicate that the low-income SOP households have a stronger taste in terms of housing consumption, and although both policies offer benefits to households, ROP households benefit more than SOP households do.The main policy conclusions drawn from our findings are that the ROP should be adopted first, and restricting resale by the purchasers is the key to achieve policy efficiency.

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)0.004
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 score0.120
Threshold uncertainty score0.238

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.099
GPT teacher head0.306
Teacher spread0.207 · 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
Published2014
Admission routes1
Has abstractyes

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Same venueJournal of Reviews on Global EconomicsSame topicHousing Market and EconomicsFrench-language works237,207