Analysis of the Real Estate Industry's Influence on the Economic Growth and Consumption Level in Yunnan Province
Bibliographic record
Abstract
By establishing vector autoregression model,employing Johansen's cointegration test,Granger causality test and impulse response function,this paper analyzes the influence of the real estate industry on the economic growth and the consumption level in Yunnan province.The result shows that,(1)there are two-way causality between the investment in real estate development and GDP,when real estate investment grows by 1%,GDP will grow by 0.53%,and 1 unit of investment in real estate will affect the economic growth,and achieve maximum impact in the third quarter.Later this effect will slowly decay;(2) as the consumption level in Yunnan province has strong inertia,wealth effect of the rising house prices is significant.When house price rises by 1%,consumption will increase by 1.24%,and the maximum impact on consumption level of 1 unit of house price is achieved in the third quarter.Then the impact will immediately attenuate and to zero.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".