The Effects of the Global Financial Crisis on Automobile Demand in China
Bibliographic record
Abstract
This paper examined the factors influencing Chinese auto demand from 2001 to 2013, using multi-regression analysis. This study also investigated the effects of the recent global financial crisis on Chinese automobile demand, and compared the results with those found for three different periods of time. According to the empicral results, the main factors influencing the quantity of Chinese automobile demand before the global financial crisis were the price of automobiles, the price of gasoline, the lending rate and the personal disposable income. The main factors of influencing the Chinese auto demand during the global financial crisis were the price of automobiles, the lending rate and the personal disposable income. Only one main factor influenced Chinese auto demand after the global financial crisis, and this was the personal disposable income. The income elasticity of the demand was 0.270, 0.928 and 0.243 before, during and after the global financial crisis, respectively. The results show that automobiles are a normal good and that the personal disposable income is a very important factor in people’s decisions whether or not to purchase an automobile in China. Moreover, automobiles were almost a luxury good during the global financial crisis, with the influence of personal income rising more three-fold during this period. Furthermore, the effects of the global financial crisis on Chinese automobile demand has been very significant.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".