Bibliographic record
Abstract
Purpose Until now, traditional western consumption theories have not been able to adequately explain the consumption behavior of Chinese residents in the economic transitional period. Based on annual data from 1986 to 2004, the purpose of this paper is to examine the excess sensitivity of consumption through a variable parameter model. Design/methodology/approach A regression model was used to analyse annual consumption data from 1986 to 2004 in China. Findings The analysis demonstrates excess sensitivity characteristic in Chinese residents' consumption in the economic transitional period. Research limitations/implications The paper concludes that in order to make the demand stimulation policy in China more effective, it is necessary to take a series of measures to correct the excess sensitivity of consumption, so as to establish a healthy cycle of national economy. The paper has only explained excess sensitivity of Chinese residents' consumption from the point of view of economics. While consumption is an economic problem as well as a social problem, those factors beyond economics should not be excluded from the analysis. Originality/value This paper differs from former studies in that previous scholars failed to take into consideration the special economic characteristics in China's transitional economy. The variable parameter model this paper employed takes full consideration of such unique factors as economic expectations and systems changes during the transitional period so as to better explain Chinese people's consumption behavior and provide a new perspective to make government policies stimulate domestic demand more effectively.
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 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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".