Hot Issue or Political Issue: A politically induced cycle in Chinese IPO market ¤
Bibliographic record
Abstract
It is evidenced that there is a cycle of hot and cold in Chinese IPO market. However, business cycle and investor sentiment hypotheses provide no explanation to these cyclical fluctuations. With socialist law origin, the Chinese IPO market was strongly influenced by political policies by government intervention. This paper argued that political policy is the primary reason for the cyclical fluctuations in Chinese IPO market. Results of this study indicate that changes of IPO quotas from political hot seasons to cold seasons lead to the cycles of hot issue markets in Chinese Market. It shows that an initial sharp decline in the volume of IPOs over 9 quarters directly after the national congress of The National Congress of Communist Party (CCP hereafter), followed by a relatively flat period in the next 4 quarters and a gradual increase in successive quarters where the volume of IPOs peaks in the quarter of national congress of CCP. The paper also finds that the reason for central government officials manipulate economic policy is to cater to the local government officials, from whom the central government officials gain political support.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".