Big businesses versus institutions for entrepreneurship: new firm creation and growth in China
Bibliographic record
Abstract
Abstract This study on entrepreneurship in China compares the relative importance of institutions with that of a new and less studied variable—big businesses. This study considers two aspects of entrepreneurship: new firm creation and new firm growth. Regression analyses are conducted using province-year panel data from 174 observations. We first find some evidence of positive but diminishing marginal impacts of the aggregate index representing institutional development on new firm creation and growth. Second, we confirm the robust impact of the greater presence of big businesses in a province on the sales of new firms, measured by the sales sum of new firms per population in each province. This result is consistent with the linkage effect, whereby big businesses build their supply chains and promote new firms to be their suppliers. We find no evidence of a net barrier-to-entry effect of big businesses on new firm creation, suggesting that positive spillover effects tend to offset negative barrier-to-entry effects on new firm creation. In terms of policy implications, the results suggest that for an economy at the middle-income stage, promoting big businesses is justified as it has no negative effects on new firm creation, while it positively affects new firm growth.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".