Research on Economic Development Stage and Marginal Effects of Trade and FDI on Economic Growth in China
Bibliographic record
Abstract
Since reform and opening up. exports and FDI, as two main internationalization patterns, successfully promote China's economic growth and increase the per capita income. In the mean time, it widens the regional economic gap. Whether exports and FDI are still two engines to promote China’s economic growth in a new stage of development? This paper collects provincial panel data from 1987 to 2010 in China with three economic areas, the east, the middle, and the west, and divides them into two periods, before entry into WTO and after, to study the stage of economic development’s growth effect on trade and FDI empirically. It concludes that the developed eastern area’s exports have the strongest promotion effect on economy, but its promotion effect is weakening now and weaker than the imports’ promotion effect which is still increasing now, in the compared undeveloped mid and west of China. Furthermore, FDI’s growth effects on all the three economic areas are increasing. In a word, foreign trade and FDI’s growth effects change periodically in the different stages of development, so the policy mix of trade and FDI need to be adjusted with economic development.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".