The trade led-growth hypothesis in China and G8 countries: pooled mean group estimation
Bibliographic record
Abstract
This research aims to examine the trade-led growth (TLG) hypothesis, especially the relationship between trade openness (TRA) and economic growth (GDP) in China and G8 (UK, Russia, Canada, USA, France, Italy, Germany, Japan) economies with two threshold variables, labour force (LF) and gross fixed capital formation (GFC). The study explores cointegration among these variables and evaluates their short and long-term effects utilising data from 1992 to 2021. Different tests, including CADF unit root, Westerlund panel cointegration, and pooled mean group estimation (PMG), are used while considering cross-section dependence (CD) and D-H tests. The PMG estimator identifies a positive long-term impact of GFC on GDP in both China and the G8 economies. Conversely, the D-H test exposes no causal relationship between GDP, labour force and gross fixed capital, and trade and gross fixed capital. These findings recommend that policymakers should prioritise trade development by spending on capital formation and labour production to improve economic growth. Furthermore, adopting amplified trade cooperation between China and G8 economies is suggested.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".