The Determinations of East Asia’s Automobile Trade Using a Gravity Model
Bibliographic record
Abstract
The aim of this study is to investigate empirically the factors that determine the level of automobile trade in East Asian countries by taking into account government policies as well as the role of MNEs. To do so, in this study we include dummies of import substitution industrialisation (ISI) and export orientation industrialisation (EOI) policies as well as Japanese FDI as additional explanatory variables in our augmented gravity models. We found that GDPs, distance, per capita income, FTA, government policies, language and FDI are the determinants for the development of automobile industry in each country in East Asia. In the case of auto P&C, apart from economic size, the role of government through trade policy (i.e., FTA) and industrial policies as well as the role of MNCs are the major contributors to the development both exports and imports of East Asian countries. In the case of final automobiles, the role of FTA and language seems to be unimportant. Nonetheless, the role of government policies and MNCs seem to be important.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".