Pollution haven hypothesis and India's intra-industry trade: an analysis
Bibliographic record
Abstract
With the adoption of trade liberalisation measures India's merchandised trade has expanded considerably in post-1991. One of the important factors of such commendable growth is the significant expansion in India's Intra-industry Trade. Given this circumstance, it is an important task to find out whether such rapid growth in Intra-industry Trade (IIT) has any detrimental effect on the environment. With this purpose, the current paper measures the shares of pollution content of India's 'inter-industry trade' and 'IIT', and its impact on the environment by using Input-Output framework for the period 2001–2002 to 2011–2012. Applying the Grubel-Lloyd index the paper estimates the shares of IIT including Vertical and Horizontal in India's total trade with the USA and the EU-27. It observes that the Vertical IIT is dominant over those of the Horizontal IIT and export in IIT is highly pollution intensive. Above all, the results of Pollution terms of trade provide stronger evidence on the pollution haven effect.
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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 | 0.001 | 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 | 0.001 |
| 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".