Export competitiveness and concentration analysis of major sugar economies with special reference to India
Bibliographic record
Abstract
Purpose This paper seeks to examine the export competitiveness and concentration level of the 15 top sugar exporting countries over the last 18 years (2001–2018) with special reference to India. Design/methodology/approach First, the paper utilizes a review based approach and explains the structures of major sugar economies in context to protected and unprotected perspectives. Subsequently, empirical research was carried out to assess the competitiveness level of sugar using Revealed Comparative Advantage (RCA) approach and Hirschman Herfindahl Index. Findings The study found structural changes in cane or beet sugar, and molasses over the time period between 2006 and 2015. Further, the findings confirmed that despite the stringent regulations in European Union, the United States of America, Guatemala, Mexico, Thailand, China, and India, the comparative advantage is high up to seven to nine sugar categories. Besides, despite the indulgent regulations in the Colombia, Brazil, and Canada, the comparative advantage is only consistent up to two to three sugar categories. Research limitations/implications This study provides an overview of competitiveness patterns of 15 sugar exporting countries and further compare their comparative and concentration levels. In this context, in future, it would be interesting to study the macro-economic and firm and industry-specific factors which may strengthen the study findings. Practical implications This study suggests that the sugar export of few countries (i.e. Mexico and Canada) is restricted up to their trade pacts and free trade zones which is restricting the competitiveness level and performance. Accordingly, such countries need to enlarge their business boundaries to foster their export competitiveness level. Rational subsidies and governmental assistance in diversification schemes in terms of products' range and sustainable processes can make India a consistent exporter in more categories. Originality/value Although, the previous studies attempted to examine the sugar industry with particular country context, this study enlarge the body of knowledge through simultaneously examining the sugar export scenario of fifteen sugar exporting countries and providing a broad comparative view of their competitiveness and concentration levels.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".