COMPETITIVENESS OF CANADIAN AGRI-FOOD EXPORTS AGAINST COMPETITORS IN ASIA: 1980-97
Bibliographic record
Abstract
Asia is the second largest market for the Canadian agri-food exports after the United States market. The competition in Asia has become more intensive in recent years as the agri-food sector in developed nations such as Australia, Canada, Europe, and the United States has increasingly relied on exports for growth because of their own slow-growing domestic food consumption. How did the performance of Canadian agri-food exports to Asia measure up to the performances of its main competitors? This research attempts to identify Canada's competitiveness in agri-food exports to Asia, relative to Canada's main competitors. The analysis is based on the 1980-97 trade data from the World Trade Analyzer (WTA), produced by the International Trade Division of Statistics Canada. According to their average market shares during the 1980-97 period, Canada's main competitors in Asia are the United States, Europe, Australia, China, Thailand, Malaysia, Taiwan, Indonesia and New Zealand. To assess each country's competitiveness, this research applies the Constant Market Share (CMS) model. The change in each country's exports is primarily divided into the structural and the competitive effects. The exporting country with larger competitive effect is considered to be more competitive. The key results are: * All exporting countries increased their agri-food exports to Asia during the 1980-97 period. The increase in their exports to Asia can be primarily attributed to the structural effect - particularly to the large increase of total Asian agri-food imports (growth effect). * Canada ranked second after China in terms of competitive effect during the 1980-1997 period. Indonesia and Thailand also exhibit strong competitiveness in Asia. Canada's traditional competitors such as the United States, Europe, Australia, and New Zealand were found to be non-competitive. * Compared with other competitors in the Asian market, Canada exhibit two areas of weakness. First, Canada did not concentrate their agri-food exports to Asia on fast-growing commodities such as consumer-ready products. Second, Canada's competitiveness was deteriorated in the processed intermediate goods in Korea and South Asia, the consumer-ready goods in Japan and Asia 7, and the bulk commodities in Taiwan. If Asia was considered to be a target region for Canadian agri-food exports, one would need not only to know the exporting strategies that will be adopted by countries such as the United States, Europe, Australia, and New Zealand, but also those adopted by countries such as China, Indonesia and Thailand. In order for Canada to maintain and improve its export performance in Asia in the future, it will be most effective if Canada could increase its market shares of processed intermediate goods in Korea and South Asia, the consumer-ready goods in Japan and Asia 7, and the bulk commodities in Taiwan.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".