Competitividade externa de commodities brasileiras: o caso das rochas ornamentais e de revestimento
Bibliographic record
Abstract
The international trade of marble and granite products, in particular that of ornamental stones and cladding material, has seen, in recent decades, a marked increase in world demand and trade. In this sector, Brazil is a major world player, either as a producer or as exporter. In this sense, it is important to identify which are the factors and the competitive advantages of Brazilian exports of these commodities. The approach followed in this study was based on an ex-post analysis, through the calculation of some international trade indicators, in the 2004-2015 period, namely the Revealed Comparative Advantages Index (RCAI), the Regional Orientation Index (ROI) and the Constant Market Share (CMS) model. The goal is to analyze the performance of Brazilian exports, of the main ornamental and cladding rocks, and to identify their main sources of growth, compared to world exports. The results indicate that, on an aggregate perspective, Brazil has comparative advantages in the entire period (2004-2015), as well as an increase in the share of Brazilian exports in the international market in the recent period, 2012-2015. The ROI results indicate that the Brazilian exports of these products are moving towards the United States of America (USA) and, to a lesser extent, to Italy, Mexico, Canada and Taiwan. Also, the US presents the most dynamic growth rate for the ROI. In addition, the results indicate that some traditional European markets such as the United Kingdom and Spain, are losing relative importance as destination markets for Brazilian exports of these commodities. Regarding the main sources of exports growth, in the first two subperiods, 2004-2007 and 2008-2011, the results indicate that the Brazilian export growth, for the whole sector, was due, mainly, to the growth effect of world trade and that the competitiveness effect was negative in both subperiods. For the most recent period, 2012-2015, the results indicate that the destination effect of exports seems to be the main source of the Brazilian exports growth of these products. Additionally, in this period, the competitiveness effect reaches a positive value. Recognizing the methodology limitations, which can’t identify the variables that determined Brazil's competitiveness in these commodities trade, the results indicate that Brazilian exporters of these commodities may increase exports, especially to new markets with a very dynamic demand.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| 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".