Análise da oferta e da demanda de produtos oriundos das florestas nativas dentro do Brasil - período de 1986 a 2016
Bibliographic record
Abstract
Analysis of supply and demand for products from native forests within Brazilfrom 1986 to 2016This master thesis aims to analyze both domestic supply and demand for wooden and no-wooden products collected from Brazilian native forests in the period between 1986 and 2016.Domestic supply and demand equations for charcoal, firewood and roundwood (wooden products); yerba mate and coagulated latex (non-wooden products) were run, based on twostage least square method (2SLS).The data related to the quantity and price were collected from IBGE´s Production of Vegetable Extraction and Silviculture survey (PEVS) and from Municipal Agricultural Production (PAM).Data related to Brazilian goods imports and exports were obtained from Comex Stat system.GDP per capita and minimum wage were also used.The analysis of the quantity and price of extractive products showed that there was a decrease in the quantity produced for all native extractive products, except for yerba mate, which has incresed.With regard to their prices, there were large oscillations, with no single trend observed.It was also found that the consumption of extractive products from Brazilian native forests takes place primarily internally.From the results of the estimated equations, it is highlighted that for all the analyzed products, the supply was price inelastic.Domestic demands for native roundwood, native firewood and native yerba mate were price elastic.On the other hand, demands for native charcoal and native coagulated latex were price inelastic.Only the demand for firewood and roundwood were income inelastic.The demands for native charcoal, native yerba mate and native coagulated latex proved to be income elastic.Except for roundwood, each good showed cross-price elasticities of demand greater than their price-elasticities.These results give new insights into the functioning of the markets for the five products analyzed.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".