MétaCan
Menu
Back to cohort
Record W2280192177 · doi:10.1093/forestry/cpv038

A trade flow analysis of the global softwood log market: implications of Russian log export tax reduction and New Zealand log production restriction

2015· article· en· W2280192177 on OpenAlexaffabout
Wei-Yew Chang, Chris Gaston

Bibliographic record

VenueForestry An International Journal of Forest Research · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsFPInnovationsUniversity of British Columbia
Fundersnot available
KeywordsSoftwoodProduction (economics)Agricultural economicsEconomicsBaseline (sea)ChinaInternational economicsInternational tradeGeographyBiologyMacroeconomicsBotany

Abstract

fetched live from OpenAlex

This study employs a recursive dynamic spatial partial equilibrium model to investigate the trade flow trends in the global softwood log market. A baseline forecast from 2012 to 2021 is first projected and then compared with three alternative scenarios: (1) Russia reduces its ad valorem softwood log export tax to 8 per cent to comply with its World Trade Organization accession agreements; (2) New Zealand experiences no expansion at all of its plantation forest log production due to social and environmental considerations (i.e. increased Māori ownership of forest land and the implementation of emissions trading schemes); and (3) a combination of the proposed policies in Russia and New Zealand mentioned above. The results of the baseline projection demonstrate that softwood log prices will increase in every region globally and that China will continue to be the world's largest softwood log importer. However, softwood log exports from Russia, the US and Canada are expected to drop significantly as a result of current Russian export restrictions, the recovery of the US housing market and mountain pine beetle infestations in western Canada. A comparison of the simulated scenarios with the baseline projection reveals that reducing the Russian softwood log export tax will have a greater impact on softwood log prices and total world trade than restricting log production in New Zealand due to the comparatively large log production capacity in Russia. In any scenario, significant trade flow changes (i.e. trade-offs) in response to the proposed policy changes are observed in China and the major export regions. The results of this study offer insights for forest managers and policy makers to examine the global impacts of potential changes in trade policies and supply constraints in these two important softwood log supply regions in addition to highlighting China's role in the world softwood log market.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.100
Threshold uncertainty score0.198

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.054
GPT teacher head0.351
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations12
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueForestry An International Journal of Forest ResearchSame topicForest Management and PolicyFrench-language works237,207