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Record W2025515470 · doi:10.1139/x00-168

Analysing the Finnish pulpwood market under alternative hypotheses of competition

2001· article· en· W2025515470 on OpenAlexvenueno aff
Maarit Kallio

Bibliographic record

VenueCanadian Journal of Forest Research · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsPulpwoodMonopsonyEconomicsCournot competitionMicroeconomicsPerfect competitionCompetition (biology)RecessionBoomImperfect competitionMacroeconomicsPulp and paper industryEcology

Abstract

fetched live from OpenAlex

Efficient functioning of the wood market is crucial in a country where the forest sector is of strong macroeconomic importance. We investigate the possibility of noncompetitive behavior of the buyers in the Finnish pulpwood market. We simulate the buyers' behavior under alternative competition structures (perfect competition, Cournot oligopsony, and monopsony) and compare the simulated equilibria with the observed behavior in the years 1988–1997. In the static models the pulp industry firms are assumed to maximize their short-run variable profits either under fixed production capacity or, hypothetically, under variable capacity. The results suggest that, during the boom years, the industry has been capacity constrained, sometimes even for monopsony output. During the recession years, the actual wood prices have often been between simulated Cournot oligopsony and monopsony prices. Hence, noncompetitive behavior of the buyers is possible during the recessions. The capacity investment behavior of the industry is explored with dynamic models. The conclusions from these models depend on the price elasticity of pulpwood supply used.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.208
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.000

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 head0.064
GPT teacher head0.317
Teacher spread0.253 · 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 teacher head, not a consensus.

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

Citations21
Published2001
Admission routes1
Has abstractyes

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