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Record W2784134961 · doi:10.1162/adev_a_00115

Indonesia's Moratorium on Palm Oil Expansion from Natural Forests: Economy-Wide Impacts and the Role of International Transfers

2018· article· en· W2784134961 on OpenAlexaff
Arief Anshory Yusuf, Louise Roos

Bibliographic record

VenueAsian Development Review · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicOil Palm Production and Sustainability
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsComputable general equilibriumIndonesianPalm oilEconomicsWelfareStock (firearms)Economic welfareNatural resource economicsEconomyMarket economyMacroeconomicsAgroforestryGeographyEnvironmental science

Abstract

fetched live from OpenAlex

Indonesia has introduced a moratorium on the conversion of natural forests to land used for palm oil production. Using a dynamic, bottom-up, interregional computable general equilibrium model of the Indonesian economy, we assess several scenarios of the moratorium and discuss its impacts on the domestic economy as well as on regional economies within Indonesia. We find the moratorium reduces Indonesian economic growth and other macroeconomic indicators, but international transfers can more than compensate the welfare losses. The impacts also vary across regions. Sumatra, which is highly dependent on palm oil and is home to forests that no longer have a high carbon stock, receives fewer transfers and suffers the greatest economic loss. Kalimantan, which is relatively less dependent on palm oil and has forests with a relatively high carbon stock, receives more transfers and gets greater benefit. This implies that additional policy measures anticipating the unbalanced impacts of the moratorium are required if the trade-off between conservation and reducing interregional economic disparity is to be reconciled.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.833
Threshold uncertainty score0.504

Codex and Gemma teacher scores by category

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

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 head0.004
GPT teacher head0.215
Teacher spread0.212 · 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.

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

Citations22
Published2018
Admission routes1
Has abstractyes

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