LOW OIL PRICES: LONG-TERM ECONOMIC EFFECTS FOR THE EU AND OTHER GLOBAL REGIONS BASED ON THE CGE PLACE model
Bibliographic record
Abstract
Oil prices on global markets have plunged from US$115 per barrel in mid-June of 2014 to US$48 at end-January 2015, and around US$30 in January 2016. Oil prices that remain low over the long-term would give a positive boost to the global economy, but the effects will vary across countries. While net oil (fossil fuel) importers are expected to win (Europe, Japan, China, India), net oil exporters (OPEC countries, EFTA, Russia, Canada) are set to lose. However, in the EU, with carbon emission constraints in place, the possible benefits for oil users will be restricted because of climate regulations. This paper quantifies the economic effects of lower fossil fuel prices in the 2020 time horizon, modeled as a supply shock, and emphasizes their interaction with EU climate policy. The impact assessment of the oil price shock was conducted using a multi-county, multi-sector computable general equilibrium (CGE) model, PLACE, maintained by the Center for Climate Policy Analysis (CCPA) in Warsaw. The effects of a permanent 60 percent oil price shock are assessed against a baseline scenario through 2020 based on the IEA 2012 World Energy Outlook assuming a high oil price scenario of US$118 in 2015 and US$128 in 2020 (both in 2010 constant prices) and correlated price changes of coal (by 50 percent), and natural gas (by 30 percent). Model simulations show that, first, oil exporters will suffer substantial double-digit welfare losses through 2020 due to significant deterioration in their terms of trade. Second, the EU, as a large oil importer, will benefit significantly from lower oil prices, with the New Member States being relatively better off, as a consequence of their relatively high energy intensity. Third, if the assumed permanent oil price shock occurs at half the level of the headline 60 percent scenario (proxying for US dollar appreciation or reflecting a rebound in oil prices from their early 2015 levels through 2020), welfare effects will be smaller and less than proportional for most countries. Finally, in the EU, the existing emissions cap constrain the use of cheaper fossil fuels and limits the welfare increase by about 0.5 percentage points.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".