Methodology or pricing: how can the greater volatility of consumer gas and electricity prices in Belgium be explained?
Bibliographic record
Abstract
Over the past three years, it has gradually become clear that consumer gas and electricity prices in Belgium are much more volatile than elsewhere in the euro area or in the three main neighbouring countries. The article first of all examines whether recent methodological changes to the registration method in the consumer price index are an explanatory factor for the differing movements in gas and electricity prices. The analysis shows that this is not the case, implying that the deviations in price movements from those in the reference zones may be attributed to the pricing itself. It also indicates an increase in volatility during the period 2007-2009 in response to a number of changes in pricesetting since the full-scale liberalisation of the gas and electricity market for residential consumption (changes that cannot necessarily be related directly to the liberalisation, however). Moreover, an international comparison of gas and electricity prices excluding taxation reveals that, contrary to what was previously the case, prices in Belgium began to move considerably ahead of those in the euro area in the course of 2008. As far as gas is concerned, this handicap was to disappear again in the third quarter of 2009, whereas the available indicators show that the gap remains substantial in the case of electricity, despite some narrowing. It may also be noted that gas and electricity prices may have then bottomed out and that the transmission (more substantial in Belgium) of the new upward momentum in prices for energy raw materials could lead to a deterioration in the relative position in the near future. It is then open to question which economic factor explains why price fluctuations for energy raw materials in Belgium are having a greater impact on consumer gas and electricity prices than elsewhere. In addition, the higher volatility of gas and electricity prices is also a factor that has to be taken into account when containing broader price and cost movements, especially in a situation where energy prices present a structural upward trend.
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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 | 0.015 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".