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Record W3125222546

The Effects of Gasoline Price Regulations: Experimental Evidence

2012· preprint· en· W3125222546 on OpenAlexaboutno aff
Justus Haucap, Hans Christian Müller

Bibliographic record

VenueRePEc: Research Papers in Economics · 2012
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicMerger and Competition Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsTacit collusionOligopolyCollusionEconomicsHarmGasolineOrder (exchange)MicroeconomicsWelfareConsumer welfarePrice fixingMonetary economicsCournot competitionMarket economy
DOInot available

Abstract

fetched live from OpenAlex

Economic theory suggests that gasoline retail markets are prone to collusive behavior. Oligopoly market structures prevail, market interactions occur frequently, prices are highly transparent, and demand is rather inelastic. A recent sector inquiry in Germany backed suspicions of tacit collusion and suggested to adopt regulatory pricing rules for gas stations similar to those implemented in Austria, parts of Australia, Luxembourg or parts of Canada. In order to increase consumer welfare these rules either restrict the number of price changes per day or they limit the mark‐up for gasoline retail prices. As theoretical predictions about the impact of these measures are mixed and empirical studies rare, we analyze the effects, using an experimental gasoline market in the lab. Our results reveal that two of the suggested rules rather decrease consumer welfare: The Austrian rule which only allows one price increase per day (while price cuts are always possible) and the Luxembourg rule which introduces a maximum markup for retailers. While no rule tends to induce lower retail prices, the Western Australian rule which allows at most one daily price change (no matter whether up or down) does at least not harm consumers.

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)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.052
GPT teacher head0.321
Teacher spread0.269 · 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 designBench or experimental
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

Citations107
Published2012
Admission routes1
Has abstractyes

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