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Record W3121178668

Uncorking a Strange Brew: The Need for More Competition in Ontario’s Alcoholic Beverage Retailing System

2014· article· en· W3121178668 on OpenAlexaboutno aff
Paul R. Masson, Anindya Sen

Bibliographic record

VenueC.D. Howe Institute Commentary · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicWine Industry and Tourism
Canadian institutionsnot available
Fundersnot available
KeywordsCompetition (biology)WineryRevenueBusinessPer capitaGovernment (linguistics)Agricultural economicsWineCommerceEconomicsFinanceFood science
DOInot available

Abstract

fetched live from OpenAlex

The lack of competition in Ontario’s system for alcoholic beverage retailing causes higher prices for consumers and foregone government revenue. A major component of the lack of competition is the disadvantage faced by small Ontario wineries and breweries relative to the larger producers. Three large brewers own The Beer Store, which dominates retailing of beer, while two large wineries enjoy the right to sell their wines in major off-winery stores: the Wine Shop and the Wine Rack. We find that freeing up alcoholic beverage retailing would result in increased government revenue, lower prices, and more convenience. Other factors being equal, Western Canadian provinces with more competition had 7 percent more per capita provincial alcohol profits than provinces with government-run monopolies. To compare Ontario’s beer prices relative to those in Quebec, a province with considerably more retail competition, we collected data on prices of comparable domestic and international brands sold in both provinces. We find modest price differences for domestic beer brands, but much higher prices in Ontario for international brands relative to Quebec. We also find that retailing costs are lower in Ontario because The Beer Store enjoys significant economies of scale. These factors combined allow brewers to earn what we estimate to be $450 to $630 million in additional profits compared to what would have occurred in a competitive retail market similar to that in Quebec. Within Ontario, we find very high prices for restaurant customers relative to retail customers. The wine industry in Ontario also has little retail competition. The LCBO and two chains of off-winery stores dominate sales. Other wineries have a hard time finding shelf space for their brands at the LCBO and (with a few exceptions) do not have access to off-winery stores. That slows their expansion and limits their economies of scale. Opening up wine retailing to free competition would reduce the advantage held by a few large producers and help create a healthier wine industry in Ontario. We recommend that the Ontario government create a more competitive system for alcoholic beverage marketing through a gradual process of liberalization. In particular, it should: • Allow sales of wine and beer in grocery and convenience stores, as in Quebec; • Further open up beer retailing by licensing other retail outlets; • Free up wine retailing by granting licences for off-winery stores to other wineries and also to new wine retailers. These changes would increase the choices available and reduce prices for Ontario consumers, as well as improve the competitiveness of Ontario’s smaller wineries and breweries and generate more revenue for the government.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.058
Threshold uncertainty score0.420

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0090.002
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.000

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 head0.032
GPT teacher head0.226
Teacher spread0.194 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations2
Published2014
Admission routes1
Has abstractyes

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