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Record W1602822857

ON EQUILIBRIUM IN MONOPOLISTIC COMPETITION

2006· article· en· W1602822857 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEastern Economic Journal · 2006
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic theories and models
Canadian institutionsCarleton University
Fundersnot available
KeywordsMonopolistic competitionEconomicsMicroeconomicsProduct differentiationCompetition (biology)UniquenessRevenueProduct (mathematics)Production (economics)MonopolyCournot competitionMathematics
DOInot available

Abstract

fetched live from OpenAlex

The price, output, and quality of a monopolistic competitor are determined by maximizing the difference between its revenue and its cost, where cost is measured exclusive of the rent on its product-specialized inputs. It can be argued that such a firm must have unique inputs that are specialized to its unique product—since product differentiation is otherwise compatible with perfect competition—and the uniqueness of these inputs allows them to earn positive rent, even in long-run equilibrium. The inclusion of rent in cost gives rise to the traditional Chamberlinian solution, in which (rent-inclusive) average cost is tangent to demand and therefore downward-sloping. But if rent is excluded, average cost may be constant or even upward-sloping in equilibrium, and in this sense, monopolistic competition need not give rise to excess capacity or to production facilities that are too small. The basic conclusion is that monopolistic competition improves welfare—that is to say, it creates consumer and producer surplus—by creating variety without necessarily reducing output.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.123
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.004

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 head0.018
GPT teacher head0.204
Teacher spread0.186 · 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