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Record W4412031952 · doi:10.1287/mnsc.2024.04555

Is the Price Right? The Role of Economic Trade-Offs in Explaining Reactions to Price Surges

2025· article· en· W4412031952 on OpenAlexaboutno aff
Julio Elías, Nicola Lacetera, Mario Macis

Bibliographic record

VenueManagement Science · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsInternational economicsPrice settingMonetary economicsMicroeconomics

Abstract

fetched live from OpenAlex

Public authorities often introduce price controls following price surges, potentially causing inefficiencies and exacerbating shortages. A survey experiment with 7,612 Canadian and U.S. respondents shows that unregulated price surges raise moral objections and widespread disapproval. However, acceptance increases and demand for regulation declines when participants are prompted to consider economic trade-offs between controlled and unregulated prices, whereby incentives from higher prices lead to additional supply and enhance access to goods. Moreover, highlighting these trade-offs reduces polarization in moral judgments between supporters and opponents of unregulated pricing. Textual analysis of responses to open-ended questions provides further insights into our findings, and an incentivized donation task demonstrates consistency between stated preferences and real-stakes behavior. Although economic trade-offs do influence public support for price control policies, the evidence indicates that even when the potential gains in economic efficiency from unregulated prices are explicit, a significant divide persists between the utilitarian views that standard economic thinking implies and the nonutilitarian values held by the general population. This paper was accepted by Dorothea Kübler, behavioral economics and decision analysis. Funding: This work was supported by Johns Hopkins “Catalyst Award” and Business of Health Initiative (HBHI) and the Sandra Rotman Centre for Health Sector Strategy at the University of Toronto. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.04555 .

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 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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.751
Threshold uncertainty score0.266

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.239
Teacher spread0.223 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations1
Published2025
Admission routes1
Has abstractyes

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