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Record W3131058939 · doi:10.15353/rea.v11i1.1515

Worker Heterogeneity and the Popularity of the Minimum Wage Institution

2019· article· en· W3131058939 on OpenAlexvenueno aff
George Economides, Thomas Moutos

Bibliographic record

VenueReview of Economic Analysis · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsLabour economicsWelfareStock (firearms)Consumption (sociology)WageMinimum wage

Abstract

fetched live from OpenAlex

This paper analyzes long run outcomes resulting from adopting a binding minimum wage. The model distinguishes between workers of heterogeneous ability, and capitalists who do all the saving, and it entails – relative to the perfectly competitive benchmark - large output and employment losses (among the lowest-ability workers) from the imposition of moderately binding minimum wages. These effects arise not only because firms respond to the wage increase – relative to the static perfectly competitive benchmark – by moving upwards along a given labour demand curve, but also due to inward shifts of the labour demand curve as savers respond to decreases in the (net of taxes) rate of return on their savings by saving less, thus reducing the economy’s steady-state capital stock. Nevertheless, and despite the large, long-run, declines in aggregate output, consumption, and the capital stock implied by this model, MW legislation can be beneficial for large segments of employed workers, as long as they do not have to provide generous welfare support to the low-ability workers that the MW prevents them from finding employment.

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)0.002
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: Empirical
Teacher disagreement score0.519
Threshold uncertainty score0.664

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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)0.0010.000

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 head0.020
GPT teacher head0.249
Teacher spread0.229 · 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
Published2019
Admission routes1
Has abstractyes

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