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Record W4411177823 · doi:10.1016/j.red.2025.101298

Entrepreneurial rates of return and wealth inequality

2025· article· en· W4411177823 on OpenAlex
Bettina Brüggemann, Zachary L. Mahone

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueReview of Economic Dynamics · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Productivity
Canadian institutionsMcMaster University
FundersSocial Sciences and Humanities Research Council of CanadaSocial Sciences and Humanities Research CouncilWestern UniversityUniversity of BristolUniversity of GuelphYork UniversityUniversity of ManchesterUniversity of ManitobaMcMaster University
KeywordsEconomicsInequalityNeoclassical economicsLabour economicsMathematics

Abstract

fetched live from OpenAlex

This paper confronts a model of entrepreneurship and wealth inequality with empirical patterns on rates of return across the wealth distribution. We find the quantitative model implies rates of return largely consistent with the data. Rates of return to business wealth are high, heterogeneous, negatively correlated with net worth, and persistent. Both dispersion in marginal products of capital and leverage are important for explaining the patterns in rates of return along the wealth distribution. Heterogeneous abilities explain a large portion of cross-sectional dispersion and drive persistence in individual returns.

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 categoriesnone
Consensus categoriesnone
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 score0.254
Threshold uncertainty score0.723

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.024
GPT teacher head0.278
Teacher spread0.254 · 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