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ON FINANCE AS A THEORY OF TFP, CROSS‐INDUSTRY PRODUCTIVITY DIFFERENCES, AND ECONOMIC RENTS*

2008· article· en· W1990938095 on OpenAlexaff
Andrés Erosa, Ana Hidalgo-Cabrillana

Bibliographic record

VenueInternational Economic Review · 2008
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEconomic rentProductivityEconomicsTotal factor productivityStatus quoEnforcementCapital (architecture)Labour economicsMonetary economicsMicroeconomicsMacroeconomicsMarket economy

Abstract

fetched live from OpenAlex

We develop a theory of capital‐market imperfections to study how the ability to enforce contracts affects resource allocation across entrepreneurs of different productivities, and across industries with different needs for external financing. The theory implies that countries with a poor ability to enforce contracts are characterized by the use of inefficient technologies, low aggregate TFP, large differences in labor productivity across industries, and large employment shares in industries with low productivity. These implications are supported by the empirical evidence. The theory also suggests that entrepreneurs have a vested interest in maintaining a status quo with low enforcement.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.008
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0010.006
Scholarly communication0.0030.006
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.256
Teacher spread0.224 · 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 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

Citations95
Published2008
Admission routes1
Has abstractyes

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