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Record W2033615651 · doi:10.1093/qje/qjr056

Incentives and the De Soto Effect

2012· article· en· W2033615651 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

VenueThe Quarterly Journal of Economics · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLand Rights and Reforms
Canadian institutionsCanadian Institute for Advanced Research
Fundersnot available
KeywordsCollateralEconomicsMoral hazardIncentiveWelfareMargin (machine learning)Competition (biology)MicroeconomicsProperty rightsDistribution (mathematics)Monetary economicsMarket economyFinance

Abstract

fetched live from OpenAlex

This paper explores the consequences of improving property rights to facilitate the use of fixed assets as collateral, popularly attributed to the influential policy advocate Hernando de Soto. We use an equilibrium model of a credit market with moral hazard to characterize the theoretical effects, and also develop a quantitative analysis using data from Sri Lanka. We show that the effects are likely to be non-linear and heterogeneous by wealth group. They also depend on the extent of competition between lenders. There can be significant increases in profits and reductions in interest rates when credit markets are competitive. However, since these are due to reductions in moral hazard, i.e. increased effort, the welfare gains tend to be modest when cost of effort is taken into account. Allowing for an extensive margin where borrowers gain access to the credit market, can make these effects larger depending on the underlying wealth distribution.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.955
Threshold uncertainty score0.115

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)0.0000.000

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 head0.007
GPT teacher head0.184
Teacher spread0.177 · 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