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Record W3121251901

Moral Hazard: Experimental Evidence from Tenancy Contracts

2017· preprint· en· W3121251901 on OpenAlexaff
Konrad Burchardi, Selim Gulesci, Benedetta Lerva, Munshi Sulaiman

Bibliographic record

VenueSSRN Electronic Journal · 2017
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicLand Rights and Reforms
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsSharecroppingLeasehold estateMoral hazardIncentiveCashEconomicsCash flowMicroeconomicsCash cropControl (management)AgricultureProduction (economics)Finance
DOInot available

Abstract

fetched live from OpenAlex

We report results from a field experiment designed to estimate the effects of tenancy contracts on agricultural input choices, risk-taking, and output. The experiment induced variation in the terms of sharecropping contracts: some tenants paid 50% of output in compensation for land usage; others paid 25%; again others paid 50% of output and received cash, either fixed or stochastic. We find that tenants with higher output share utilized more inputs, cultivated riskier crops, and generated 60% more output relative to control. Cash transfers did not effect farm output. We interpret the increase in output as the incentive effect of sharecropping.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
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 score0.903
Threshold uncertainty score0.999

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
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 head0.031
GPT teacher head0.262
Teacher spread0.231 · 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.

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

Citations0
Published2017
Admission routes1
Has abstractyes

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