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Record W2564364335 · doi:10.1111/agec.12351

Demand for a labor‐based drought insurance scheme in Ethiopia: a stated choice experiment approach

2016· article· en· W2564364335 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

VenueAgricultural Economics · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural risk and resilience
Canadian institutionsUniversity of Waterloo
FundersNorges Forskningsråd
KeywordsWillingness to payCashIndex (typography)PaymentActuarial scienceMixed logitWageEconomicsWork (physics)SubsidyBusinessLabour economicsFinanceLogistic regressionMicroeconomics

Abstract

fetched live from OpenAlex

Abstract Index‐based weather insurance is increasingly used to manage weather‐related risks in smallholder agriculture. However, cash‐constrained smallholders often lack the resources to pay an insurance premium, which may undermine its wider adoption. This article investigates alternative insurance payment methods that may help to enhance the adoption of index‐based weather insurance. We use a choice experiment to elicit smallholders’ willingness to pay in cash or labor for index‐based weather insurance in four districts in the south‐central highlands of Ethiopia. The insurance schemes were created using a fractional factorial design with three factors: work, cash, and payout rate. We analyze the choice data using a random parameter mixed logit model. We find that the average participants need a subsidy to pay cash for insurance because their willingness to pay is less than the expected cost of the insurance. On average, they are willing to pay only 0.81 ETB (Ethiopian currency) to get an expected yearly payout of 1 ETB. However, most are willing to participate in work‐for‐insurance programs at lower daily wage rates than is common for other work programs in Ethiopia.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.787
Threshold uncertainty score0.343

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.017
GPT teacher head0.225
Teacher spread0.208 · 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