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Record W3014828573 · doi:10.1093/wber/lhaa010

Increasing Financial Inclusion in the Muslim World: Evidence from an Islamic Finance Marketing Experiment

2020· article· en· W3014828573 on OpenAlex
Dean Karlan, Adam Osman, Nour Shammout

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 World Bank Economic Review · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsKellogg's (Canada)
Fundersnot available
KeywordsLoanShariaFinancial inclusionPaymentProduct (mathematics)EconomicsIslamInterest rateFinancial servicesBusinessCommercial lawAccountingFinanceLaw

Abstract

fetched live from OpenAlex

Abstract Low utilization of household credit in developing countries may be partially due to religious considerations. In a randomized marketing experiment in Jordan, this paper estimates the effect of sharia-compliant loan features on demand for credit. To comply with Islamic law, the sharia-compliant product uses a bank fee rather than an interest payment structure, while keeping the rest of the product features very similar. Sharia-compliance increased the application rate for loans from 18 percent to 22 percent, an increase in demand that is equivalent to a 10 percent decrease in interest rates. This study also randomly varied the price of the sharia-compliant loan and finds that less religious individuals are twice as elastic with respect to price as the more religious. By comparing reasons for refusal across treatment groups, this paper estimates that survey measures that try to assess the importance of religious objections to conventional credit overestimate the importance of this type of objection by a third.

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)0.004
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.764
Threshold uncertainty score0.826

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.002
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 head0.028
GPT teacher head0.271
Teacher spread0.243 · 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