Willingness to Pay for Solar Lanterns: Does the Trial Period Play a Role?
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.
Bibliographic record
Abstract
Abstract Where electricity access is limited, solar lanterns are a viable and relatively inexpensive source of basic lighting for households. However, the creation of commercially viable business models for solar lanterns is difficult because the customers are poor and make decisions under tight liquidity constraints. To understand the economics of technology adoption in the case of solar lanterns, we conduct a field experiment on willingness to pay (WTP) for solar lanterns in rural Uttar Pradesh. Applying the Becker–DeGroot–Marschak method of eliciting WTP, we evaluate the ability of a trial period and postponed payment to increase sales. We find no evidence for the effectiveness of the trial period and only weak evidence for the positive effect of postponed payment. Overall, WTP for the product among the customers is low. There is no clear evidence for concerns about the uncertain quality of the product, liquidity constraints, or present‐bias. In this context, policies to subsidize very small solar lanterns would not correct a market failure, as people appear to have only a limited interest in the product.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it