arbiter
JournalsPricingAccount

Optimal Refund Mechanism With Consumer Learning

Qianjun Lyu

RAND Journal of Economics2026https://doi.org/10.1111/1756-2171.70046article
AJG 4ABDC A*
Weight
0.50

What the paper says

This article studies the optimal refund mechanism when an uninformed buyer learns about their valuation over time. We consider various refund mechanisms including simple return policies (no returns or free returns), and stochastic return policies, which allow the buyer to keep the product with some probability upon receiving a refund. We show that the optimal refund mechanism is deterministic and takes a simple form: either the seller deters buyer learning by offering a low price without returns, or encourages maximal learning by setting a high price with free returns. Interestingly, free returns are optimal only for intermediate prior beliefs.

Open paper page →

Cite this paper

https://doi.org/https://doi.org/10.1111/1756-2171.70046

Or copy a formatted citation

@article{qianjun2026,
  title        = {{Optimal Refund Mechanism With Consumer Learning}},
  author       = {Qianjun Lyu},
  journal      = {RAND Journal of Economics},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1111/1756-2171.70046},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Optimal Refund Mechanism With Consumer Learning

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.