Working Paper: NBER ID: w17385
Authors: Liran Einav; Theresa Kuchler; Jonathan D. Levin; Neel Sundaresan
Abstract: The internet has dramatically reduced the cost of varying prices, displays and information provided to consumers, facilitating both active and passive experimentation. We document the prevalence of targeted pricing and auction design variation on eBay, and identify hundreds of thousands of experiments conducted by sellers across a wide array of retail products. We show how this type of data can be used to address questions about consumer behavior and market outcomes, and provide illustrative results on price dispersion, the frequency of over-bidding, the choice of reserve prices, "buy now" options and other auction design parameters, and on consumer sensitivity to shipping fees. We argue that leveraging the experiments of market participants takes advantage of the scale and heterogeneity of online markets and can be a powerful approach for testing and measurement.
Keywords: eBay; seller experiments; consumer behavior; auction design
JEL Codes: C93; D44; L13; L86
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| auction parameters (D44) | sale probabilities (L11) |
| auction parameters (D44) | sale prices (P22) |
| increasing auction reserve price (D44) | lower probability of sale (D49) |
| increasing auction reserve price (D44) | higher price conditional on sale (D49) |
| lower start prices (D44) | increase odds of sale (M31) |
| lower start prices (D44) | increase final sale price (D44) |
| buy now option (G13) | increase seller revenues (D49) |
| shipping fees (L87) | final sale prices (D44) |