Abstract
A rich theory literature predicts mixed strategies in posted prices due to standard price discrimination, search frictions, and various other rationales. While typically interpreted as implying occasional sales or price dispersion, online marketplaces enable a firm to truly use randomization as a tool in pricing, and so such behavior should be expected to arise in online settings. We investigate a case of mixed pricing across a large subset of products on a major e-commerce website. We first test for randomizing behavior, and then construct a model of price discrimination that would generate randomization as optimal behavior. We estimate the model and use it to assess pricing effects of a proposed merger in the industry.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 129-155 |
| Number of pages | 27 |
| Journal | Quantitative Marketing and Economics |
| Volume | 14 |
| Issue number | 2 |
| DOIs | |
| State | Published - Jun 1 2016 |
Funding
We thank the Dean’s Research Fund at the Wharton School for financial support. Elizabeth Oppong and Manasvi Ramanujam provided outstanding research assistance. We would like to thank those that provided helpful comments at IIOC, the Econometric Society, and Designing the Digital Economy Conferences, as well as Judy Chevalier, Joe Harrington, JF Houde, Rob Porter, Bruno Strulovici, Jennifer Valentino-Devries, anonymous referees, and others.
Keywords
- Merger analysis
- Online markets
- Price discrimination
ASJC Scopus subject areas
- Economics, Econometrics and Finance (miscellaneous)
- Marketing