Clicks, Discontinuities, and Firm Demand Online
Abstract
We exploit a unique dataset from a price comparison site to estimate the determinants of clicks received by online retailers. We find that a firm enjoys a 60% jump in its clicks when it offers the lowest price at the site, and failure to account for discontinuities distorts parameter estimates by nearly 100%. This discontinuity is consistent with a variety of models that have been used to rationalize online price dispersion. Finally, we show that one may use estimates of the determinants of a firm's clicks to obtain bounds on its underlying demand parameters, including standard elasticities of demand.
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The ranking signal is directly observable and has a clear economic interpretation since higher ranks translate strongly into more clicks, conversions, and revenue.
“This ranking signal is directly observable and has a clear economic interpretation since higher ranks translate strongly into more clicks, conversions, and revenue (Baye et al., 2009).”
From E-GEO: A Testbed for Generative Engine Optimization in E-Commerce (2025) · cites this paper as Baye et al., 2009
Cited by
Sorted by citations
How Does Popularity Information Affect Choices? A Field Experiment
Tucker, C., & Zhang, J. (2011) · Management Science · doi:10.1287/mnsc.1110.1312 · Cited by 322 · see citing works
Examining the Impact of Ranking on Consumer Behavior and Search Engine Revenue
Ghose, A., Ipeirotis, P. G., & Li, B. (2014) · Management Science · doi:10.1287/mnsc.2013.1828 · Cited by 299 · see citing works
An Empirical Analysis of User Content Generation and Usage Behavior on the Mobile Internet
Ghose, A., & Han, S. P. (2011) · Management Science · doi:10.1287/mnsc.1110.1350 · Cited by 282 · see citing works
Gorodnichenko, Y., & Talavera, O. (2017) · American Economic Review · doi:10.1257/aer.20141127 · Cited by 43 · see citing works
E-GEO: A Testbed for Generative Engine Optimization in E-Commerce
Bagga, P. S., Farias, V. F., Korkotashvili, T., Peng, T., & Wu, Y. (2025) · arXiv · doi:10.48550/arxiv.2511.20867 · Cited by 1 · see citing works
“Moreover, a large empirical literature shows that higher rankings translate strongly into increased clicks, conversions, and revenue (e.g., see Baye et al. (2009) and references therein), making GEO performance readily interpretable in economic terms.”
- Authors
- Baye, M. R., Gatti, J. R. J., Kattuman, P., & Morgan, J.
- Affiliations
- Indiana University Bloomington (US)
- University of Cambridge (GB)
- University of California, Berkeley (US)
- Venue
- Journal of Economics & Management Strategy
- Publisher
- Wiley
- Published
- 2009-10-21
- Volume
- 18
- Issue
- 4
- Pages
- 935-975
- ISSN
- 1058-6407 (ISSN-L)
- 1530-9134
- OpenAlex
- W2166577222
- Cited by
- 79
- References
- 0
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 1 · 2023: 4 · 2022: 4 · 2021: 6 · 2020: 3 · 2019: 1 · 2018: 6 · 2017: 8 · 2016: 4 · 2015: 6 · 2014: 8 · 2013: 6 · 2012: 7
- FWCI
- 17.83
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Economics & Management Strategy (publishedVersion)
- Faculty Digital Archive (New York University Florence) (submittedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Market Behavior and Pricing
- Social Sciences › Business, Management and Accounting › Strategy and Management › Digital Platforms and Economics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Merger and Competition Analysis
- Keywords
- online retail, price comparison sites, price dispersion, demand estimation
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