Leveraging Market Power through Tying: Does Google Behave Anti-Competitively?

Edelman, Benjamin. “Leveraging Market Power through Tying: Does Google Behave Anti-Competitively?” Harvard Business School Working Paper, No. 14-112, May 2014.

I examine Google’s pattern and practice of tying to leverage its dominance into new sectors. In particular, I show how Google used these tactics to enter numerous markets, to compel usage of its services, and often to dominate competing offerings. I explore the technical and commercial implementations of these practices, then identify their effects on competition. I conclude that Google’s tying tactics are suspect under antitrust law.

Advertising Disclosures: Measuring Labeling Alternatives in Internet Search Engines

Edelman, Benjamin, and Duncan S. Gilchrist. “Advertising Disclosures: Measuring Labeling Alternatives in Internet Search Engines.” Information Economics and Policy 24, no. 1 (March 2012): 75-89.

In an online experiment, we measure users’ interactions with search engines, both in standard configurations and in modified versions with clearer labels identifying search engine advertisements. In particular, for a random subset of users, we change “Sponsored links” or “Ads” labels to instead read “Paid Advertisements.” Relative to users receiving the “Sponsored link” or “Ad” labels, users receiving the “Paid Advertisement” label click 25% and 27% fewer advertisements, respectively. Users seeing “Paid Advertisement” labels also correctly report that they click fewer advertisements, controlling for the number of advertisements they actually click. Results are most pronounced for commercial searches and for vulnerable users with low education and little online experience.

Antitrust Scrutiny of Google

Edelman, Benjamin. “Antitrust Scrutiny of Google.” Journal of Law 2, no. 2 (2012): 445-464.

I evaluate antitrust claims against Google and propose possible remedies. While Google’s specific tactics are often novel, I show connections to practices deemed unlawful over a period of decades, and I identify remedies well grounded in antitrust precedent.

Bias in Search Results?: Diagnosis and Response

Edelman, Benjamin. “Bias in Search Results?: Diagnosis and Response.” Indian Journal of Law and Technology 7 (2011): 16-32.

I explore allegations of search engine bias, including understanding a search engine’s incentives to bias results, identifying possible forms of bias, and evaluating methods of verifying whether bias in fact occurs. I then consider possible legal and policy responses, and I assess search engines’ likely defenses. I conclude that regulatory intervention is justified in light of the importance of search engines in referring users to all manner of other sites, and in light of striking market concentration among search engines.

Least-Cost Avoiders in Online Fraud and Abuse

Edelman, Benjamin. “Least-Cost Avoiders in Online Fraud and Abuse.” IEEE Security & Privacy 8, no. 4 (July-August 2010): 78-81.

Web users face considerable fraud, malfeasance, and economic harm that system operators could prevent or mitigate. Although the legal system can respond, regulations have mixed results. I examine the applicable legal rules that constrain online fraud and the economic underpinnings to identify whether those rules assign responsibility to the parties best positioned to take action.

Deterring Online Advertising Fraud Through Optimal Payment in Arrears

Edelman, Benjamin. “Deterring Online Advertising Fraud Through Optimal Payment in Arrears.” Financial Cryptography and Data Security: Proceedings of the International Conference (September 2009). (Springer-Verlag Lecture Notes in Computer Science.) (Featured in Working Knowledge: Reducing Risk with Online Advertising.)

Online advertisers face substantial difficulty in selecting and supervising small advertising partners. Fraud can be well hidden, and limited reputation systems reduce accountability. But partners are not paid until after their work is complete, and advertisers can extend this delay both to improve detection of improper partner practices and to punish partners who turn out to be rule-breakers. I capture these relationships in a screening model with delayed payments and probabilistic delayed observation of agents’ types. I derive conditions in which an advertising principal can set its payment delay to deter rogue agents and to attract solely or primarily good-type agents. Through the savings from excluding rogue agents, the principal can increase its profits while offering increased payments to good-type agents. I estimate that a leading affiliate network could have invoked an optimal payment delay to eliminate 71% of fraud without decreasing profit.