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I'm a law professor at the University of Iowa. My research focuses on:
Antitrust Law
Evidence Law
Law and Economics

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My research merges traditional legal analysis with economics and statistics. I am particularly interested in using game theory, probability theory, and experimental economics as tools of legal analysis. I write on topics in Antitrust Law, Evidence Law, and Law and Economics.

Antitrust Law

My antitrust research focuses on improving the fit between economic theory and competition policy, particularly in the area of competitive inferences drawn from market structure and market definition. While modern antitrust generally does a good job of fusing law and economics, this is one area where that fusion is imperfect and incomplete. The thesis of all my antitrust work is that meaningful societal gains can be unlocked by addressing tensions and omissions in the integration of economics in modern antitrust law.

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An example is The Logic of Market Definition, a paper in which I and a coauthor critique the modern understanding of antitrust market definition. Starting fresh from economic fundamentals, we identify several common fallacies in how market definition is currently understood in antitrust practice. These include a tendency to confuse antitrust markets with lay concepts of industry or competition, a tendency to misunderstand the dependence of market definition on a given theory of anticompetitive harm, and a tendency to overlook the importance of defining different relevant markets for different theories of harm, even within a single case or controversy. In place of these fallacies, our paper proposes an economically valid and internally consistent approach to market definition.

Another example is Anticompetitive Entrenchment, a paper in which I review both policy commentary and recent empirical scholarship to identify gaps in antitrust enforcement relating to highly concentrated markets. I propose to close these gaps by reinvigorating a nearly forgotten channel of merger enforcement: opposition to the anticompetitive entrenchment of already-existing market power. I show how this old concept can be retrofitted to work within the modern economic framework, and I further show how doing so may help to address market concentration and market power problems in a careful and surgical way.

This interest in closing gaps between law and economics in regard to market structure motivated my earlier antitrust work as well. In What Structural Presumption?, I show how the addition of ostensibly innocuous evidentiary formalism in merger analysis has actually dis-placed economic analysis in a critically important aspect of antitrust law. Using concepts from both economics and evidence law, I propose a path forward for remedying this problem and returning mer-ger analysis to an economically appropriate use of available evidence.

The same basic themes also underlie my shorter works. For example, in Lumps in Antitrust Law, I identify an under-appreciated ambiguity in how competition policy addresses the specific market structure of exchange between small numbers of trading partners on both sides of a transaction, and I try to clarify the problems inherent in a simplistic understanding of antitrust objectives. I continue this focus on antitrust objectives in Antitrust Amorphisms, showing how imprecise use of economic terminology has resulted in a competition regime that resists easy explanation and may even be internally inconsistent.

Evidence Law

The thesis of my evidence scholarship is that probability theory can be used to clarify important aspects of legal fact-finding and the rules of evidence. This broad thesis is not itself earth shattering; efforts to leverage probability theory in evidence scholarship date to at least the 1960s. But existing syntheses of evidence law and probability theory are not uniformly persuasive, and there is still a great deal to be learned in this space.

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An illustration of that point is A Likelihood Story, a paper in which I argue that decades of prior efforts to conceptualize fact-finding in terms of Bayesian probability theory have focused on the wrong cognitive model. Instead, this paper argues that fact-finding is better understood in the purely comparative terms of a related but distinct concept of uncertainty: likelihoods. This revised understanding clarifies the common structure of the major burdens of persuasion and could offer concrete improvements in fact-finding if the process was revised to focus attention away from subjective believe and toward more objective concepts like weight of evidence.

In a short follow-on paper, Challenges for Comparative Fact-Finding, I extend the previous argument, contending that to fully unlock the potential of comparative models of fact-finding, like my own, several remaining hurdles need to be addressed. I describe these hurdles in detail in this paper, and plan to return to them in future research.

Another illustration of my interest in fact-finding is Insincere Evidence, a paper in which I and a coauthor employ my work on comparative fact-finding and some basic economics to show how proof costs lead to consistent underdeterence, and how the exaggeration of legal standards may sometimes reduce this underdeterence. Important from an evidentiary perspective, this paper demonstrates a connection between burdens of persuasion and substantive standards that is, if known at all, greatly under-appreciated in the literature on optimal burdens of persuasion.

Beyond fact-finding, I am interested in using probability theory to clarify the operation of the rules of evidence themselves. In one of my older papers, Probative Inference from Phenomenal Coincidence, I use simple numerical models to illustrate errors and imprecisions in common articulations of the lack-of-accident category in Federal Rule of Evidence 404(b)(2) and equivalent state codes. One important contribution of this paper is the invalidation of an important non-character theory of relevance under most rules of evidence.

Law and Economics

My law and economics research is trans-substantive, but unified by a common methodological focus on the use of game theory and experimental economics as tools of legal analysis. My interest in game theory includes both formal and informal applications of game-theoretic modeling.

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An example of how informal game theory can be used to inform legal doctrine is Powers, But How Much Power?, a paper in which I use principal-agent models and other concepts in game theory to pro-pose a novel interpretation of the constitutional nondelegation principle. In brief, I argue that the “power” part of “legislative power” can only be understood in terms of the relationship between Congress and an empowered agent, adding an additional element to prior non-delegation scholarship that may help to reconcile expansive delegations of lawmaking authority with faithful adherence to a serious nondelegation principle.

An example of how formal game theory can be used to better under-stand legal institutions is Why Wait to Settle?, a paper in which I use a large-scale economics experiment to test the popular hypothesis that asymmetric information explains the failure to litigants to settle cases in a timely and efficient manner. The results of my experiment lend qualified support to the asymmetric information hypothesis—showing that informational asymmetries can lead to causal increases in settlement delay, but also showing that much of observed settlement delay may owe to factors other than information asymmetry alone.

Reflecting my broad interest in empirical applications of game theory to legal applications, I was previously asked to coauthor the experimental economics chapter of the Oxford Handbook of Law and Economics. My chapter surveys three primary uses of economics in law: (1) as a tool for studying legal institutions, (2) as a tool for studying legal doctrine, and (3) as a tool for litigators and trial strategists. Across all three categories, I argue that experimental economics represents a powerful tool for advancing legal research and practice.