After much anticipation, the Department of Justice Antitrust Division and the Federal Trade Commission released a draft of the Vertical Merger Guidelines (VMGs) on January 10, 2020. The Global Antitrust Institute (GAI) will be submitting formal comments to the agencies regarding the VMGs and this post summarizes our main points.

Read the full piece here.

In a recent article Joe Kattan and Tim Muris (K&M) criticize our article on the predictive power of bargaining models in antitrust, in which we used two recent applications to explore implications for uses of bargaining models in courts and antitrust agencies moving forward.  Like other theoretical models used to predict competitive effects, complex bargaining models require courts and agencies rigorously to test their predictions against data from the real world markets and institutions to which they are being applied.  Where the “real-world evidence,” as Judge Leon described such data in AT&T/Time Warner, is inconsistent with the predictions of a complex bargaining model, then the tribunal should reject the model rather than reality.

Read the full piece here.

In the brave new world contemplated by the advocates of government policies informed by behavioral law and economics, many more aspects of each individual’s life will be regulated, or more stringently regulated, than at present.  Within the legal academy, the growth of the behavioral law and economics movement has been dramatic.  Surveying all legal publications from 1980 through 1984 reveals that only a single article made mention of the phrase “behavioral economics.”  In 2005 through 2009, however, there were 917 such articles.  What, we must ask, accounts for the great and increasing attraction of the subject to legal academics?

Read the full piece here. 

The behavioral economics research agenda is an ambitious one for several reasons.  The first reason is that behavioral economics requires a theory “true” preferences aside from – and in opposition to — the “revealed” preferences of the decision maker.  A second reason is that while collecting and documenting individual biases in an ad hoc fashion can generate interesting results, policy relevance requires an integrative theory of errors that can predict the sufficient and necessary conditions under which cognitive biases will hamper the decision-making of economic agents.  A third is not unique to behavioral economics but is nonetheless significant: demonstrating that behavioral economics improves predictive power.  The core methodological commitment of the behavioral economics enterprise — as with economics generally at least since Friedman (1953) —  is an empirical one: predictive power.  Indeed, no less than  Christine Jolls, Cass Sunstein and Richard Thaler have described the behavioralist research program as the economic analysis of law “with a higher R-squared,” that is, “a greater power to explain the observed data.”

Read the full piece here.