Call for Papers: Developing a Benefit-Cost Framework for Data Policy


The Program on Economics & Privacy at George Mason University’s Antonin Scalia Law School and the Future of Privacy Forum are seeking papers to explore the development of a benefit-cost framework in privacy policy. Scholars from an interdisciplinary background, including economics, law, public policy, business and marketing, are encouraged to submit abstracts for consideration.

Selected submissions will be presented at the Fifth Annual Public Policy Symposium on the Law & Economics of Privacy and Data Security Policy, on June 8, 2017, at the Antonin Scalia Law School, and published in a special symposium issue of the Journal of Law, Economics & Policy.


To be considered, please send an abstract outlining your proposed paper to [email protected] by April 15, 2017. Selections will be announced by May 1, 2017. Selected authors will be expected to have completed a discussion draft by June 1, 2017, to circulate to conference participants. Final papers will be due on September 1, 2017.

Topics of special interest include:

  • Developing metrics to measure the costs and impacts of privacy controls.
  • Unpacking the economics of privacy using microeconomic tools.
  • Calculating the value of privacy for consumers through analysis of competitive offerings.
  • Benefit-cost analysis of innovative data uses.
  • Understanding the concept of cognizable privacy harm constituting substantial injury under Section 5 of the FTC Act.
  • Measuring consumer reactions to changes in tracking.
  • Understanding the value of anonymity and pseudonymity in online interactions.
  • Weighing the benefits of data use to individuals, organizations, communities and society at large.
  • Assessing the possibility of market failures in privacy—to what extent will the market fail to produce the “correct” amount of privacy?
  • What are the roles of neoclassical and behavioral economics in explaining consumers’ relative unresponsiveness to privacy policies or the limited role for privacy as a dimension of competition?
  • Are there impediments to the development of privacy offerings that play a larger role in competition among firms and platforms?
  • What are the economic implications of privacy issues raised by artificial intelligence and machine learning?