1. The 2018 Revealed-Preferences Ranking of Law Schools by CJ Ryan (Vanderbilt University, Peabody College) and Brian L. Frye (University of Kentucky – College of Law)

In 2017, we published A Revealed-Preferences Ranking of Law Schools, which presented the first (intentionally) subjective ranking of law schools. Essentially, our ranking asks where students choose to matriculate by ranking law schools according to the combined LSAT scores and undergraduate GPAs of their 2011-16 matriculants. Other law school rankings are objective because their purpose is to tell prospective law students where to matriculate. Our “revealed-preferences” ranking is subjective because its purpose is to ask where prospective law students choose to matriculate. In other words, objective rankings tell students what they should want, but our subjective ranking asks what students actually want.

Our revealed-preferences ranking of law schools received a considerable amount of attention. It was featured in articles published by Above the Law, The Volokh Conspiracy, Scholastica, and FindLaw, among others, and was downloaded almost 8000 times. Accordingly, we created this updated ranking based on the combined LSAT scores and undergraduate GPAs of 2017 law schools matriculants. It provides additional information about student choices, and bolsters our previous conclusion that objective ranking systems fail to consider at least some factors that are salient to prospective law students. In particular, we note that some prospective law students appear to prefer law schools with a strong religious identity or ideological affiliation. Presumably, other factors are also salient to prospective law students and account for the divergence between the advice provided by objective rankings and the choices that matriculating students actually make. – CJ Ryan & Brian L. Frye

2. Market Risk Premium and Risk-Free Rate used for 59 countries in 2018: a survey by Pablo Fernandez (University of Navarra – IESE Business School) and Vitaly Pershin (University of Navarra – IESE Business School) and Isabel Fernández Acín (University of Navarra – University of Navarra, Students)

3. Asymmetric Information and Entrepreneurship by Deepak Hegde (New York University (NYU) – Leonard N. Stern School of Business) and Justin Tumlinson (Loughborough University)

We were inspired by an apparent paradox: the academic literature on entrepreneurs largely describes them as “misfits” who can’t find, can’t stand, or can’t stay in, conventional employment.  And yet, history and the popular press portray entrepreneurs as highly productive self-made visionaries, rejected by employers who could not discern their exceptional talents.  But are these anecdotes merely a biased sample of successful entrepreneurs? We wanted to dig deeper into why individuals become entrepreneurs and what makes some successful.

In this paper, we formally derive and empirically confirm that asymmetric information about worker ability can drive anyone, who believes her productive capabilities to be greater than employers can perceive, to become an entrepreneur.  This explanation holds over a spectrum of entrepreneurs: from immigrant food vendors (whose foreign credentials often go unrecognized) to college dropout technology moguls. Identifying this novel driver of entrepreneurial choice also moves us a step toward cracking the entrepreneurial earnings puzzle. Why individuals choose entrepreneurship likely influences their income—those choosing it for non-pecuniary benefits may reasonably earn less than employees, while those strategically responding to asymmetric information in the labor market about their ability, should earn more. – Deepak Hegde and Justin Tumlinson

4. Some Simple Economics of the Blockchain by Christian Catalini (Massachusetts Institute of Technology (MIT) – Sloan School of Management) and Joshua S. Gans (University of Toronto – Rotman School of Management)

The paper relies on economic theory to surface two key costs affected by blockchain technology: the cost of verification of transaction attributes, and the cost of bootstrapping and operating a digital marketplace without the need for a traditional intermediary. When combined with a native token (as in Bitcoin and Ethereum), a blockchain allows a decentralized network of economic agents to agree, at regular intervals, about the true state of shared data.

This shared data can represent exchanges of currency, intellectual property, equity, information or other types of contracts and digital assets – making blockchain a general purpose technology that can be used to trade scarce, digital property rights and create novel types of digital platforms. The resulting marketplaces are characterized by increased competition, lower barriers to entry and innovation, lower privacy and censorship risk, and allow participants within the same ecosystem to make investments to support and operate shared infrastructure without assigning market power to a platform operator. – Christian Catalini

5. A Brief Introduction to the Basics of Game Theory by Matthew O. Jackson ( Stanford University – Department of Economics)