Datafication has massively influenced processes within organizations, on markets, and more generally throughout society. Machine learning pushes the loop between data accumulation and innovation even further. The Tilburg Law and Economics Center (TILEC) and the Governance and Regulation Chair (GovReg) at University Paris-Dauphine | PSL Research University are pleased to announce the 5th Economic Governance workshop, which will take place at Tilburg University, the Netherlands, on June 6-7, 2019.
We now strive to stimulate the debate about the economic, political, legal, and social effects of big data and artificial intelligence. As a case of special focus, algorithm-driven platforms such as social media, search engines, and news aggregators have become dominant players in news dissemination. This has transformed the media sector and the way we think about democratic political elections and the legitimacy of those elections’ outcomes, with yet unknown consequences for our political systems and for many markets that are tipping towards the technological leader.
These developments challenge our rules of the game: are Western institutions, formal and informal, set up appropriately to ensure fair competition among firms, innovators, politicians, or political parties? What does it mean for competition law, privacy and data access laws, international treaties, election commissions’ procedures, and the codes of conduct on online platforms if most of us can be traced and monitored most of the time – but these masses of data can only be accessed, worked with, and potentially be manipulated by a few parties? Are we heading towards a future with virtually unbounded opportunities and progress for humanity – or towards a setting, where the state or large private actors control every aspect of life and the net profits of global technological progress are enjoyed by very few very rich and influential individuals?
The deadline for submissions is January 20, 2019. Details and further information are here.
Cloud computing technologies can increase innovation and economic growth considerably. Empirical studies have shown, however, that many users underutilize cloud technologies because of privacy concerns. Individuals do not fully trust that their personal pictures, for instance, don’t leak if put to the cloud for once. Firms do not trust that their critical business applications run smoothly and that their business secrets are kept safe if stored on servers that can be mirrored or changed over night.
“Trusting Privacy in the Cloud” addresses these concerns. In that paper, which is forthcoming in Information Economics and Policy, I design an institution attenuating the trust problem in cloud computing: a two-layered certification scheme built around a private, nonprofit organization called cloud association. This association is governed by representatives of both users and cloud service providers and sources auditing and certification of providers out to independent for-profit certifiers. It is shown how this institution incentivizes providers to produce high data security, and users with strong privacy preferences to trust them and pay a premium for their services. The theoretical proposed mechanism is compared with procedures in an existing organization. Suggestions for how to improve the existing one are made.
For the Beste Studies 2018 survey, weekly newspaper Elsevier has compared 2,181 programs in Dutch higher education (research universities and universities of applied sciences). The Beste Studies ranking is largely based on assessments by students of their program in the National Student Survey (NSE 2018). These assessments were supplemented with practical information, such as student population and academic success rates.
The MSc Economics at Tilburg University, which I am involved in, came out on top of all MSc Economics programs in the country this year.
|Rank||University||Score (satisfaction %)|
Vrije Universiteit Amsterdam
|3||University of Groningen||71|
|7||University of Amsterdam||61|
|* Erasmus University’s program is accredited as Economics and Business, therefore it is officially not a part of this ranking.|
This result is especially satisfying because last year our score was 69. It is good to read that the combination of a high-quality program with a very international classroom (and heterogeneous student experiences) and a distinct customer/student-orientation are acknowledged.
Now, back to work …
A team of researchers at TILEC, the Tilburg Law and Economics Center, has submitted a contribution responding to a call issued by the European Commission’s Directorate-General for Competition (DG COMP) on on “Shaping competition policy in the era of digitization.” The call elicits contributions from interested stakeholders that can inform the discussion at a conference DG COMP organizes in January of 2019.
According to DG COMP, the conference is “designed to provide input to the Commission’s ongoing reflection process about how competition policy can best serve European consumers in a fast-changing world. The conference may also help to identify problems and solutions as markets go through rapid changes. The objective is to identify the key upcoming digital challenges and their implications for competition policy.”
TILEC’s contribution revolves around the three panels that will be featured at the conference: (1) competition, data, privacy and AI, (2) digital platforms’ market power, (3) preserving digital innovation through competition policy. It summarizes recent research undertaken by TILEC researchers in these fields and derives implications for competition policy.
Lisa Bernstein (Chicago Law School), together with a formidable set of other scholars, organizes a fascinating meeting next week, where the ins and outs of relational contracting and transacting in the shadow of the law will be discussed. Promises, rules, social norms, property rights, productivity, and incentive contracts combine a range of topics relevant for relationships where the future matters. The program is populated by exquisite legal scholars, economists, and political scientists. For a glimpse, click here!
My recent work with Cedric Argenton and Christoph Schottmueller on competition in data-driven markets had some policy impact (details here). The key proposal we put forward and analyzed in those theory papers was to require competitors in data-driven markets to share their user information – data about the preferences and characteristics of users gained as a virtually free byproduct of offering certain services, e.g. search engines or online platforms.
Now ESB, a Dutch economic policy outlet, published an entire special issue on such mandated data sharing. Naturally, authors from different backgrounds disagree about the right measures to prevent monopolization of markets. Together with legal scholar Inge Graef, a colleague at the Tilburg Law and Economics Center (TILEC), I explain the original reasoning in a nutshell and discuss policy implementation options, both from a legal and an economic perspective. Our 4-page essay, a bit sensationally called “Mandated data sharing is a necessity in specific sectors,” is here. Financieele Dagblad, a Dutch (language) daily newspaper, wrote about it here.
Is it possible to elicit the ideological positions of voters by having information about the structure of their social media networks? Can we make predictions about upcoming policy changes by analyzing the speeches of statesmen, although they could be considered cheap talk? Is there a way to analyze all court decisions of a jurisdiction in order to identify individual biases of judges, thereby suggesting a way how to make the legal system more impartial? Or can we develop a reliable index of organized crime and subversion in industrial areas, typical hotbeds of such crimes, taking into account a wide range of Internet, social media and administrative data sources? These questions are within the domain of Institutional and Organizational Economics (IOE). And all of them could not be seriously studied, let alone answered, by traditional empirical methods. Data science, a new toolkit combining statistics with computer science, is changing this.
Together with Patricia Prüfer, I have written a brief introductory essay that will be published in a handbook, “A Research Agenda for New Institutional Economics,” edited by Claude Menard and Mary Shirley. We describe the most prominent data science techniques that lend themselves to analyses of the governance structures of institutions and organizations. Several examples using data science to analyze legal, political, and social institutions are introduced. Then we sketch how specific data science techniques can be used to study important research questions that could not (to the same extent) be studied without these techniques. We conclude by comparing the main strengths and limitations of computational social science with traditional empirical research methods and its relation to theory. All this is amended by links to literature and Internet resources and to the most relevant text mining tools and download sources, showing how to get started with data science methods independently.