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Mandated data sharing in data-driven markets

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.

Data Science for Institutional and Organizational Economics

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.

The essay can be accessed here.

“Religion, Moral Attitudes & Economic Behavior” in JEBO

Do religious people hold different moral views than non-religious people? Given that a good part of religious teachings are ethical, we could think so. But where exactly are the differences between Catholics, Protestants, and other believers—and non-religious people? And, more importantly for policy insights, are there significant differences not only in views but also in economically relevant actions across denominations or even between clearly identifiable groups within one congregation?

“Religion, Moral Attitudes & Economic Behavior” (joint with Isadora Kirchmaier and Stefan Trautmann) studies and answers such questions empirically, based on a representative survey of the Dutch population and an experimental game with monetary payoffs played with the survey respondents. The paper is now forthcoming in the Journal of Economic Behavior & Organization. Its background and some details are here. The final working paper version is here.


Policy Impact of “Competing with Big Data”

One year ago, Christoph Schottmüller and I put out “Competing with Big Data,” a theory-paper offering a definition and analysis of “data-driven markets”—and a policy proposal to overcome the main problem, market tipping. Based on the idea of an earlier paper (Argenton and Prüfer, 2012), we studied the consequences of a (currently fictive) regulatory requirement for dominant firms in data-driven markets (think of search engines, many digital platform markets, self-driving cars, etc.) to share their data on user preferences and characteristics with each other. We showed that such a policy intervention can mitigate the strong tendency of data-driven markets towards monopolization and that in most relevant cases the net welfare effects would be highly positive.

Since then, this paper—and especially the policy proposal—has been discussed widely both in academic and in policy circles. In January 2018, the Secretary General of the Dutch Ministry of Economic Affairs adopted our view on data sharing (Camps, 2018, p.3):

“one can think of data used for search engine optimisation, such as users’ clickstream following certain search queries. By increasing access to such anonymised clickstream data, other parties in different markets can use them for further innovation. At the same time, a strong concentration of large internet companies on these markets can be avoided (Prüfer and Schottmüller, 2017). One can think of the markets for digital maps, retail and, in the future, autonomous cars.”

Similarly, in his latest book, Viktor Mayer-Schönberger, who co-authored a highly successful book on the economic and social consequences of big data, attributes :

“Rather than algorithmic transparency, regulators wanting to ensure competitive markets should mandate the sharing of data. To this end, economists Jens Prüfer and Christoph Schottmüller offer an intriguing idea.  They suggest that large players using feedback data must share such data (stripped of obvious personal identifiers, and stringently ensuring that privacy is not being unduly compromised) with their competitors. Calculating the effect of such mandated data sharing over a wide spectrum of scenarios, they see an overall net benefit in most cases, especially when one incumbent is close to dominating a market. Building on this idea, we suggest what we term a progressive data-sharing mandate.” (Mayer-Schönberger and Ramge, 2018, p.167)

So, for now we keep the watch from the ivory tower and view to which extent these influential multiplicators may help policy implementation. And we are thinking about an empirical validation of several data-driven sectors …

SIOE 2018: Call for Papers

The Society for Institutional and Organizational Economics (SIOE) just publicized the call for papers for the SIOE 2018 conference, which will be held at HEC Montreal, Canada, on June 21-23, 2018. Keynote lectures will be given by Naomi Lamoreaux (Yale) and Nobel Laureate Jean Tirole (Toulouse), representing nicely SIOE’s two intellectual pillars, institutions and organizations.

The exquisite Program Committee, chaired by President-Elect Francine Lafontaine (Michigan), invites you to submit your proposal to present a paper at the conference. Paper proposals are due by February 5th, 2018.

Job Opening: Postdoc on Economic Governance of Data-driven Markets

The Tilburg Law and Economics Center (TILEC) advertises a position for a Postdoctoral Researcher on the Economic Governance of Data-driven Markets (starting date: September 2018). This is a three-year position targeted at promising researchers in economics or related fields who work on the effects of digitalization and datafication on institutions, including markets, legal and political institutions. We are looking for a researcher who combines expertise in the quantitative techniques of modern economics with an interest both in technologies currently transforming our societies, industries, polities, and jurisdictions and with a sincere openness to interdisciplinary research approaches from other social sciences. Within this field, all types of research interests are welcome, with a slight preference for researchers performing empirical work.

TILEC also advertises another Postdoc Position, on the Economics of Innovation. This is a two-year position targeted at promising researchers in economics or related fields who work on the Economics of Innovation. Within this field, all types of research interests are welcome but preference will be given to researchers performing empirical work and/or working on standardization and standard-setting.

Details on the jobs and the application procedure are available via EconJobMarket. 

“Faithful Strategies: How Religion Shapes Nonprofit Management” to be published in Management Science

Nonprofit organizations, religious values, and a complete dataset on strategic choices of German hospitals: these are the main ingredients into a paper co-authored with my colleague Lapo Filistrucchi, which is forthcoming in Management Science.

This paper makes three key contributions. First, it confirms that the values and beliefs of organizational decision makers, as required by their employers, influence the strategic actions of firms. This study is the first to show that this premise of some behavioral scholars also holds for nonprofits.

Second, this paper is among the first to investigate the strategic effects of decision makers’ religious values. Thereby, as Laurence Iannacone told me recently, we are the first to show that the content of religious teachings actually influence firms’ strategies in a coherent and, thereby, predictable way: roughly speaking, we propose that, because Catholicism is more communal and because Protestantism is more individualistic (and education-oriented), Catholic hospitals are larger, make more revenues, and serve more medical fields, whereas Protestant hospitals are smaller, focus on a few medical fields, specialize in more complex (and more expensive) treatments, and have more links to universities.

Third, we have tackled the difficulties of the empirical and theoretical literatures on nonprofits to predict their strategic choices by fleshing out lines of distinction between different nonprofit subgroups that are distinguishable according to observable organizational characteristics (here: whether a given organization is Catholic or Protestant or neither of the two).

Earlier press coverage related to the paper: