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In This Forum

Data-Driven Economy: Challenges and Opportunities

The transformation of data into an independent and strategic asset poses challenges for companies, regulators and policymakers alike. On 17 June 2019 in Berlin, together with the German Economic Institute (IW), Intereconomics hosted a conference on the “Data-Driven Economy” to reflect on the challenges and opportunities of competition policy, business models and data governance.

In order to guide the data-driven economy to benefit the greater good, regulators and policymakers will have to refine an often inefficient legal and regulatory framework. Justus Haucap opened the event with a look at direct and indirect network effects and the challenges they pose for regulators with regards to competition and competition policy for platform markets. On the business side, Markus Spiekermann looked at tools such as marketplaces to utilise and monetise data.

During the conference as well as here in this issue, Barbara Engels, Bruno Carballa Smichowski and Max von Grafenstein discuss their perspectives on – and varying models of – data governance. From the role data governance plays as an enabler of the data economy to its role in enhancing innovation and welfare, our discussants clearly showed that there is no “one-size-fits-all” model of this concept. Looking at data governance from a management as well as a societal perspective, participants defined its terminology and provided examples of its application.

As we prepared to send this issue to print, we conducted final reviews with our authors who were on planes, trains and on top of mountains. To everyone heading out on summer holidays, we wish you a relaxing vacation and may we recommend taking the latest issue of Intereconomics with you to the beach or wherever you may be heading – it makes excellent summer reading. ;-)

International Monetary System

Two Views of the International Monetary System

Barry Eichengreen breaks down the two schools of thought on the future of the international monetary system, named after two top schools: Harvard University and the University of California Berkeley. The 'Harvard view', states that there is a striking degree of persistence in the structure of the system, which is dollar-based and U.S. led to a large extent. Whereas the 'Berkeley view' believes that the system is evolving away from the US and the dollar, toward a multipolar world in which several consequential international and reserve currencies will coexist, other countries will no longer rely exclusively or even mainly on the U.S. for international liquidity and governance will be a collective endeavor. Find out which view he espouses in this article. Spoiler alert: Eichengreen is a Berkeley professor.

Quote of the Month

Data Governance: Enhancing Innovation and Protecting Against Its Risks

"Big Data is expected to unleash data-driven innovation, which is supposed to better address and solve challenges in our society."

from Max von Grafenstein, Alina Wernick and Christopher Olk's Forum article Data Governance: Enhancing Innovation and Protecting Against Its Risks

Figure of the Month

Definition and implementation of data governance

This figure from Barbara Engels' forum article Data Governance as the Enabler of the Data Economy shows the definition and implementation of data governance in companies that store at least a small amount of data.

Competition Policy

Competition and Competition Policy in a Data-Driven Economy

How has the digital economy changed value chains and competitive processes in many industries and markets? Justus Haucap explains the importance of digital platforms and the essential nature of data across so many industries. And while data has been referred to as the 'new oil' of this century, he jokes that although both data and oil may be extracted via platforms, they are still different in that data is non-rival in use and it is not only non-exhaustible, but growing. These differences have substantial consequences for competiton policy and Haucap lays them out in this article.

Big Data

Access to Data Will Change the World Power Structure

Access to data - not Artificial Intelligence - and countries' management of that data will determine the future world power structure, says data scientist Lutz Finger. As data usage is a societal decision, different countries will have different regulations regarding data and how to use predictions made from it. For example, in Europe, car insurance companies may not use gender as a data point whereas this data is permissable in the US. While Europe has established its signature legislation on privacy, General Data Protection Regulation (GDPR), the Chinese government's relative lack of regulation and the behavioral information they are able to collect may give them a competitive edge.