Effects of data localization on digital trade: An agent-based modeling approach

Abstract

Post the Snowden and Cambridge Analytica episodes, concerns have been raised by governments and regulators on protecting consumer data collected and transmitted by various digital firms. Driven by concerns of privacy, national security, surveillance, and cyber terrorism, governments around the world have been erecting barriers in cyberspace through data localization. The extent of data localization varies from free flow of data, to stringent restrictions requiring all data to be stored only within the territorial jurisdiction of the country. Though there are certain legitimate concerns regarding protection of personal data, scholars and liberal economists have long proclaimed that any restrictions on the Internet and associated digital trade will have serious economic consequences. Data localization affects digital trade between consumers and producers of digital services to varying degrees. In this paper, we use agent based modeling to study the properties and behaviours of consumers and producers under varying data localization regimes. An augmented gravity model of trade with iceberg coefficient is incorporated to reflect distance-related costs between producers and consumers. Varying data localization compliance costs are included to reflect the effect of non-tariff barriers of data restrictions. Our extensive simulations indicate that there is often clustering of consumers around local firms in highly restrictive data localization regimes, thus enabling local firms to effectively compete against global multinationals. However, results also indicate that while free cross-border data flow enables intense competition amongst producers, data localization restrictions often limit consumer choice due to its effect on price and quality of services.