Digital Economy

This paper reviews the efforts of the Bureau of Economic Analysis (BEA) to measure international services categorized by mode of supply. BEA has adopted a survey form that uses an innovative approach to collect information on mode of supply by simply having companies report the percentage of its services supplied through one mode as opposed to all modes, with the idea that the other modes can be estimated as a residual or using other data sources. Of the few previous efforts by countries to measure trade by mode of supply, most are based on assumptions about industry practices or on surveys that simply asked for the predominant mode of supply rather than a more precise percentage supplied by mode. BEA also uses a pioneering method to measure services supplied through affiliates across service types by mapping its comprehensive industry-based foreign affiliate statistics to its product-based trade statistics. The estimates also include a breakdown of the mode where consumers obtain the service outside their home territory, such as services received when traveling abroad, that more closely corresponds with guidelines set out in the General Agreement on Trade in Services than most previous efforts.

The Facebook-Cambridge Analytica data scandal demonstrates that there is no such thing as a free lunch in the digital world. Online platform companies exchange “free” digital goods and services for consumer data, reaping potentially significant economic benefits by monetizing data. The proliferation of “free” digital goods and services pose challenges not only to policymakers who generally rely on prices to indicate a good’s value but also to corporate managers and investors who need to know how to value data, a key input of digital goods and services. In this research, we first examine the data activities for seven major types of online platforms based on the underlying business models. We show how online platform companies take steps to create the value of data, and present the data value chain to show the value-added activities involved in each step. We find that online platform companies can vary in the degree of vertical integration in the data value chain, and the variation can determine how they monetize their data and how much economic benefits they can capture. Unlike R&D that may depreciate due to obsolescence, data can produce new values through data fusion, a unique feature that creates unprecedented challenges in measurements. Our initial estimates indicate that data can have enormous value. Online platform companies can capture most benefits of the data, because they create the value of data and because consumers lack knowledge to value their own data. As trends such as 5G and the Internet of Things are accelerating the accumulation speed of data types and volume, the valuation of data will have important policy implications for investment, trade, and growth.