Digital Economy

The U.S. Bureau of Economic Analysis (BEA) produces economic statistics through its system of satellite accounts that highlight specialized areas of the economy that are not directly apparent in BEA’s official economic statistics published under the North American Industry Classification System (NAICS), such as outdoor recreation and arts and culture. BEA recently developed a Digital Economy Satellite Account (DESA) to better understand this area of the economy as it involves production that spans multiple NAICS industries, ranging from computer manufacturing to internet-based retail trade (e-commerce) to software production. Currently, BEA’s digital economy statistics do not fully capture production of digital intermediary services earned from operating a digital platform that facilitates the direct interaction between multiple buyers and multiple sellers for a fee (such as rideshare), resulting in an incomplete picture of the digital economy. In this paper, we discuss options for measuring digital intermediary services across selected industries of interest to other international statistical agencies as well as BEA: rideshare, travel services, and food/grocery delivery services. We also provide experimental estimates of gross output for these services that cover 2018–2021 using two approaches. We find that digital intermediation services for rideshare, travel services, and food/grocery delivery services represented at least $31 billion in 2021 gross output, or close to 1 percent of the overall value of the digital economy based on the latest DESA statistics.

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.

Brick and mortar retailers spent $484 billion providing “free” shopping experiences in 2016. For example, vehicle dealerships provide “free” test drives, book stores provide “free” book signings and grocery stores provide “free” food samples. To capture the value of “free” shopping experiences, the paper models them as an implicit barter transaction of shopping experiences for sales attention. The paper then modifies previously created productivity accounts for the wholesale and retail sector (Jorgenson, Ho and Samuels 2016) to include shopping experiences as a new industry output and sales attention as a new industry input.

Despite the rise of e-commerce, “free” brick and mortar shopping experiences grew faster than overall retail margins after 2002. Furthermore, brick and mortar stores have dramatically increased service speed since 2002. Between 2002 and 2014, better shopping experiences contributed $110 billion to real industry output growth and faster service speed subtracted $78 billion from real industry input growth. Furthermore, slower service speed between 1947 and 2002 increases real industry input growth and decreases productivity growth for that time period. Combining all these modifications together, the post-2002 wholesale and retail productivity slowdown shrinks from 0.98 percentage points per year to only 0.08 percentage points per year.

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.

Digitally-enabled services are those for which digital information and communications technologies (ICT) play an important role in facilitating cross-border trade in services. Improvements in ICT technologies and reductions in their costs could be expected to contribute to growth in trade in services. BEA’s statistics on trade in services can be used to examine trends in exports and imports of services whose trade is enabled by digital technologies.