How do we capture the digital economy in statistics?
By some estimates, the digital economy now accounts for trillions of dollars. But policymakers and companies still lack the data needed to fully understand it.
The pursuit of greater efficiency, driven by the rapid ascent of internet use and accessibility, technological breakthroughs and advances, and more complex consumer demand, has pushed society into the age of digitalization. Estimates of the global digital economy range between 4.5% to 15.5% of world GDP, with digitally deliverable service exports amounting to $2.9 trillion, according to a report by UNCTAD.
The impacts of digitalization have permeated industries beyond the information and communications technology sector, with tangible effects to financial services, retail, transportation, hotels and restaurants, among many others. As technology and internet accessibility continue to improve, such trends are expected to persist. Though the digital economy has certainly been evident and increasingly important in daily activities, defining and measuring it still pose key challenges to institutions worldwide.
There is a general consensus in the literature about the importance of quantifying income derived from and the sectoral effects of digitalization. However, there are still some methodological challenges due to complexities presented by the subject matter. First, the lines separating the traditional economy from the digital economy are starting to blur - firms across various sectors adapt new and more advanced ways of conducting business to keep up with the changing of the times while consumers use different platforms to make more informed decisions.
Second, some authors argue that the value-added of digitalization is prone to measurement error due to the difficulty of tracking digital transactions. Since the digital economy measures how digitized knowledge and information are used as inputs to production, then the use of data as an intermediate, together with its value-added to production, must be properly documented. This becomes particularly problematic when digitally produced goods (e.g., online advertisements) appear and are viewed in different platforms before convincing an economic agent to purchase another good.
Third, from a welfare perspective, improvements in price transparency caused by digitalization should also be quantified to arrive at more comprehensive analyses in consumer surplus. This kind of data, however, is not readily available and is open to subjectivity, which can lead to more questionable estimates of value.
Realizing this, institutions such as the Asian Development Bank have started developing nuanced and more holistic measures of the digital economy within GDP statistics.
The first two challenges may be addressed by establishing a solid definition and classification system for what constitutes the digital economy. Goods and services that fall under certain criteria may be considered as digital, and delineated within more specific product groupings, and separately from non-digital counterparts. This should not be limited to their inputs and production processes, but also include an assessment of how they are transacted.
After the establishment of a concrete categorization, it is essential to properly reflect these transactions in the supply and use tables. Capturing the actual value and movement of products is key to obtain the resulting figures used to compute the digital GDP. Complexities such as approximating “partially digital” products, isolating digital intermediary costs, or considering analog inputs to digital products in the digital economy, must first be resolved, by going back to the definitions.
The third challenge behooves us to look further than interfaces as the face value of many digital products. Social media, streaming sites, and other free or low-priced products may only appear to have a large consumer surplus from the perspective of retail price. However, looking at other stages in the value chain may reveal and explain the actual revenue flows (e.g. consumer data used for advertising revenues, consumer spending on internet to access social media). Only in perfectly understanding these types of scenarios can we accurately translate them into reliable statistics.
While a myriad of indicators can be analyzed in the context of the digital economy, the foremost challenge will be in obtaining accurate figures necessary to the study, especially when dealing with developing countries. Data will certainly be incomplete for many countries, with only a few statistics offices conducting surveys with the necessary information to delineate digital from non-digital output.
While improving collection and enforcement methods is the best solution, evidence-based estimation techniques may be the next best thing. Multiple approaches such as the use of industry digitization indices, or extrapolation from specialized or related information sources, may be explored and tested, as long as these are bound by reasonable assumptions and ascertained by logical and statistically sound frameworks.
Given the all-encompassing, considerable impacts of the digital economy, properly quantifying these will result in valuable information to all economic units. Firms use information about costs related to investment in and production of digital technologies as well as expected revenues in order to come up with profit-maximizing decisions. Governments, on the other hand, need the most accurate information about digitalization to minimize rents involved in the procurement and/or regulation of digital technologies (e.g., broadband service providers) as well as in estimating contributions of particular sectors to pertinent macroeconomic indicators.
Households or individuals can make better-informed spending decisions based on varying levels of consumer surplus, as well as face potential welfare gain from more cost-effective public investment.
Putting all of these together, economies that have measured the digital economy will be more equipped to grow and develop over the long term.