Policymakers, scholars, business leaders, and ordinary citizens are all grappling with the far-reaching implications of digital technology, and economists are no exception. In fact, more than most other academic fields, economics urgently needs to revise its assumptions to make sense of the current era.
CAMBRIDGE – Just within the past few decades, digital technology has transformed the global economy and societies worldwide multiple times. In the 1980s, the automation of manufacturing produced waves of outsourcing and offshoring. In 1989, computer scientist Tim Berners-Lee invented the World Wide Web, and beginning around 2007, a confluence of smartphones, 3G/4G, and new algorithms brought much of the world’s population online, where we have been living ever since.
With the new technologies have come global production chains, e-commerce, social media, and the platform economy. And owing to advances in artificial intelligence, genomics, additive manufacturing, the green transition, and advanced materials, an even broader transformation is still on the horizon. During such periods of change, there are always more questions than answers for policymakers and academics alike. Each wave of digital disruption raises new problems for economists, in particular.
Some of these problems are well known, particularly the perceived threat to jobs – an area where David Autor of MIT and the University of Oxford’s Carl Benedikt Frey, among others, have already contributed significant scholarlywork. Yet many other issues still need to be addressed. One is economic measurement. Standard definitions and data-gathering processes do not go far enough in capturing digital activities such as cloud computing and contract manufacturing.
The latest technologies raise other difficult conceptual questions as well, such as how best to account for new or higher-quality goods and services in price indices, and how to value intangible assets like data. Without more progress toward resolving these issues, economic policymakers will be flying blind.
The issue of data, in particular, poses a pressing policy challenge. Everybody recognizes the importance of data: the daily volume of digital information being transmitted is soaring, businesses are hoarding data as a source of competitive advantage, and the risks and costs of data breaches are increasingly apparent.
Yet there is scant data on data, including how it flows across national borders and between data centers. It is unclear how the value of data should be determined. As something that defies traditional metrics such as quantity and price, data is unlike any other standard economic good. Electronic ones and zeroes have a physical basis, but a bit of data is both a record of something and an economic unit of volume, the value of which depends on the informational context.
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Economic research and analysis of data – like debates about the appropriate regulatory framework – are still in their early days. But policymakers are eager for insights. Recent major studies of competition in digital markets in the UK, Germany, Australia, and the European Union have found that major tech firms’ vast troves of data are acting as powerful entry barriers. With tougher competition enforcement and new regulation becoming more likely across many jurisdictions, there is a growing need for more research into these dynamics.
The problems surrounding data illustrate the broader challenge facing economists today. The digital economy features massive spillovers and externalities, some of which stem from a single choice made by a single person in a single firm. Externalities are an old problem, but the scale and scope of spillovers in the digital economy are something new.
In the case of data, much of the debate has focused on the (potential) loss of privacy, a negative externality resulting from companies’ pursuit of information with which to improve marketing and other business functions. But equally important is the potential for big data to improve social welfare, not just corporate profits. Information provided by many individuals, for example, could be used to improve traffic conditions or medical research.
Another major feature of the digital economy is the network effect, whereby the value of a service increases exponentially with the growth of its user base. The more people there are using a particular search engine, the better that search engine will become at interpreting human-generated search terms and returning the most relevant information. Digital platforms also create indirect network effects when users on one side of the platform (holidaymakers, say) benefit from more suppliers joining the other side (apartment owners).
But owing to network effects, digital markets tend to follow a winner-takes-all (or most) dynamic, which is why just one or two large firms now dominate them. Here, too, economists need to improve their understanding of why some platforms succeed where others fail. For example, it is unclear at what point the network effect kicks in, tipping a market decisively in a particular direction, or the extent to which network effects are the result rather than the cause of market power. Without knowing, it will be much harder for policymakers to strike the right balance between ensuring competition and enabling value creation in digital markets.
Yet another distinction of the digital economy is the scope of increasing returns to scale. Again, this basic dynamic is not new: operating a steel mill or a power plant involves very high up-front fixed costs, and far lower marginal costs once production gets off the ground. But in the digital economy, increasing marginal returns are everywhere. While software can be costly to write, it costs nothing to reproduce and distribute.
And even for services where economies of scale and scope cannot operate, such as haircuts or dining out, digital platforms can still tap into the network effect. Whereas a restaurant can accommodate only a certain number of diners per hour, a platform that matches restaurants with diners can enjoy vast economies of scope.
These dynamics pose a significant challenge to mainstream economics in two ways. First, the standard models for measuring productivity and other indicators assume diminishing or constant returns to scale, which leads to misinterpretations when analyzing non-linear systems. Generally speaking, economists (with some honorableexceptions) have been too slow in accounting for tipping points, multiple equilibria, and other alternative possibilities.
Second, standard assessments of economic-policy interventions assume an absence of increasing returns or spillover effects. When these appear, they are classified as “market failures.” Meanwhile, the benchmark assumption that market forces will always produce the best outcome remains unchallenged. But when an entire economy displays “market failures,” that should prompt economists to rethink their policy recommendations.
With research and analysis ongoing in all the areas mentioned above, the next few years will be an exciting time for economists, especially younger scholars venturing into the under-explored territory of the digital economy. Technology notoriously moves faster than politics and regulation, but after four decades of digital upheaval, policymakers are catching up. Economists’ task is to ensure that policy interventions do more good than harm. In an age of techlash, meeting that challenge could not be more urgent.
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CAMBRIDGE – Just within the past few decades, digital technology has transformed the global economy and societies worldwide multiple times. In the 1980s, the automation of manufacturing produced waves of outsourcing and offshoring. In 1989, computer scientist Tim Berners-Lee invented the World Wide Web, and beginning around 2007, a confluence of smartphones, 3G/4G, and new algorithms brought much of the world’s population online, where we have been living ever since.
With the new technologies have come global production chains, e-commerce, social media, and the platform economy. And owing to advances in artificial intelligence, genomics, additive manufacturing, the green transition, and advanced materials, an even broader transformation is still on the horizon. During such periods of change, there are always more questions than answers for policymakers and academics alike. Each wave of digital disruption raises new problems for economists, in particular.
Some of these problems are well known, particularly the perceived threat to jobs – an area where David Autor of MIT and the University of Oxford’s Carl Benedikt Frey, among others, have already contributed significant scholarly work. Yet many other issues still need to be addressed. One is economic measurement. Standard definitions and data-gathering processes do not go far enough in capturing digital activities such as cloud computing and contract manufacturing.
The latest technologies raise other difficult conceptual questions as well, such as how best to account for new or higher-quality goods and services in price indices, and how to value intangible assets like data. Without more progress toward resolving these issues, economic policymakers will be flying blind.
The issue of data, in particular, poses a pressing policy challenge. Everybody recognizes the importance of data: the daily volume of digital information being transmitted is soaring, businesses are hoarding data as a source of competitive advantage, and the risks and costs of data breaches are increasingly apparent.
Yet there is scant data on data, including how it flows across national borders and between data centers. It is unclear how the value of data should be determined. As something that defies traditional metrics such as quantity and price, data is unlike any other standard economic good. Electronic ones and zeroes have a physical basis, but a bit of data is both a record of something and an economic unit of volume, the value of which depends on the informational context.
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At a time of escalating global turmoil, there is an urgent need for incisive, informed analysis of the issues and questions driving the news – just what PS has always provided.
Subscribe to Digital or Digital Plus now to secure your discount.
Subscribe Now
Economic research and analysis of data – like debates about the appropriate regulatory framework – are still in their early days. But policymakers are eager for insights. Recent major studies of competition in digital markets in the UK, Germany, Australia, and the European Union have found that major tech firms’ vast troves of data are acting as powerful entry barriers. With tougher competition enforcement and new regulation becoming more likely across many jurisdictions, there is a growing need for more research into these dynamics.
The problems surrounding data illustrate the broader challenge facing economists today. The digital economy features massive spillovers and externalities, some of which stem from a single choice made by a single person in a single firm. Externalities are an old problem, but the scale and scope of spillovers in the digital economy are something new.
In the case of data, much of the debate has focused on the (potential) loss of privacy, a negative externality resulting from companies’ pursuit of information with which to improve marketing and other business functions. But equally important is the potential for big data to improve social welfare, not just corporate profits. Information provided by many individuals, for example, could be used to improve traffic conditions or medical research.
Another major feature of the digital economy is the network effect, whereby the value of a service increases exponentially with the growth of its user base. The more people there are using a particular search engine, the better that search engine will become at interpreting human-generated search terms and returning the most relevant information. Digital platforms also create indirect network effects when users on one side of the platform (holidaymakers, say) benefit from more suppliers joining the other side (apartment owners).
But owing to network effects, digital markets tend to follow a winner-takes-all (or most) dynamic, which is why just one or two large firms now dominate them. Here, too, economists need to improve their understanding of why some platforms succeed where others fail. For example, it is unclear at what point the network effect kicks in, tipping a market decisively in a particular direction, or the extent to which network effects are the result rather than the cause of market power. Without knowing, it will be much harder for policymakers to strike the right balance between ensuring competition and enabling value creation in digital markets.
Yet another distinction of the digital economy is the scope of increasing returns to scale. Again, this basic dynamic is not new: operating a steel mill or a power plant involves very high up-front fixed costs, and far lower marginal costs once production gets off the ground. But in the digital economy, increasing marginal returns are everywhere. While software can be costly to write, it costs nothing to reproduce and distribute.
And even for services where economies of scale and scope cannot operate, such as haircuts or dining out, digital platforms can still tap into the network effect. Whereas a restaurant can accommodate only a certain number of diners per hour, a platform that matches restaurants with diners can enjoy vast economies of scope.
These dynamics pose a significant challenge to mainstream economics in two ways. First, the standard models for measuring productivity and other indicators assume diminishing or constant returns to scale, which leads to misinterpretations when analyzing non-linear systems. Generally speaking, economists (with some honorable exceptions) have been too slow in accounting for tipping points, multiple equilibria, and other alternative possibilities.
Second, standard assessments of economic-policy interventions assume an absence of increasing returns or spillover effects. When these appear, they are classified as “market failures.” Meanwhile, the benchmark assumption that market forces will always produce the best outcome remains unchallenged. But when an entire economy displays “market failures,” that should prompt economists to rethink their policy recommendations.
With research and analysis ongoing in all the areas mentioned above, the next few years will be an exciting time for economists, especially younger scholars venturing into the under-explored territory of the digital economy. Technology notoriously moves faster than politics and regulation, but after four decades of digital upheaval, policymakers are catching up. Economists’ task is to ensure that policy interventions do more good than harm. In an age of techlash, meeting that challenge could not be more urgent.