The dramatic rise of the digital economy presents unique challenges to the bean counters who try to measure the size of national economies.
The standard measures of economic output used by statisticians were originally designed at a time when most economic activity was about the production of standard stuff such as wheat or steel. Are these statistical tools adequate to capture the complexity, dynamism and technological churn of the 21st-century economy? And what about the growing use of modern barter or peer-to-peer deals in what has been described as the sharing economy?
Let us begin with an example a lot of people will easily identify with. You have been traditionally booking airline tickets for your annual family holiday through a travel agent. Now, airline sites allow you to book those tickets on your own. The effect is the same, but what used to once be a market transaction that involved payment to a travel agent has now become a household activity for which no money is paid. National income has actually declined even though the underlying transaction is the same: the purchase of a ticket.
Now, let us shift our attention to mobile phones. You have decided to eventually replace your old clunky phone with a new-generation gizmo that allows you to do much more at the same price. What economic statisticians capture in their data is the number of mobile phones sold as well as their price.
There is still little clarity on how to deal with the rapid improvements in the quality of the digital products we use, though there has been some advance in the creation of hedonic price data that captures changes in quality. A phone that can only make calls is quite different in terms of human welfare with a phone you can use to do banking transactions.
And then there is the very unique way digital products are priced. They have high fixed costs but zero marginal costs. Now, what does that mean? A software company spends big bucks to write its code. It then can replicate this code at zero cost. Or think about a new-age music band that can distribute its new album at minimal cost over the Internet despite the initial high costs of recording.
The prices of many digital products tend to fall to zero because of their unique economics. Many business models are designed to create other revenue streams such as advertising since the main product is given away free to build a large customer base. There is again not much agreement on how to capture these changes in national accounts.
These examples have been adapted from a new report by a committee headed by Charles Bean, a professor at the London School of Economics and a former deputy governor of the Bank of England. The committee was set up by the UK government in July 2015 to review the current state of economic statistics.
The challenges from the digital economy identified by the Bean committee are part of a wider examination of economic statistics. Across the Atlantic, the US is also struggling with similar dilemmas. As Charles Hulton of the National Bureau of Economic Research says in a recent paper: “The rapid transformation of the US economy brought about by the revolution in information technology has introduced a profusion of new products and processes, new market channels, and greater organizational complexity. Parts of the statistical system are struggling to keep up. The problem is nowhere more evident than in the difficulties associated with the Internet’s contribution to GDP. Valuing the Net and the wide range of applications offered with little or no direct charge is challenging because there is no reliable monetary yardstick to guide measurement, and their omission or undervaluation surely affects GDP.”
GDP (gross domestic product) is the cornerstone of all national economic statistics. It measures how much output is produced in a country in a particular period. Perhaps the finest introduction to how this measure took the world by storm is a book by economist Diane Coyle, GDP: A Brief But Affectionate History.
In my review of this book, I had pointed to three problems with GDP as a measure of economic activity. First, it is neutral between bread and bombs since it is a measure of output rather than human welfare. Two, feminist critics have quite rightly pointed out that it ignores the value of household work that is done outside the market. Three, it does not capture environmental degradations as well as resource depletion.
The digital economy presents a new set of challenges. Economists have struggled to understand what the transition from an economy of atoms to an economy of digits actually entails. One of the first questions raised was by Nobel laureate Robert Solow, a pioneer of modern growth theory, when he had famously quipped in 1987: “You can see the computer age everywhere but in the productivity statistics.” The initial debates were thus on why the impact of computers was not being seen in the measures of productivity.
Former US Federal Reserve chairman Alan Greenspan eventually came round to the view that the widespread use of computers and communications technologies by enterprises had led to a jump in productivity growth, and that had in turn led to an increase in the rate at which the US economy could grow without pushing up inflation.
One good example of his thinking at the time can be found in this 2002 speech. Greenspan used the productivity argument as one justification for holding interest rates low, even as unemployment fell below what economists horridly describe as the non-accelerating inflation rate of unemployment, or Nairu.
The new World Development Report published by the World Bank this month focuses on the dividends from the digital economy. It notes that much of the benefit that the Internet offers individuals is not captured in GDP data because there are no monetary transactions involved.
The authors of the report say that these benefits—be it time saved, expanded choice, consumer convenience or access to more knowledge—should be seen as consumer surplus. It is the difference between what consumers are willing to pay for something versus the actual amount they pay on the Internet, or perhaps get free.
The World Bank agrees that it is still very difficult to get a good sense of the aggregate effect of the Internet on an economy. But it makes an interesting point on page 70: “The initial gains from past technological change were also undercounted in GDP. For example, the cost savings from railroads made up about three-fourths of the total gains in GDP in the mid-19th century; by the early 20th century, this had fallen to about one-fourth. Time saving became by far the more important benefit as commute times shortened and the leisure time of working class customers increased. Similarly, US national accounts did not reflect the output from automobiles for nearly 15 years after the Ford Model T, the first mass-produced car, was available.”
Most of the emerging debates are not about the productivity effects of the digital economy, or the Solow paradox. They are more about how to measure an economy where some important distinctions are getting blurred.
In the words of the Bean committee: “Leaving public services to one side, GDP and its constituent components are estimated by focusing exclusively on activities carried out in the market economy, and assuming that market prices reflect values. Moreover, labour market data typically assumes a clean distinction between work and leisure. The digital economy and the Internet have made these assumptions less tenable by blurring boundaries between work, domestic activity (‘home production’) and leisure. It has also led to business models where it is harder for the statistician to observe both transactions and a corresponding price.”
Remember: you are in all probability reading this for free. So, this article has not contributed to Indian GDP, perhaps deservedly so! Or has it? Readers are invited to figure it out.
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