Few weeks ago I had written a blog in Marathi on GDP. There is a lot of apprehension on the GDP numbers reported by the current Government of India, and the methodology is dubious. However, there is a wider (and Global) concern whether or not the GDP is a right metric in the first place. I had also written a blog post titled “Mansoor Khan on Third Curve” which was about the unsustainable economic model we have adopted. It is an excellent talk; do check at leisure!
The reason for this blog is that I came across an interesting review of a book on this topic and downloaded the eBook version (yet to read it but want to begin very soon).
I am reproducing the review which appeared on The Guardian website. The Book title is “Growth Delusion” by David Pilling. The original article can be accessed here:
Growth is our gauge of national progress. It is against gross domestic product (GDP) that we measure the priority we assign to health spending or defence. We pay the national debt out of GDP. The share of the top 1% in GDP is how we rate social inequality. It was the IMF’s estimates of GDP (purchasing power adjusted) that recorded the historic moment in 2014 when China returned to the top of the economic leader board for the first time since the days of the opium wars.
GDP maps our past, present and future. No wonder this statistic has been dubbed one of the greatest inventions of the 20th century. And yet, what is it exactly? It sounds simple. GDP is the sum of the value of all goods and services produced within a country’s territory without allowing for wear and tear. But this does not count something that is “out there”. What is out there are car factories, the warehouses of online retailers, and fees charged per hour by lawyers and doctors. This means that GDP is something quite abstract, as is “the economy” for which GDP stands. And both are of relatively recent vintage. Until the early 20th century the word “economy” was used to denote frugality, not the economic system which it evokes today. These abstractions have to be made up. They have to be put together by registering millions of acts of highly varied activity and production and incorporating them all into a single sum.
The insight that the economy is “made up” is no longer new. Depending on your intellectual tastes you could credit the idea to Karl Marx, Rosa Luxemburg, Karl Polanyi or Michel Foucault. As we come to terms with an environmental crisis, there has been a rash of books about the growth fetish and how to overcome it. David Pilling’s book isn’t the first or the deepest, but it certainly has a claim to being the most engaging and fast paced. In a wonderfully cosmopolitan survey he shows us the work that goes into making up the world economy. He introduces us to Chinese accountants struggling to scrub their numbers of lethal pollution, Nigerian economists trying to count the informal economy, shamefaced British statisticians valuing sex work.
GDP at its neatest captures a narrow and somewhat arbitrary slice of reality – goods and services that are (legally) sold. Extending it to cover a richer view of reality requires hair-raising statistical acrobatics. In the process we may flatten reality. But the risk of not doing so is that activities not included in GDP will be neglected. It’s a ticklish balance.
Given both the influence and limitations of this abstract entity, the obvious question to ask is how it came into being. Unfortunately, Pilling is less convincing as a historian than as a journalist. As he tells it, GDP emerged from an Anglo-American joust between two economists – Simon Kuznets and John Maynard Keynes. Their wrangle makes for a neat narrative, but it drastically undersells the story. Even if we start from the biographies of Pilling’s protagonists it is clear that he is missing a trick. In his Edwardian youth Keynes cut his teeth on the question of how to give a stable currency and thus a stable basis for valuation to the Raj. By the time he was writing the Economic Consequences of the Peace in 1919 Keynes was already struggling with the question of how to count German national income. It is with the first world war that the story of GDP should begin. This matters not only as a matter of historical correctness, but because it points to what was at stake. Amid the imperialist rivalries and domestic class struggles that exploded into war, what economists and statisticians were doing was carving a manageable national economy out of the open expanse of a Victorian world system.One of the reasons that 19th-century English did not have a neat term for “the economy” is that the boundaries between national economies were porous, gold-backed currencies were fungible, trade was largely free, national labelling was in its infancy, money moved uninhibitedly, a third of British wealth was invested offshore. Most migrants arriving at Ellis Island in New York had no passports. The new breed of experts that invented GDP invented our modern concept of unemployment, the cost of living and the balance of payments too. William Beveridge was a statistician as well as a pioneer of the welfare state. The two went hand in hand. A key element in the estimate of GDP were comprehensive national income tax, and social insurance data. The argument between Kuznets and Keynes was simply the final trimming of a bureaucratic-statistical complex that had been under development for half a century.
One can agree absolutely with Pilling’s diagnosis that we currently live in a state of dysphoria in which a gulf looms between economic reality and the measures experts use to measure it. What a broader gauge history would have done is to explain why. The problem is not simply that back in the 1940s Kuznet’s more humanist conception of economic data lost out to that of Keynes. It is that the mid-century idea of the national economy is coming apart. Oligarchic inequality, the breakneck incorporation of underdeveloped economies into global markets, and the environmental crisis all render this vision increasingly obsolete.
Pilling ends his book with a call for us to move beyond GDP. He is right. We need a debate about what to measure. But as he acknowledges, well-meaning efforts to augment or adjust it are easily dismissed by those in power. That should be no surprise. Power and knowledge are joined at the hip. New data emerges not just from good intentions or good ideas, but from real power shifts. If we want to change the data set, we might do better to start by asking what new types of numbers our current crisis is producing and how they might be suborned and mobilised for public purposes. After all huge businesses are being built on data.
The standard response is a defensive one of emphasising the right to privacy and data protection. Perhaps the better question would be what new public purposes we might requisition data for. As Pilling says, it is a glaring anomaly that the entire statistical budget of the UK is barely larger than the budget of a single big science programme. But what do those who control the pursestrings actually want the public to know? And which questions will those who hold the power and much of the data be willing to answer?