Measuring stuff is one of the things that sets humans apart from the other animals on the planet. In some cases we are very good at it.
For example, scientists from the Harvard-Smithsonian Centre for Astrophysics recently used a telescope at the South Pole to detect cosmic waves created a fraction of a second after the Big Bang 13.8 billion years ago. An incredible achievement. So why are we so bad at measuring things such as the global economy?
After all, most of us care more about where our next pay cheque is coming from than we do about the early universe. Yet the tool we use to measure the economy — gross domestic product — is hardly what you’d call cutting edge. It is based on concepts developed during the industrial revolution to help politicians work out the military capability available to them.
Today, the task of calculating national income using GDP has become so complicated that the latest guidelines for bean counters runs to a whopping 722 pages.
“The community of national statisticians with a command of all this detail is small,” writes Diane Coyle in a recently published book, titled GDP: A Brief but Affectionate History. “In other words, very few people indeed truly understand how the regularly published GDP figures are constructed.”
In an entertaining read, Coyle traces the history of our most popular economic yardstick and argues that GDP is good at counting stuff that comes out of a factory, but is increasingly unsuited to measuring the economic value of the stuff that defines our modern economy: innovation, technology and services.
It is perhaps no surprise that most of our recent economic crises have centred on these hard-to-measure areas: technology and innovation in the case of the dotcom bust; financial services in the case of the recent crisis.
Indeed, it might come as a surprise to free-market enthusiasts in the financial community that Adam Smith considered their work — and all other services — to be unproductive. The toil of all the bankers in the country, he figured, contributed nothing to the nation’s productivity. Perhaps the Occupy crowd should claim Smith as one of their own.
Of course, the great economist would doubtless have changed his mind about services as many more people started to work in the sector, but he would not have found the task of valuing their output much easier. Consider, for example, the question of what a bank actually produces.
We haven’t really sorted that out yet, which is to say that the value created by the financial industry is a bit of a mystery. This can clearly be seen in the UK’s GDP numbers for the last quarter of 2008, when Lehman Brothers went bankrupt and the global economy teetered on the edge of collapse. In that quarter, the British financial sector grew at record pace according to GDP accounting, suggesting that finance was making the same economic contribution as manufacturing. In fact, the industry was being bailed out by the state and continues to rely on subsidised funding.
Clearly, this failure to measure the actual productivity of finance can lead to terrible policy decisions. The same can also be said about the government sector, but in the opposite direction.
“If there is no private-sector comparator, or the market is not truly competitive, the only alternative is to measure the value of these services in terms of the wages paid to the public-sector employees providing them,” writes Coyle. “That gives a serviceable figure to use for GDP, but the catch is that those particular services can never show any improvement in the amount of output per government employee.”
Overlooking this statistical factor can sometimes make privatisation seem more attractive than it is, which is convenient for those who profit from the sale of government assets.
Globalisation poses another huge challenge. Failure to understand the economic costs of overseas borrowing was at the heart of the Asian financial crisis and even today the job of comparing one country to another is beset by inconsistent data and political shenanigans.
For example, on a single day in 2007 the size of China’s economy fell by 40% in purchasing-power terms. On the same day, the Philippines dropped by 43% and India by 36%. These apparent economic calamities were actually anomalies created by the World Bank’s methodology for calculating purchasing-power parity, which derives a price index from international survey data taken roughly once a decade.
China had not taken part in the bank’s first two international comparison surveys in 1985 and 1993, so the 2005 survey was the first chance for World Bank economists to gather accurate data. India refused to take part in 1993.
It is undoubtedly a complex task — measuring ancient cosmic waves is trivial when compared to the challenge of putting a timely value on all human economic activity.
But the task is made more complicated when we forget the purpose of all this measuring: the delivery of goods and services in mutually beneficial transactions, rather than the maximisation of short-term profit or even shareholder value.
GDP is not a perfect tool, but it does at least do a good job of measuring changes in growth from one period to the next. But Coyle hopes that we can come up with an alternative and complementary measure of “comprehensive wealth” that gives more emphasis to things such as human capital, the environment and sustainability.
Unfortunately, few governments around the world are increasing the money they spend on statistical collection and analysis. They should all be made to read Coyle’s book.