Book Review: The GDP conundrum: Financial Express 11th February 2018

Whenever we evaluate the economic state of a country, the first indicator to look at is GDP. This is quite common today and becomes significant, as we can use the same measure to compare GDP growth across various countries because the methodology tends to converge in the course of time. As Indians, we love to say we are the fastest-growing economy. Earlier, China would talk of this coveted position. But is this a fair measure?

David Pilling, in his rather interesting book titled The Growth Delusion, examines in detail the concept and, more importantly, highlights its serious shortcomings that actually make it a poor indicator of the economic health of a country. For a student of economics, it would be like going back to college, where the same limitations were learnt. For example, the services of housewives in India go unaccounted for, while those in the West have a value, as the work is paid for, which makes the number an understatement.

But let us go back to the basics. A starting point is that the calculation of GDP can never be precise, as the economy is too large to be actually surveyed completely. Samples are drawn across economic streams and the results blown up to reflect the whole. Reading through this book would be a great comfort for the Central Statistics Office in India, as it has been pointed out that, even in England, few people have confidence in the numbers that are announced.

The credit for evolving this concept goes to Simon Kuznets in 1934. He recognised the limitations and wanted illegal activities and government activity excluded, as these did not add to welfare. Here, Pilling brings up issues like ‘sins’ (like drugs or prostitution), which add to the domestic product, but are not included, as they are part of the grey economy. This is one reason why GDP calculated by output, income and expenditure methods does not tally. At the same time, products like liquor and tobacco are added in GDP, but cause health issues that can lead to expensive treatment. Should these industries be excluded or repercussions adjusted for the negative fallouts?

Other conundrums that come up are exemplified by the outcomes on health in the US. When one is registered for government health insurance in the US, the cost of any procedure is just a fraction of the market price and this number gets included in the GDP. But for the same treatment, a person without insurance would be paying a very high price. Should adjustments be made here?

Another issue raised pertains to the environment. China grew very fast with high investment outlays and a sharp jump in the number of automobiles on the road. This led to high levels of pollution, which affects life expectancy, as well as the working life of people, which gets reduced. How does one account for such negative effects? One way is to ignore them, as they will get reflected in, say, a couple of decades when the economy slows down due to these factors playing out.

Further, an interesting facet brought out in the Internet age is that the economy has actually shrunk as we go online. There are fewer people required to issue tickets or even handle stores, with online bookings and home delivery on the rise. This has an impact on the GDP, which tends to slow down, as there are fewer jobs being created in relative terms. While this is not an issue with GDP conceptually, it’s something that one should keep at the back of the mind, as such growth does not tell us anything about employment. It’s relevant because with artificial intelligence becoming the norm in the future, the link between growth and employment will get severed.

Pilling also asks a question as to whether or not high growth in GDP with higher inequality makes sense from a welfare perspective. This is pertinent because in the age of Piketty, inequality has become a major issue, which, when combined with the distribution of wealth, tells another story. Another interesting observation made is that when we talk of average per capita income, we should be looking at the median and not the arithmetic mean because the latter gets skewed by extreme inequality and wealth distribution. This becomes relevant in India where the inequality levels are stark, especially in the past 20 years following economic reforms, where a capitalist-oriented economy has been fostered.
A well-known limitation of the GDP number is in the context of developing economies, where there is a very large informal sector. Here, it’s virtually impossible to know the true numbers because households tend to understate their income, as they fear that the tax authorities will come after them. This has been a problem even in India with the introduction of GST, where small players are hard to get inside the fold.

Pilling has a chapter on India, where he raises the now famous debate, or rather acrimonious argument, between Jagdish Bhagwati and Amartya Sen on the growth situation in India. There is still no clarity on whether growth without development is acceptable or not. It is clear, however, that after 20 years of growth, the benefits have not trickled down to the poor adequately and hence the story could be flawed. Sen’s argument was that Bangladesh, with a lower GDP, had made better progress in terms of development and social advancement, which matters more. In this context, the gross happiness index has also been discussed, where other dimensions of overall development can be measured.

Pilling provides a 360-degree view of the concept of GDP and its limitations. Governments in general like to overstate and overemphasise the GDP size, as it helps them show that they are doing well. Also, as almost all comparative indicators like fiscal deficit, debt, current account balance, etc, are linked to GDP, a higher denominator helps the cause for sure. But what can be concluded from reading this book is that, first, GDP measurement is heavily flawed, biased and can be calculated to suit the regime. Second, the calculation is never comprehensive and is based on samples and assumptions, and could tend to overstate or understate. Third, there are several negative outcomes from production and growth that are not captured in the number. Fourth, GDP per capita should always be based on the median and not the mean due to the issues of inequality and skewed distribution. Fifth, we also need to have a concept that subtracts the ‘ills of growth’ from GDP. Net domestic product takes into account only depreciation of capital and not health, environment and social effects.

Is there an alternative right now? Honestly, the answer is no, and it’s only after a lot of effort has been put in do countries try and converge in terms of conceptually calculating their GDP. Getting information on issues like environmental degradation and human illness caused by such growth is very difficult and, hence, this will remain merely a concept for a very long time.