Hoping to ‘debunk’ myths about India’s growth, Bhagwati and Panagariya spin some fairy tales of their own
Among those who think that on the whole liberalisation in India has been for the better—and I certainly do—there are two ways to approach what has ensued. One is to believe that liberalisation has come with its attendant problems, some of them severe enough to raise serious questions about our developmental priorities and the need to refocus government efforts to ameliorate them. The other, however politely framed, is to dismiss all criticism as the work of Left loonies, overlook all contrary evidence, and tailor facts to suit their arguments.
Having invested so much of their academic career in promoting global trade, Jagdish Bhagwati and Arvind Panagariya have written a book that is as good an example of Panglossian economics as any you will find. It boasts of ‘debunking myths that undermine progress and addressing new challenges’ when it does nothing of the sort. All the book does is set up straw men and proceed to knock them down, while failing to address many essential criticisms of growth in post-liberalisation India.
Since it is easy to cherry pick examples, let me be guided by Panagariya on where to start with this book. In a recent interview, when Shekhar Gupta asked him to “talk about a couple of your favourite myths that you have mentioned in your book”, Panagariya said, “One of my favourite ones is that when we say poverty has come down and growth did help the poor, it immediately comes down to this—that socially disadvantaged groups have not benefited. It turns out to be false. When you do the numbers, you see steady decline in the poverty rates for both Scheduled Castes and Scheduled Tribes. There is this widespread belief that because the socially backward are out of the mainstream economy, nothing has happened to them. That is wrong.”
It is an invitation to look at that section in their book—Myth 3.3: Reforms have bypassed, even hurt, socially disadvantaged groups. In support of this myth, Bhagwati and Panagariya quote a submission by the National Campaign on Dalit Human Rights (NCDHR) to the House of Commons of the UK Parliament and a piece by Praful Bidwai. For a myth that is believed to be widespread, that is a rather limited set of formulations to depend on. Surely there would have been more credible criticisms that deserved their attention. And then it turns out that they need this exact formulation to be able to assert that ‘sustained growth alongside liberalising reforms has reduced poverty not just among the better-off castes but across all broadly defined groups’. They then go on to specifically focus on Scheduled Tribes and conclude that ‘the evidence of the decline in poverty among the Scheduled Tribes is quite unequivocal’.
In other words, all that these esteemed men are interested in showing is that there has been some decline in poverty during the period of liberalisation. They are not interested in debunking any claims that would suggest that the decline in poverty has slowed down drastically among Scheduled Tribes after liberalisation or that reforms have largely bypassed them. It is no wonder that they had to depend on the NCDHR and Praful Bidwai to provide an absurd formulation that they can knock down.
In doing so, they cite some data that speaks for itself: ‘Mukim and Panagariya (2012) calculate the poverty ratios by social groups for the expenditure surveys conducted by the NSSO…For the Scheduled Tribes, the ratio fell from 64.4 per cent in 1983 to 51.2 per cent in 1993-94 and to 46.3 in 2004-05.’ Thus, their own data suggests that the poverty ratio among STs, which declined by 13.3 per cent in the decade preceding liberalisation, declined only by 4.8 per cent in the first decade of liberalisation. Not only that, the percentage decline of the poverty ratio among STs in the five years from 1983 to 1987-88 was greater than for the entire first decade of liberalisation. In fact, by their estimates, if India had managed the 1980s rate of decline among STs in the next two decades of liberalisation, we would be looking at ST poverty ratios in the low 20s. Since STs are by far the most socially disadvantaged group in the country on most counts, it is safe to say this would have resulted in a sharply better overall poverty ratio than what exists today.
When we talk of STs, we are not talking of a small number, we are talking of 104 million people. By Panagariya’s own calculations, a population larger than that of Egypt, Germany, Iran or the UK has been largely bypassed by liberalisation. What Bhagwati and Panagariya refuse to face up to is that while STs have benefitted marginally, they would have gained far more even in the stilted paradigm of growth of the 1980s. In an entire chapter, ‘Reforms and their Impact on Growth and Poverty’, there is almost no acknowledgment of this fact, but at the very end of the chapter when they discuss the impact of trade openness on poverty, this becomes blindingly obvious. They conclude the chapter by stating that according to the same Mukim and Panagariya paper, ‘one or more measures have had a statistically significant and favourable impact on poverty levels among the Scheduled Castes and non-Scheduled Castes in rural and urban regions and in both regions taken together. As regards the Scheduled Tribes, they find a statistically significant effect of openness on poverty in urban areas only’. Of the 104 million STs in India, 94 million live in rural areas. In plain language, what they have stated is that the opening up of the economy has had an impact on poverty levels of every section of Indian society but for those who are worst off.
Since this suggests increasing inequality, you would expect that this rather strong observation would merit some discussion in their chapter on ‘Reforms and Inequality’. It comes up briefly and they state that ‘critics often assert that the income differences between Scheduled Castes and Scheduled Tribes on one hand and non-Scheduled Castes on the other have gone up during the years of rapid growth. But in a comprehensive analysis, Hnatkovska, Lahiri and Paul (2012) show that such claims are not supported by empirical evidence… Using Employment-Unemployment Survey data from the NSS rounds conducted in 1983, 1987-88, 1993-94, 1999-2000 and 2004-05, they show wages of Scheduled Castes and Scheduled Tribes have been converging with those of non-Scheduled Castes since 1983’. Considering that almost 50 per cent of rural ST households—the vast majority of all ST households—were self-employed even as of the 2009-2010 NSS, this conclusion based on wage earnings is a non-sequitur.
The rest of the chapter on inequality does not dwell on STs, but rather uses one of the favourite tools of economists to dispel claims about widening inequality—the Gini coefficient. Non-economists intimidated by mathematics are easily silenced when these two economists cite that the change in the coefficient post-liberalisation has been insignificant. As a non-economist with some understanding of the mathematics they use, let me just illustrate what this coefficient actually measures and why it is largely irrelevant to the discussion. If you earn Rs 10,000 a month and your boss earns Rs 50,000 and you both get a 20 per cent hike and your income goes up to Rs 12,000 and his goes up to Rs 60,000, this makes no difference to the Gini coefficient of a society comprising you and your boss despite the fact that the gap between your incomes has gone up from Rs 40,000 to Rs 48,000. Another way to look at it is to realise that of the Rs 12,000 of wealth generated in the year, you get only Rs 2,000 while your boss gets Rs 10,000 and this is considered an equitable distribution of wealth by economists who rely on this coefficient. It is another matter that goods can never actually be bought in terms of relative measures of wealth. In a society like ours where STs have very low incomes to begin with, and a large population, even a very slight absolute increase in their incomes can ensure an unchanged Gini coefficient even when the top one or two per cent or so add an obscene amount of wealth to their incomes.
Given that their attempts to dismantle Panagariya’s favourite myth is so ludicrous, we can go on to other examples from the book. My favourite is the section where they deal with malnourishment in India and descend into biology that is even sloppier than the mathematics they have used in the example cited above. Stung by the oft repeated comparison that the percentage of stunted and underweight children in India is higher than even sub-Saharan Africa, they cite a National Family Health Survey of ‘elite’ Indian children which finds that even among these, the proportion of the stunted is over 15 per cent, far higher than the expected 2.25 per cent. They then conclude that the explanation lies in genetics—Indian children are genetically smaller on average.
Unlike economics, science requires a careful examination of facts before arriving at a final conclusion. Bhagwati and Panagariya lazily consider one other alternative, dismiss it and go on to pronounce on the genetics of a subcontinent. A recent working paper by Seema Jayachandran and Rohini Pande makes short shrift of their conclusions: ‘In this paper, we use 27 Sub-Saharan African and one Indian Demographic and Health Survey (DHS) conducted since 2004 to demonstrate the importance of parental preferences within the class of environmental explanations. We find a much greater height drop-off for later-born children in India than in Africa: Height-for-age is actually higher in India than in Africa for first-born children. The Indian height disadvantage materialises for second-born children and increases for third and higher order births, at which point Indian children have a mean height-for-age lower than that of African children by 0.35 standard deviations of the worldwide distribution. We see the same pattern (a much steeper birth order gradient in child height in India than in Africa) when the estimation is limited to between-sibling variation. Thus, birth order is not just proxying for family background differences between smaller and larger families.’
‘This birth order pattern suggests that the prevalence of malnutrition in India is not an artefact of using child height to measure malnutrition rates (Panagariya, 2013). Genotypes do not vary with birth order, so a simple genetic predisposition to be short likely would not generate the very significant birth order effects we find.’ It doesn’t even matter whether Jayachandran and Pande’s own explanations are correct or not, their observations suggest that the world is a far more complicated place than Bhagwati and Panagariya can imagine.
The utter lack of self-doubt as they traipse from myth to myth suggests a problem not just of attitude but of training. It seems equity arguments just do not seem to permeate through to their conscience.
There are two good reasons for this. One stems from the nature of their subject. If Sikhs, for example, had cited the treatment they received in 1983 when their vehicles were singled out for search and they were harassed by Bhajan Lal’s Haryana cops, as an example of lack of equity, an economist would be unable to factor this in. In any calculation of equity for 1983, all an economist would consider is that many Sikhs owned cars while most of their countrymen didn’t. The kind of inequity that cannot be quantified is treated as besides the point by such economists, which is why in Gujarat the riots of 2002 are ignored when discussing development, as if the right to physical protection lies outside the purview of development.
It is this absurd view of the world that led Panagariya in the interview with Shekhar Gupta to articulate this gem:
Gupta: “In conclusion, tell me one thing that you will say today to Dr Manmohan Singh and to Narendra Modi.”
Panagariya: “To Dr Singh, get back to reforms. I think we have waited long enough. To Narendra Modi, I would say, don’t lose sight of it. Once you get into power, it is very easy to.”
Gupta: “Will you also tell him to defocus himself from the puppies and the burkhas?”
Panagariya: “Yes, when this happens, it doesn’t help people like us who admire him.”
Gupta: “And, you do admire him?”
Panagariya: “Yes, for all that he has done for Gujarat and for the policies he has advocated. I have written about it. But I think the puppies and burkhas, I can really do without.”
For Panagariya, puppies and burkhas are minor blemishes on a personality who has brought growth to Gujarat. Inequity does not even fit into this economist’s worldview. He does not even pay attention to the fact that growth has treated Muslims in Gujarat exactly as Modi’s language and administration has—by sidelining them.
This brings us to the second point. Even when inequity can be measured, as is true of Muslims in Gujarat, economists such as these are so insistent on arguing for growth that they choose to overlook the evidence. In March 2012, the Planning Commission estimated that while Gujarat has an urban poverty ratio of almost 18 per cent, compared with almost 21 per cent for the country as a whole, 42.4 per cent of Muslims in urban Gujarat are poor, compared with 33.9 per cent of Muslims in urban India overall.
This takes us back to Panagariya’s favourite myth. In Narendra Modi’s Gujarat, as with the state’s Muslims, the evidence shows that STs have been left behind, as they have been by liberalisation in general. The Modi growth model, which is in the end what Bhagwati and Panagariya are quietly pitching for throughout this book, is a form of social Darwinism, a culling of the most disadvantaged.
Hartosh Singh Bal turned from the difficulty of doing mathematics to the ease of writing on politics. Unlike mathematics all this requires is being less wrong than most others who dwell on the subject.