Scorched by a Data Drought

In December 1956, Zhou En Lai, the Chinese premier and, after Mao, the second mostpowerful man in China, created much consternation by refusing to leave his meeting at the National Sample Survey Organisation (NSSO) office at the Indian Statistical Institute (ISI) in Kolkata. He was talking to Prasanta Chandra Mahalanobis, the founder of the institute, and one of the pioneers in the field of survey methods.

Zhou was frustrated by his country’s inability to produce useable data on time. China at the time collected data in every single economic unit, which generated more data than they could process. By contrast, India, under Mahalanobis, had opted to use carefully designed random samples of the economic units to infer what was going on for the entire population, which was cheaper and quicker.

In the 1940s, even before India became independent, the ISI had emerged as one of the great centres for the study of statistical methods. Giants of modern day statistics such as Ronald Fisher, Andrei Kolmogorov, Jerzy Neyman, Abraham Wald and Norbert Weiner spent extended periods of time at the ISI in its first three decades, collaborating with the many outstanding Indian statisticians there including Mahalanobis and CR Rao, and publishing in its home journal, Sankhya. There is no other instance of an entirely homegrown institution in a developing country becoming a world leader in a large field of general interest.

Setting Standards

The National Sample Survey (NSS), when launched by the NSSO in 1949, was the most ambitious household survey in the world, covering over 1,800 villages and over 100,000 households across India. The methods used by the NSS became the standard for household surveys the world over.

For example, the use of inter-penetrating samples — essentially, two independent samples drawn from the same population — to test the reliability of the survey results, was developed by Mahalanobis in a 1936 paper and remains a standard tool for survey design. The Living Standard Measurement Surveys the World Bank still carries out in many countries are a direct descendent of the NSS.

And yet, despite our almost unquenchable thirst for national distinction, almost no one in India today knows this proud history. To most of us the acronym ISI stands for a Pakistani organisation dedicated to mischief. And if anyone has heard of Mahalanobis, it is as the inspiration behind our supposedly failed planning experiment.

The consequence of our present indifference is not merely a lost opportunity to take pride. It pervades our attitude to data, both as consumers and producers of evidence. We quibble about whether growth was 7.1% or 7.4%, ignoring the fact that our two main sources of official consumption data, the NSS and the GDP data produced by the Central Statistical Organisation (CSO), now tell entirely different stories.

If you believe the NSS, GDP co- uld be just about half of what it is according to the CSO. There are occasional academic debates about which one is correct, which no one in power pays any attention to. And yet, it is almost surely true that both estimates (and their growth rates) are off by a huge margin.

More worrying, this divergence has been known for nearly 50 years (though it has grown a lot). And though we are occasionally told that the NSS is understaffed, or that no one knows where the CSO got a particular number, there is absolutely no political interest in improving things. From being the world leader in surveys, we are now one of the countries with a serious data problem while people talk about the really good data you can get in Indonesia or Brazil or even Pakistan.

With the express intention of stirring up some action on this subject, we recently re-edited and updated a volume of essays, Poverty and Income Distribution in India, which Pranab Bardhan and TN Srinivasan had edited and the ISI published in the early 1970s. The goal was to showcase a remarkable body of work, now mostly sadly forgotten, on the nature of poverty and inequality in India, how to quantify it and what to do about it based on that evidence.

Attention to Detail

What jumps out when one reads these papers is the fine-grained attention to the details of how data gets collected and assembled, and an interesting mixture of activism and scepticism, no doubt in part a result of their clear-sighted understanding of the strengths and weaknesses of the evidence.

Inequality and poverty are back in fashion both in economic research and the political discourse today. But the same sophistication about the underlying data that drives these conclusions is often missing. Even more than the essays themselves — and there are four new ones by the editors and one by Amartya Sen — the book’s real value is as a reminder of a glorious (recent) past. And as an encouragement to turn our attention to an embarrassing present.

Banerjee, Bardhan, Somanathan and Srinivasan teach economics at the Massachusetts Institute of Technology, University of California (Berkeley), Delhi School of Economics, and Yale University, respectively