Data and Dogma: The great Indian poverty debate

Anyone who wants to understand why Angus Deaton got the Nobel Memorial Price in Economics for 2015, should read his 2004 paper on Indian poverty. Deaton is appreciated for his work of careful estimates of poverty. Deaton's book on household surveys is the go-to book for any development economist conducting surveys.

The usual figures reported in media like 'consumption', 'income', 'assets' etc. are not as easy to measure as they seem. 

For instance, how do you measure consumption of a household in surveys? If you ask them, what exactly should the question be? How should it be phrased? Should we ask, what the respondent ate yesterday or should we ask what they ate a week ago? 

Similarly, income is not a straight number that households give you when you survey them. Employed people can directly quote the monthly income but what about those who have irregular income from diverse sources? These things have to be measured carefully. In one of the surveys that I ran, our income module ran into 4-5 pages! Usually, people think income is just about only one question in the survey.

More important is the comparison across surveys. How do you account for change in the text of the question, recall period and so on? Similarly, how to correct for missing data or non-response. It's a complex job.

Owing to this uncertainty, there's a lot of scope for diverse interpretations making it a fertile ground for ideologically motivated people to dress figures to suit their narrative.

Deaton's 2004 paper "Data and Dogma: The great Indian poverty dabate" captures the essence of many arguments around growth-poverty-inequality data. In this paper, Deaton carefully deconstructs difference in data across surveys and how certain sections of economists have (deliberately) misinterpreted it. It also reflects the larger issue of politics around the data.

Some comments in this paper on Surjit Bhalla's work are insightful to read to get a sense of the politics around data and statistics.
Bhalla does not address the detailed arguments by Minhas against this sort of adjustment, nor Kulsheshtra and Kar’s demonstration of the inferiority of the numbers that Bhalla treats as correct compared with those that he rejects. Indeed, Bhalla does not reference their papers.
Further, Bhalla compares data across surveys that are incomparable, to prove his point.
Bhalla’s argument that there has been no increase in inequality is based on measures that appear to be taken directly from the unadjusted 1999–2000 survey, and are compared with similar measures from earlier surveys. But as we have seen, the unadjusted data from the 55th Round understate measured inequality because of the change in response periods for the low frequency items such as durables and clothing. 
Deaton makes these final comments on Bhalla's work
Bhalla’s work is important, not so much for its calculations and conclusions, which are not credible, but because it represents an important and widespread strand in recent Indian thinking, that the reforms have not only been associated with rapid growth of national income, but with the virtual elimination of poverty in India.
Anyways, I highly recommend reading Deaton's paper to get a rich understanding of the nuances behind poverty and inequality data and how even a slight change (for example, change in recall period in survey question) can lead to completely different set of results. 

At a time, when working on these seemingly minor pedantic things wasn't a fashion as compared to other research themes in economics, Angus Deaton persistently worked on them bringing rigour and clarity. Deaton rightly deserved the Nobel Memorial Prize for this.

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