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LATEST NEWS UPDATES | Data in a post-truth age -Sonalde Desai

Data in a post-truth age -Sonalde Desai

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published Published on May 30, 2018   modified Modified on May 30, 2018
-The Hindu

Trust in official statistics is vital for democracy — the new policy must avoid centralisation

David Spiegelhalter, president of Royal Statistical Society in the U.K., gave a most unusual presidential address in 2017. Instead of talking about esoteric statistical techniques, he talked about declining trust in numbers in a post-truth society bombarded by fake news and alternative facts. He recommended to the statistical community that the best way of inspiring trust was to be trustworthy by demonstrating competence, reliability and honesty.

India has been fortunate in inheriting a statistical system from stalwarts like P.C. Mahalanobis and C.R. Rao that has historically demonstrated all three. However, with the growing demand for statistics and increasingly challenging data collection environment, the move by Ministry of Statistics and Programme Implementation (MOSPI) towards developing a National Policy on Official Statistics is most welcome.

There is much to like in this policy. It notes increasing data needs, lays down the groundwork for ethical data collection, highlights the importance of data quality and addresses the need for documentation and durable data storage. However, it also remains rooted within the confines of governmental administrative structures and does not directly address the criteria identified by Mr. Spiegelhalter. In the Indian context, each of these presents great challenge.

Competence

Sample surveys, the bedrock of Indian statistical systems, must make explicit choices about who to ask various questions as well as what to ask and how to ask. In a statistical system developed by renowned statisticians and econometricians, it is not surprising that much attention has been directed towards identifying the universe of respondents and sample selection. However, this is only a small part of the challenge. Given the increasing need for statistics in diverse areas, it is important that scholars from many different disciplines be involved.

The National Sample Survey (NSS) collects data on occupations and industries of workers. In 2009, it suddenly switched from older codes designed in 1968 to new series of codes developed in 2004. This change makes it difficult to differentiate between farmers and farm managers and shopkeepers and sales managers via occupational codes alone. This leaves out such a large portion of the Indian workforce that it is mind-boggling. Why? We decided to adopt international standards developed for industrial societies where self-employed farmers and shopkeepers have been swallowed up by large corporations. I suspect that if a sociologist interested in occupations was involved in overseeing this change, it might not have passed the scrutiny.

Reliability

How surveys are designed and questions are developed has evolved into a science that transcends the skill set usually employed by our statistical systems. The Reserve Bank of India has adopted an inflation-targeting approach that relies on data on inflation expectations of individuals. In a country where ASER (Annual Status of Education Report) surveys repeatedly document extremely low mathematical skills, how reliable are the data when individuals are asked to compare their expectations of inflation rates over the coming year with that in the future? We have little understanding of reliability and validity of these data, and yet they form the bedrock of our policy. Experiments designed by cognitive anthropologists, educational assessment experts and survey design specialists are needed to arrive at the correct questions. And even then, we will need some way of estimating uncertainty surrounding these results.

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The Hindu, 30 May, 2018, http://www.thehindu.com/opinion/lead/data-in-a-post-truth-age/article24027330.ece?homepage=true


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