Right data, wrong data: Statistical sampling and the making of modern agriculture in India.

Abstract

The size of India's food deficit became a pressing question for the Indian state in the early years of independence. As different organizations, government bodies, and individuals debated over the ways, means, and expertise needed to tide over the food crisis, policymakers realized that the primary requirement was to have a numerical understanding of the problem. Data became crucial to accurately assess production trends and compare them with requirements. This article looks into the use of statistical methods, particularly, random sampling and production estimation through a crop-cutting technique. Exploring the statistical survey work done by P.C. Mahalanobis in Bengal from the late years of colonial rule to the surveys conducted by the Indian Council of Agricultural Research under the supervision of P.V. Sukhatme and V.G. Panse, the article analyzes how different factors, such as varying revenue systems of different regions and administrative structures, power struggles amongst statisticians, and leverage gained by Indian statisticians from support they received from better known British counterparts, all played a role in determining the nature of statistical tools adopted in India to measure its food production. Inaccurate data continued to be a challenge for the Indian state until well into the late 1950s, and that can now be explained in terms of this discord between Mahalanobis-led Kolkata-ISI and the ICAR of Sukhatme's time. India continued to follow different methods of statistical survey of foodcrops, thus, the scientific/political establishment always struggled with the apprehension that they did not have the 'right' data to come up with the correct assessment of the scene.