Data mining for social research: a study of nutritious food consumption of Indian households

Abstract

There are various approaches to measure the differences in household income. Income measured from the monetary earnings point of view is called the nominal income. Income measured from the consumption point of view i.e. the basket of consumption goods a household buys is called the real income. In this paper we analyze the income based on the consumption of Highly Nutritious Food. Using tools of data mining (C&R tree and C5.0) we predict the trends in expenditure of households of India in the consumption of Highly Nutritious Food (Pulses, Cereal Products, Meat, egg, milk and milk products) which are not available through the Public Distribution System (PDS). We study the differences in expenditure on Highly Nutritious Food (HNF) across caste, religion, states and demonstrate that multiple factors influence the expenditure on HNF. We also categorize the per capita consumption of HNF as Low, Average and High. The outcome shows disparity in consumption of Highly Nutritious Food and argues that it can be a way to look at income disparity.