Volume: 03, May 2014, Pages: 972-985 International Journal of Computing Algorithm Integrated Intelligent Research (IIR) 972 Sieving Out the Poor Using Fuzzy Tools T. Pathinathan, Raj Kumar Department of Mathematics, Loyola College, Chennai- 34. Emails:frrajkumar@gmail.com, nathanpathi@hotmail.com Abstract This paper proposes a fuzzy complementary approach to the multi-dimensional measure of poverty. The paper uses the Capability approach initiated by Dr. Amartya Sen to examine the one- dimensional measures of poverty and its drawback. This paper adapts the method of ‘counting and multidimensional poverty’ as proposed by Sabina Alkire and James Foster [1] to the state of Bihar situation. Keywords: BPL (Below Poverty Line), Totally Fuzzy and Relative (TFR) Introduction In India ‘Poverty line’ has become a ‘Lakshman Rekha’ while welfare measures are distributed. There is a poverty line in India and elsewhere, which tell us how we can measure poverty. The global line for extreme poverty is $ 1.25 per day (approximately Rs. 75.00: $ 1= Rs.60.00) and for moderate poverty is $ 2 per day (approximately Rs. 120.00). In India, until recently, we measured poverty in term of income – expenditure (consumption) and calorific values. These measures do not capture the full picture of the poor, as poverty has many dimensions and there is a need to recognize it as multi-dimensional. 1. One-dimensional approach One-dimensional approach of poverty assessment is based on Income Poverty Line. Uni-dimensional model takes only absolute poverty into consideration. Absolute poverty line sets a poverty line as an income or consumption amount per year, based on the estimated value of goods necessary for proper living. The government of India has set the poverty line BPL (Below Poverty Line) as anyone earning Rs. 27.20 per day or less in rural areas and up to Rs.33.33 a day in urban areas are poor [2]. This means that a person who consumes goods and services more than the set poverty line is not considered poor.Each state in India is not alike in terms of poverty estimation. It is due to a different geographical, social, political, and economical set up in each state. And each state has its own methods of alleviating poverty and reducing the number of the poor through various scheme programmes. For example, the figures of poverty ratio in the following states are reported (BPL-Below Poverty Level) in the national dailies [2] as it is given in the following table. Table -1: BPL status of some States in India STATE YEAR (2004-05) YEAR (2011-12) STATE YEAR (2004-2005) YEAR (2011-2012) Worst - 5 Best - 5 Bihar 54.4 33.74 Goa 24.9 5.09 Chhatitisgarh 49.4 39.93 Kerala 19.6 7.05 Jharkhand 45.3 36.96 Himachal Pradesh 22.9 8.06 Manipur 37.9 36.89 Punjab 20.9 8.26 Andhra Pradesh (A P) 31.4 34.67 Puducherry 14.2 9.69 In Bihar, BPL was estimated at 33.7% in 2011-12, compared to 54.4% in 2004-05, a reduction by 20.7 % percentage points. That means above 20% of the population has gone above BPL in Bihar. From the above income based approach example it is clear that uni-dimensional approach is not able to capture the complexity of the multidimensional nature of the poverty in assessment. As Atkison, A. B. would put it “There is a widespread agreement that deprivation is multi-dimensional. It is not enough to look only at income poverty; we have also to look at other attributes.” As Sen has put it, ‘the role of income and wealth…. has to be integrated into a broader and fuller picture of success and deprivation.” [3] Therefore, there is considerable and growing literature, both theoretical and empirical on the multi-dimensional measure of poverty. 2. Multidimensional approach Across the country as well as all over the world, policymakers, government sectors and people in general have started to understand