10 months ago


durable seen as an

durable seen as an extreme deprivation at par with ‘having less than one square meal per day for major part of the year’. Further, the ranking on the aggregate score of rural households is not needed for programmes addressing deprivations that are universal in scope like illiteracy, lack of sanitation, and safe drinking water. The ranking is not relevant for key employment programmes (JGSY and EAS) that are focused on locations of need and not at individual households. The ranking does not matter for programmes like Antyodaya and Annapoorna. In a recent study, Jalan and Murgai (2006), by mapping of BPL criteria to NSS data, find that the BPL identification methodology is a weak mechanism for identifying the poor. Table 6.3 reports the extent of under-coverage in the BPL classification at the state-level estimated by them. One key findings of their study is that the BPL score misclassifies nearly half (49 percent) of the poor as non-poor, and conversely, 49 percent of those identified as BPL poor are actually non-poor. Jalan and Murgai argue that the targeting errors of the BPL design imply large welfare losses, both to households, and in terms of efficiency of public spending, which is based on the BPL mechanism. The problems of targeting across the distribution are also shown in Table 6.4 which reports poverty rates (expenditure based and BPL score based) and under-coverage and leakage rates by per capita expenditure classes. State Table 6.3: Poverty Rate and Targeting Errors in the 2002 BPL Classification, by State Rural Poverty Rate 99/00 (percent) Share of Poor Misclassified as Non-poor by BPL Criteria (percent) State Rural Poverty Rate 99/00 (percent) Share of Poor Misclassified as Non-poor by BPL Criteria (percent) Andhra Pradesh 10.5 76.9 Madhya Pradesh 37.2 43.8 Assam 40.3 41.6 Maharashtra 23.2 54.4 Bihar 44.0 40.6 Orissa 47.8 32.1 Gujarat 12.4 64.9 Punjab 6.0 72.4 Haryana 7.4 73.8 Rajasthan 13.5 63.8 Himachal Pradesh 7.5 74.5 Tamil Nadu 20.0 64.5 Karnataka 16.8 64.2 Uttar Pradesh 31.1 51.9 Kerala 9.4 72.6 West Bengal 31.7 46.3 All India 26.8 49.1 Source: Jalan and Murgai (2006), based on NSS 55 th round. Note: Rural poverty rates use official Planning Commission state-specific rural poverty lines. 132

In the nighbourhood of the poverty line (i.e., the third decile), the BPL indicator misclassifies 62 percent of the poor as BPL non-poor and 33 percent of the non-poor are classified as poor. In the poorest decile, a large share of the population (around 37 percent) is incorrectly classified as being non-poor. Targeting errors in the richer expenditure classes are, by comparison, marginal. Table 6.4: Poverty Rate and Targeting Errors in the 2002 BPL Classification, by Expenditure Class Poverty Rate Targeting Errors Expenditure Class Expenditure BPL Score Undercoverage Leakage Based Based Poorest 10 % 100.0 63.2 36.8 --- 2 nd decile 100.0 47.6 52.4 --- 3 rd decile 69.7 36.2 62.2 27.3 4 th decile 0.0 31.9 --- 100.0 3 rd quintile 0.0 23.0 --- 100.0 4 th quintile 0.0 14.3 --- 100.0 Richest 20 % 0.0 8.0 --- 100.0 Total 27.0 27.0 49.1 49.1 Source: Jalan and Murgai (2006), based on NSS 55 th round. Note: Leakage is the percentage of the BPL poor that is actually (expenditure-based) non-poor. These findings indicate that the BPL Census should be used for targeting programmes with adequate caution. In particular, targeting strategies should be developed separately for different objectives like income, health, education, and gender. 6.3 Targeting Strategies for Tamil Nadu In Tamil Nadu, distribution of funds/benefits among districts, for various central, centrally sponsored, and state schemes follow a variety of criteria. Often these are ad-hoc. A fourstage targeting strategy of (a) districts ranked in order of deficiency separately for different goals (income-deficiency, health, education, and gender objectives), (b) blocks/urban agglomerations, and (c) wherever the discretion is with the state government or district officials would improve outcomes. a. First Stage: Districts The first stage of targeting involves ranking of district in order of deficiency. This is most straightforward as data on levels of achievement are available. b. Second Stage: Rural: Blocks; Urban: Cities/Towns Within the district, allocation of funds should be done block-wise for rural areas and in proportion to urban poor in total urban poor in the urban segments. 133

World Comparative Economic And Social Data
Police Stations - Tamil Nadu Police
Nammakal - Tamil Nadu Police
N u m b e r o f S c h o o l s - DISE
Census 2011 population of Latur district
PDF: 1.0MB - Population Reference Bureau