Presentation on theme: "Multidimensional Poverty Reduction in India 1998/99 to 2005/06: Where and How? Sabina Alkire and Suman Seth The Development Studies Association Annual."— Presentation transcript:
Multidimensional Poverty Reduction in India 1998/99 to 2005/06: Where and How? Sabina Alkire and Suman Seth The Development Studies Association Annual Conference Institute of Education, London 3 November 2012
Motivation Poverty measurement has been traditionally based on Per Capita Consumption Expenditure (PCE) Non-poor by PCE does not necessarily imply non- deprived in other indicators, such as – Basic services like health, education, sanitation, clean drinking water (Ahluwalia 2011) – Nutrition (National Family Health Survey 2005/06; HUNGaMA Survey Report, 2011) 2
Motivation Reduction in income poverty did not necessarily translate into improvement in other social indicators 3 PCE/Income poverty % to 37.2 % 0.74 % p.a. Pop. with no education % to 33.7% 0.37 % p.a. Women under-nutrition % to 32.3% 0.43 % p.a Child under-nutrition % to 47.0% 0.15 % p.a. Source: Tendulkar (2009) and National Family Health Survey (NFHS)
Motivation Need for understanding the joint distribution of deprivations and distinguish those who are multiply deprived from those who are not Need for a complementary measure that can capture direct deprivations 4
Multidimensional Poverty Index (MPI) The method is an adaptation of Alkire and Foster (2011) which can deal with the binary or categorical data and was introduced by Alkire and Santos (2010) and UNDP (2010) A person is identified as poor using a counting approach in two steps 1) A person is identified as deprived or not in each dimension using a set of deprivation cutoff (z) 2)Based on the deprivation profile, a person is identified as poor or not Terms: deprived and poor are not synonymous
How is MPI Computed? The MPI uses the Adjusted Headcount Ratio: H is the percent of people who are identified as poor, it shows the incidence of multidimensional poverty. A is the average proportion of weighted deprivations people suffer at the same time. It shows the intensity of peoples poverty – the joint distribution of their deprivations. A person is identified as poor if deprived in 1/3 of ten weighted indicators (k = 1/3). Formula: MPI = H × A
Useful Properties 7 The MPI can be broken down into the headcount ratio (H) and the average deprivation score (intensity) among the poor (A) to understand how poverty has been reduced over time Population subgroup decomposition Breakdown of overall poverty by dimensions to understand their contribution
Data for Analysis over Time 8 We use two rounds of National Family Health Surveys for trend analysis NFHS-2 conducted in NFHS-3 conducted in Not all ten MPI indicators are available in the NFHS-2 dataset
Indicators for Comparison over Time 9 IndicatorsDeprivation cutoff 1. Years of SchoolingDeprived if no household member has completed five years of schooling 2. Child School Attendance Deprived if any school-aged child (6-14) in the household is not attending school up to class 8 3. Child MortalityDeprived if any child has died in the household (only among ever-married women) 4. Nutrition Deprived if any ever-married adult woman or child under 36 months in the household with nutritional information is undernourished 5. Access to ElectricityDeprived if the household has no electricity 6. Access to Improved Sanitation Deprived if the household´s sanitation facility is not improved or it is shared with other households 7. Access to Safe Drinking Water Deprived if the household does not have access to safe drinking water or safe water is more than 30 minutes walk round trip 8. Housing and Land Deprived if the household lives in kaccha house or lives in semi-pucca house but owns less than one acre of unirrigated or less than 0.5 acre of irrigated land 9. Type of Cooking FuelDeprived if the household cooks with dung, wood or charcoal 10. Asset Ownership Deprived if the household does not own more than one of: radio, TV, telephone, bike, motorbike or refrigerator, and does not own a car or truck
An Almost MPI for India (MPI-I) 10 Based on the indicators and dimensions we create a poverty index similar to the global MPI We refer it as MPI-I It takes a lower value than the global MPI for India because of the changes in indicators.
11 How Did Uncensored Deprivation in Indicators Change Over Time (raw)? Significant reduction in all deprivations except attendance. Highest reductions in housing, sanitation, water and electricity deprivations.
12 Change in MD Poverty Nationally for Different Poverty Cut-offs Poverty Cutoff (k) Change M0M * Union (>0)H92.9%89.1%-3.8%* A39.2%35.9%-3.4%* M0M * One-fifth (0.2)H73.4%65.1%-8.3%* A46.5%44.8%-1.6% One-third (0.33) M0M * H56.5%48.3%-8.1%* A52.9%51.7%-1.2% Half (0.5) M0M * H30.6%23.6%-7.1%* A64.5%64.7%0.3%
How has Acute Poverty Decreased Nationally? 13
Absolute Reduction in Acute Poverty Across Large States 14 We combined Bihar and Jharkhand, Madhya Pradesh and Chhattishgarh, and Uttar Pradesh and Uttarakhand Significant reduction in all states except Bihar, MP and Haryana.
Improvement in Poverty: H or A? 15 Performance consistently strongest in Kerala, TN, & AP.
Comparison with Change in Income Poverty (p.a.) 16
Acute Poverty Across Castes/Tribes 17 M 0 -99M Change H-99H-06 Change A-99A-06 Change Scheduled Tribe %73.2%-6.5%56.9%56.1%-0.8% Scheduled Caste %58.3%-10.4%55.0%52.8%-2.2% OBCs %50.8%-6.5%52.0%50.7%-1.2% None Above %32.7%-12.3%50.7%49.8%-0.9% Disparity Increases MPI Poverty decreased least among the poorest. The STs (8.5% population share) are the poorest, but the change is lowest for them and for OBCs, who have a higher pop share. MPI Poverty decreased most for SC and None.
Distribution of Poor (k = 1/3) Across Castes We see the % of None decreased most, and that of SC, ST increased a bit and OBC increased quite a bit. 18 Change in Population Share
Poverty for k = 50% Subset of poor for k = 1/3: each persons intensity > 50% 19 Deprivation Score 50% Deprived 33% No Deprivations Poor by k = 1/3 MPI-I z Cutoffs Poor by k = 1/2 k cutoffs
Poverty for k = 1/2 Across States Regions Headcount Ratio (k = 1/3) Headcount Ratio (k = 1/2) Share of k = 1/2 Poor to k = 1/3 Poor Headcount Ratio (k = 1/3) Headcount Ratio (k = 1/2) Share of k = 1/2 Poor to k = 1/3 Poor Kerala33.3%8.6% %1.8%0.17 Himachal Pradesh35.3%7.7% %4.7%0.20 Tamil Nadu42.3%15.2% %6.6%0.25 Maharashtra46.4%21.5% %11.8%0.37 Jammu43.8%19.6% %13.0%0.39 Haryana39.7%15.9% %13.1%0.39 Punjab24.7%9.0% %7.4%0.39 Andhra Pradesh56.4%31.7% %16.4%0.40 Karnataka50.3%24.7% %15.3%0.40 Gujarat47.6%26.2% %16.0%0.44 Orissa70.5%39.4% %30.3%0.52 Eastern States61.1%32.8% %27.0%0.53 West Bengal60.3%35.2% %27.8%0.53 Uttar Pradesh64.3%36.1% %31.3%0.53 Rajasthan63.5%36.2% %31.4%0.54 Madhya Pradesh66.6%38.5% %34.0%0.55 Bihar76.1%49.5% %48.4%0.66 India56.5%30.6% %23.6%0.49
Poverty for k = 1/2 Across other Subgroups Regions Headcount Ratio (k = 1/3) Headcount Ratio (k = 1/2) Share of k = 1/2 Poor to k = 1/3 Poor Headcount Ratio (k = 1/3) Headcount Ratio (k = 1/2) Share of k = 1/2 Poor to k = 1/3 Poor Rural68.0%38.2% %31.9%0.53 Urban24.7%9.9% %8.3%0.39 Scheduled Tribe68.7%51.5% %45.5%0.78 Scheduled Caste79.7%40.5% %31.2%0.43 OBCs57.4%30.1% %25.2%0.49 None Obove45.0%21.9% %14.7%0.45 Hindu57.5%31.2% %24.1%0.50 Muslim59.1%33.9% %32.5%0.59 Christian40.6%17.4% %14.8%0.45 Sikh24.8%8.2% %5.7%0.33 Other Religion43.4%21.8% %20.6%0.49 No Education78.0%50.4% %43.2% Years60.7%30.7% %23.1% Years40.6%14.9% %11.5% Years25.2%8.0% %6.5%0.31 More Than 12 Years12.8%3.3% %2.0%0.21 India56.5%30.6% %23.6%0.49
Deprivation Score Ultra Poor: Changing Both Deprivation and Poverty Cutoffs 50% Deprived 33% No Deprivations Poor by k = 1/3 MPI z Cutoffs Ultra z Cutoffs k cutoffs Poor by k = 1/2 Ultra Poor
Ultra-poverty Deprivation Cutoffs Subset of MPI poor that are most deprived in each dimension 23 IndicatorAcute Deprivation Cut-offUltra Cutoff Nutrition Any adult or child in the household with nutritional information is undernourished (2SD below z score or 18.5 kg/m 2 BMI) 3SD or 17 BMI Child mortality Any child has died in the household Years of schooling No household member has completed five years of schooling No Schooling School attendance Any school-aged child is not attending school up to class 8 Electricity The household has no electricity Sanitation The household´s sanitation facility is not improved or it is shared with other households Uses bush/field Drinking water The household does not have access to safe drinking water or safe water is more than 30 minutes walk round trip Unprotected and 45 Minutes House The house is kachha, or semi-pucca and owns <1 acre or < 0.5 irrigated kaccha & no land Cooking fuel The household cooks with dung, wood or charcoal. Wood, grass, Crops, dung Assets The household does not own more than one of: radio, TV, telephone, bike, motorbike or refrigerator, and does not own a car or truck even one
Total Change in Deprivations of Ultra Poor across time (raw) 25
Ultra & k = 1/3 is 37.9% Deprivation Score Ultra Poor in % Deprived 33% No Deprivations Poor by k = 1/3 is 56.4% MPI z Cutoffs Ultra z Cutoffs k cutoffs Poor by k =1/2 is 30.6% Ultra & k = 1/2 is 15.8% 3.7% 22.1% 36.4% Only 7.1% of the population did not have any deprivations at all
Ultra and k = 1/3 is 31.7% Deprivation Score Ultra Poor in % Deprived 33% No Deprivations Poor by k = 1/3 is 48.3% MPI z Cutoffs Ultra z Cutoffs k cutoffs Poor by k =1/2 is 23.6% Ultra & k = 1/2 is 12.5% 5.5% 19.2% 40.8% 10.9%
Summary 28 MPI-I 99Ultra 99 Poverty Cutoff M0M0 HA M0M0 HA Union %39.2% Union %29.7% 20.0% %46.5% 20.0% %39.9% 33.3% %52.9% 33.3% %46.9% 50.0% %64.5% 50.0% %59.8% MPI-I 06Ultra 06 Poverty Cutoff M0M0 HA M0M0 HA Union %35.9% Union %27.6% 20.0% %44.8% 20.0% %38.8% 33.3% %51.7% 33.3% %46.0% 50.0% %64.1% 50.0% %59.3%
Conclusion – i (of ii) We have compared multidimensional poverty MPI-I across a seven year period, matching the global MPI indicators as closely as possible Multidimensional poverty declined across India, with an 8% fall in the % of poor (or 1.17% p.a.). But disparity among the poor has increased Progress has been slowest for STs, for hh with uneducated head of household, for Bihar MP and Rajasthan, and for Muslims. 29
Conclusion – ii We also looked at two subsets of the MD poor: those with severe intensity (k = 1/2), and those with high depths of deprivations (ultra). They are not the same: most ultra poor are not poor for k = 1/2. Still 12.5 percent of the population experienced ultra poverty and also poverty for k= 1/2 We are unable to update these results: needed data are unavailable for India since 2005/6. 30