Soc Indic Res DOI 10.1007/s11205-015-1006-6
Regional Estimates of Poverty and Inequality in India, 1993–2012 Rajesh K. Chauhan1 • Sanjay K. Mohanty2,3 • S V Subramanian6,7 • Jajati K Parida4 • Balakrushna Padhi5
Accepted: 8 June 2015 Ó Springer Science+Business Media Dordrecht 2015
Abstract Using three quinquennial rounds of consumption expenditure data over two decades (1993–2012), this paper estimates the extent of money metric poverty and inequality in regions of India. Regions are made comparable, and the poverty head count ratio and the poverty gap ratio for 81 regions are derived using the state specific poverty lines as recommended by the Planning Commission of India. The gini index, rich–poor ratio and regression analyses are used to understand the extent of economic inequality in regions of India. Results indicate that though the extent of poverty has declined, economic & Rajesh K. Chauhan
[email protected] Sanjay K. Mohanty
[email protected];
[email protected] S V Subramanian
[email protected] Jajati K Parida
[email protected] Balakrushna Padhi
[email protected] 1
Population Research Centre, Department of Economics, University of Lucknow, Lucknow 226 007, UP, India
2
Harvard Center for Population and Development Studies, Cambridge 02138, MA, USA
3
Department of Fertility Studies, International Institute for Population Sciences, Govandi Station Road, Deonar, Mumbai 400088, India
4
National Institute of Labour Economics Research and Development, NITI Aayog, Govt. of India, New Delhi, India
5
Centre for the Study of Regional Development, Jawaharlal Nehru University, New Delhi, India
6
Population Health and Geography, Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston 02115, MA, USA
7
Population Health and Geography, Harvard Center for Population and Development Studies, Cambridge 02138, MA, USA
123
R. K. Chauhan et al.
inequality has increased in regions of India. During 1993–2012, the poverty head count ratio had decreased in 70 regions, increased in seven regions and remained similar in four regions of India. The southern regions of Odisha and southern regions of Chhattisgarh are reeling under high persistent poverty. The spread in poverty head count ratio among regions has increased from 0.38 in 1993–1994 to 0.64 in 2011–2012 confirming divergence in regional poverty in India. The pattern is similar with respect to poverty gap ratio. Regions of Tripura and Sikkim had highest improvements in poverty level. On contrast to poverty estimates, the gini index has decreased in 20 regions and increased in 61 regions. Likewise, 57 regions have recorded increase in rich–poor ratio. The rich–poor ratio was higher in developed regions and lower in less developed regions. Based on these findings, we suggest that regions with persistently high poverty be accorded priority in poverty alleviation program and explore the factors leading to increasing economic inequality. Keywords Poverty Inequality Head count ratio Gini index Rich–poor ratio Regions India
1 Introduction Estimates of poverty and inequality are routinely monitored at global, national and local level. While the World Bank provides the comparable estimates of poverty across countries, the national governments use varying methods to estimate poverty. These include the estimation of money-metric poverty using per capita income, per capita consumption expenditure, asset ownership etc. Despite differences in methodology, evidences support reduction of poverty across countries. The global estimates on poverty suggests that the poverty level had declined in all six regions1 across developing countries and developing countries are said to have achieved the Millennium Development Goals (MDGs) target of reduction in poverty. The poverty head count ratio, measured by $1.25 a day in 2005 prices, has declined from 43 % in 1990 to 21 % by 2010 in developing countries with fastest decline in East Asia (World Bank 2014). Though poverty has been declining, evidences suggests diverse pattern of inequality across and among countries. In literature, the Kuznets curve that suggests increasing inequality (inverted U shaped curve of inequality) along with economic development (Kuznets 1955) is often used to explain the pattern of inequality. However, the Kuznets curve does not have universal appeal (Galbraith 2012). Recent trends of gini index (a measure of inequality) in 130 countries suggests diversified pattern; the rising inequality (continuously rising/U-shaped curve) in 65 countries, falling inequality in 51 countries (continuously falling or inverted U-shape) and no trend in 14 countries (United Nations 2013). The European countries had shown lower inequality within countries and higher inequality across countries (Galbraith and Chowdhury 2007) while income and wage inequality in USA during 1913–1998 was of U shaped curve (Piketty and Saez 2003). These studies suggest that the Kuznets hypotheses may not necessarily hold true for all countries and over time. Among developing countries, inequality in China and Brazil are often referred. While poverty in China had reduced from 60 % in 1990 to 13 % by 2008,
1
East Asia, South Asia, Latin America and the Caribbean, East Europe and Central Asia, Middle East and North Africa and Sub-Saharan Africa.
123
Regional Estimates of Poverty and Inequality in India, 1993–2012
inequality seems to have increased. The gini index varies widely across countries; 0.53 in Brazil, 0.41 in United States of America and 0.37 in China (World Bank 2015). The global agenda of reduction in poverty and inequality is contingent on India’s progress in reduction of poverty as India is home to one-third of World poor. Also, reduction of poverty and inequality is a priority agenda and routinely featured in India’s plan documents. The trends in official estimates of poverty suggests reduction in poverty level (also known as money-metric poverty) from 44 % in 1993–1994 to 22 % by 2011–2012 (Planning Commission, Government of India 2013), similar to trends of developing countries. However, the decline in poverty estimates conceals large disparities among regions and districts of India. Evidence also suggests increasing economic inequality within and among states of India (Himannshu and Sen 2014). Disaggregated analyses at the regional level is a beginning step in understanding the spatial pattern of poverty and inequality in India.
1.1 Official Poverty Estimates in India The Planning Commission, Government of India estimates the poverty in India (referred as money metric poverty) using the consumption expenditure data (Schedule 1.0) collected by the National Sample Survey Organisation (NSSO). These estimates are widely used among planners, policy makers, national and local government, international organizations, academia and researchers for all practical purposes. The system of estimating poverty based on consumption expenditure basing household surveys assumed to be pioneered by India accord reasonably good reputation for poverty estimation (Deaton and Kozel 2004). Till recently, the per-capita consumption expenditure of 1973–1974 (rupees 49.09 in rural and rupees 56.64 in urban areas) was used as a base and updated to price index to obtain poverty lines in subsequent years. The Government of India had accepted the recommendations of Tendulkar Committee to re-estimate poverty lines (Planning Commission, Government of India 2009) and the committee recommended use of intrinsic price indices for adjusting the price changes over the time for update and upkeep of state specific poverty lines in India. The methodology prescribed also suggested of using mixed recall period (MRP), i.e. 30 days recall period for items frequently consumed and 365 days for items consumed less frequently (clothing-bedding, footwear, medical institutional, education and consumer durables). The committee provided with MRP based state specific poverty lines for 1993–1994 and 2004–2005 and the Planning Commission revised the poverty lines for 2011–2012. The state specific poverty lines have been provided for 28 states and two union territories (UTs) for three time periods for rural and urban areas separately. For remaining five UTs, the poverty lines of neighbouring states are recommended; for Andaman and Nicobar Islands line of Tamil Nadu, for Chandigarh line of urban Punjab, for Dadra and Nagar Haveli line of Maharashtra, for Daman and Diu line of Goa and for Lakshadweep line of Kerala were used.
1.2 Review of Literature Numerous studies have provided disaggregated estimates of poverty and inequality using the consumption expenditure data across states, among social groups and by selected attributes in India (Thorat 2010; Sundaram and Tendulkar 2003; Kannan and Raveendran 2011; Ahluwalia 1978; Chelliah and Shanmugam 2007). Sundaram et al. (1988) estimated rural poverty in 56 regions of India for 1972–1973. They found higher inter-regional inequalities compared to intra-regional inequalities among the poor contrary to intra
123
R. K. Chauhan et al.
regional inequality being higher compared to inter-regional for overall rural population. Jha and Sharma (2003) found no change in ranking of rural poverty for 1987–1988, 1993–1994 and 1999–2000 and observed that inequality have persisted over time. Kannan and Raveendran (2011) using 1993–1994 and 2004–2005 data demonstrate that social divide was more prominent compared to state specific divide in poverty. Thorat (2010) examined the propensity of being poor or falling poor for different social groups i.e. scheduled caste (SC), scheduled tribe (ST), other backward class (OBC) and others and by religious groups in India. Sundaram and Tendulkar (2003) found a similar decline in poverty among the scheduled caste, agricultural labour (rural) and casual labour (urban) households while the scheduled tribe households fared badly between 1993–1994 and 1999–2000. Sen and Palmer-Jones (2001) found divergence between poverty estimates derived from official poverty line and those directly from calorie consumption and suggested that credibility of data may be enhanced by incorporating subjective or in-depth methods. Guruswamy and Abraham (2006) proposed a minimum needs based poverty line and estimated it using data from 55th round of National Sample Survey (NSS). Gangopadhyay and Singh (2013) suggested that the approach by Jensen and Miller (2010) may successfully be used for estimating poverty lines by use of staple calorie share in food share and come-up with comparable estimates of head count ratio of poverty to estimates by Tendulkar committee for 2004–2005. Basu and Das (2014) observed calorie consumption puzzle may be seen, as a result, of a budget squeeze for food items in the long run. World Bank (2011) acknowledged steady progress in reducing consumption poverty but found that inequality which was on southward path until 1980s is headed north again and concluded that improving human development outcomes for the poor remains a key challenge for India. Himannshu (2007) also indicated poverty decline in Indian states during 1993–2005. Panagariya and Mukim (2014) illustrate that choice of poverty lines does not dispute the poverty decline during 2004–2005 and 2009–2010 and found narrowing gap in poverty incidence between social groups. Murgai et al. (2003) estimated the district level poverty by pooling the state and central sample for districts of Karnataka because the central sample was not adequate. The pooling state and central sample data of 61st round by Chauhan (2008) found higher standard errors of poverty estimates; nearly half of the districts were very high even after pooling. Chaudhuri and Gupta (2009) estimated the poverty for districts of India using the consumption expenditure data of 2004–2005. However, large sampling error for some districts of India were observed e.g. Relative Standard Error (RSE) for rural monthly per capita consumption expenditure (MPCE) for one-thirds of districts was beyond 10 % and for nearly 60 % districts urban MPCE similar RSE prevailed (Chaudhuri and Gupta 2009). Sen (1997) highlights the need to involve individual well being and economic freedom as a locus shift from income inequality to economic equality. Literature on economic inequality in India is relatively less compared to poverty but gaining increasing attention. Deaton and Dreze (2002) found widening disparities and increasing economic inequality in regions of India. Pathak and Mishra (2011) compared the estimates of poverty and inequality using alternative methods for social class and regions of India for 2004–2005. Highlighting the importance of state and region level factors Bhandari and Khare (2002) used level of economic activity (five variables) for 78 NSS regions to understand the change in economic activity during 1992–1999 and identified that broadly western regions gained and eastern region lost the ground. To understand growth story better authors stressed need for more studies on lower levels of aggregations with statistical rigor. Earlier Sastry (2003) examines RSEs for 55th round data and explains feasibility of reliable estimates of MPCE for most of the districts. Using convergence regression for prominent
123
Regional Estimates of Poverty and Inequality in India, 1993–2012
variables Singh et al. (2003, 2013) portray picture of regional inequality of for 59 NSS regions and were able to identify low performing regions belonging mainly to poorer states. Dubey (2009) demonstrate by using poverty analysis for five Indian states that intrastate disparities require similar attention that inter state receive. Rahman and Rao (2004) presented re-examination of gender equity and suggested increase in opportunities for women and investment in rural infrastructure can improve women’s agency in India. Besides estimates of poverty and inequality, studies also suggest alternative measures of poverty and inequality. Mukhopadhyay (2011) demonstrated that the squared poverty gap is efficient index to measure under-nutrition and allows decomposition as well. Sen (1976) presents relative poverty measurement through ordinal approach of welfare comparisons and stresses its simplicity and less data requirements. Joe et al. (2009) display that child malnutrition is linked to income, mother’s nutritional status and their education and advocates behavioural interventions to reduce it.
2 Aim and Rationale The aim of this paper is to provide the comparable estimate of poverty and inequality in regions of India over last two decades. The unit data from three quinquennial rounds of consumption expenditure survey; 1993–1994, 2004–2005 and 2011–2012 are used in the analysis. The extent of money-metric poverty is estimated using the poverty head count ratio and poverty gap ratio and inequality is measured using the gini index and rich–poor ratio (ratio of richest to the poorest consumption quintile). The official state specific poverty lines adopted by the Planning Commission; Government of India are used in estimating the poverty headcount ratio. The comparable estimates are provided for 81 regions of India to the extent possible for rural and urban areas as well otherwise for overall areas. Given the volume of work, we limit the analyses of this paper on estimation and trends in regional level on a comparable basis. We have carried out this exercise with following rationales. First, the estimates of poverty are often carried out at state level that conceals large disparities within the administrative regions in the country. The sample size at regional level is sufficient to provide robust estimate of poverty in regions of India. Though regions are homogeneous within, the regional pattern of development and disparity is stark in India. There are only few studies that estimated poverty in regions of India (Sundaram et al. 1988; Jha and Sharma 2003; Kijima and Lanjouw 2003; Jha et al. 2010) though a large number of studies have examined the poverty and inequality at state level and among social groups, there are limited number of studies that provide estimates of poverty and inequality in regions and districts of India. Second, the sub-national analyses i.e. by regions would identify the backward regions that need particular attention for alleviation of poverty and reduction of inequality in the population. The NSSO classified regions by taking agro-climatic characteristic into account and these regions are homogeneous with respect to economic activity. Third, the state is the unit for policy while district is the unit for administrative control. Regions in India are generally spread up to eight districts and these are similar culturally with respect to dialect, customs and other cultural practices. Fourth, there has been growing concern that inequality has increased over time though the poverty level declined across socio-economic groups and space. Fifth, studies on poverty and inequality are often carried out independently. But it may so happen that both poverty and inequality are working in same direction or in opposite direction. Though some attempts have been
123
R. K. Chauhan et al.
made on inequality at state level, no attempt has been made at regional level. Hence, it is necessary to understand the trends for multiple uses. This study will contribute to literature by providing trends in poverty and economic inequality in regions of India.
3 Data and Methods We have used the unit data of consumption expenditure (Schedule 1.0) three quinquennial rounds; 1993–1994, 2004–2005 and 2011–2012 and the cut-off point as used by Planning Commission to estimate the trends of poverty and inequality in regions of India. All three rounds are comparable and the household consumption expenditures are estimated based on MRP. The number of question on consumption expenditure were 416 in 1993–1994, 340 in 2004–2005 and 346 in 2012. The detailed questionnaire, sampling and the finding are available in respective report (National Sample Survey Organisation, Ministry of Statistics and Programme Implementation, Government of India 1996, 2006, 2014). The unit data are organised in several blocks and we have mainly used data from blocks 1, 3, 4 and 12. The monthly per capita expenditure (MPCE) is the key variable in deriving the estimates and we have validated our estimates of MPCE with published results of 50th round (Chaudhury 2007), and for 61st and 68th rounds with NSSO reports (National Sample Survey Organisation, Ministry of Statistics and Programme Implementation, Government of India 2006, 2014). In addition to household consumption expenditure, we have used the percentage of labourer households, percentage of SC population, percentage of ST population, percentage of Muslim population and percentage of households using liquefied petroleum gas (LPG) for cooking and households electrified in the analyses. We have also tabulated the average household size and female literacy for each of the regions. Besides using the unit data, a cross sectional panel data file was prepared for three periods of time keeping region as the unit. Since we do not have information on regional estimates of domestic product, we used the state domestic product per capita (SDPP) at uniform base (2004) and constant prices. The SDPP data were taken from the reserve bank of India’s website (www.rbi.org.in) and to bring 1993–1994 SDDP data at uniform base of 2004–2005 price deflator based on Wholesale Price Index (WPI) was used.
3.1 Comparability of NSS Regions 1993–2012 One of the daunting tasks in estimating the regional poverty and inequality is the comparability of regions over time. This is because either new regions are added, or some regions were combined or in few cases changed the boundary of the region within the state. We make regions comparable by taking both backward (the 68th round as a base) and forward (50th round as base) approach. However in cases where boundary of regions had changed, the district was reorganised over time to make regions comparable. In case new regions were created after 1993, the estimates of the new region in earlier period were kept same as that of the parent region from which it was created. In case geographic location of regions has changed, the district was considered to make the estimates comparable. A similar exercise was carried out by Murthie et al. (2001) and limited till 1993–1994. Appendix 1 presents the detailed arrangement of regions in three time periods. There were 78 regions each during 50th and 61st rounds and 88 regions during 68th round. There has been the reorganisation, a new creation by vertical division and recreation of regions by shifting the constituent districts. Utmost care is taken to keep comparability among the regional structures of the three rounds.
123
Regional Estimates of Poverty and Inequality in India, 1993–2012
Among 35 states and UTs; six UTs (Andaman and Nicobar Islands, Chandigarh, Dadra and Nagar Haveli, Daman and Diu, Lakshadweep and Pondicherry) and nine smaller states (Arunachal Pradesh, Goa, Meghalaya, Mizoram, Nagaland, Sikkim, Tripura, Uttarakhand and Delhi) comprised of a single region each during three rounds (the period 1993–2012). Among the rest of the twenty states, seven states namely Haryana, Karnataka, Kerala, MP, Maharashtra, Manipur and Tamil Nadu did not experience any change in boundaries of regions during three rounds. For the six states of Andhra Pradesh, Jharkhand, Himachal Pradesh, Jammu and Kashmir, Chhattisgarh and West Bengal there were vertical division of regions over time and parent region’s estimates for the earlier round were repeated against the newly created regions of 68th round. In this way, the comparable regional structures were maintained for regions falling in the above mentioned 28 states. For the rest seven states namely Assam, Bihar, Gujarat, Odisha, Punjab, Rajasthan and Uttar Pradesh there has been a reorganisation of regions in such a way that regional structures were not comparable across the time period. The stratum formation for urban areas during 50th round of the survey was done at the region level thus keeping those regions as domains of estimation. Thus, reorganisation of districts over time would not make them comparable if regions of 68 round were to be taken as a reference. Though backward comparability of 68th round regional structures was not possible but forward comparability of 50 round regional structure was possible for six out of seven such states excluding Gujarat. For these six states of Assam, Bihar, Odisha, Punjab, Rajasthan and Uttar Pradesh, regional structure of 50th round was kept as a reference. For 61st and 68th rounds the change in design, making district as a domain of estimation, enabled us to generate equivalent regions to that of 50th round by pooling constituent districts. Gujarat presented a unique challenge, except Saurashtra, remaining four regions of state experienced massive boundary change during three rounds. In 50th round seven districts were partly included in more than one region. Districts of Panch Mahals, Vadodara, Bharuch, Surat and Valsad were concurrently present in two regions namely Eastern and Plains Southern. Likewise, district Mehsana was part of two regions of Plains Northern and Dry Area and district Sabar Kantha was included in regions of Plains Northern and Eastern regions. Later in 61st round these seven districts were assigned in totality to particular regions of the state. These four regions could not be made comparable except pooling them, and thus, we did new regional classification for Gujarat by having two comparable regions namely ‘‘Saurashtra’’ and ‘‘Gujarat excluding Saurashtra’’. Thus, total of 82 regions was formed, and survey could not be conducted for ‘‘Laddakh’’ region of Jammu and Kashmir in 50th and 61st rounds thus could not be included. Hence technically and spatially comparable estimates of various quantities were generated and presented for 81 regions of India and each of the regions are comparable over time. Appendix 1 presents the detailed description of regions during the three rounds.
3.2 Methods We have computed the poverty head count ratio (HCR), poverty gap ratio (PGR), the Gini index (GI) and the rich poor ratio (RPR) for each of the regions at three periods of time. The state specific poverty line as recommended by Tendulkar Committee is used to demarcate poor and non-poor. While the head count ratio provides the percentage of population living below the poverty line and measures the incidence of poverty, the poverty gap ratio measures the depth of poverty. The Gini index is used to measure the extent of inequality in the population. Though we are aware of the more advanced methods of inequality analysis such as Atkinson (1970) alternative method for measuring income inequality and Ogwang’s (2014) regression based approach to decompose gini index into
123
R. K. Chauhan et al.
within-group, between-group and interaction components, we prefer use gini index to generate comparable descriptive statistics and to align with the scope of paper. We have also estimated the MPCE quintile separately for rural and urban areas and then derived combined MPCE quintiles. The ratio of richest and poorest MPCE quintile (termed as rich– poor ratio) is used to measure the rich–poor gap across the regions. It may be mentioned that each of the four indicators is not affected by price changes and thus are comparable over time. The multiple regression analyses are carried out to understand the determinants of poverty headcount ratio, poverty gap and inequality. A brief description of these measures as used in literature (Litchfield 1999) and in this paper is given below: Head count ratio (HCR) Poverty head count ratio also known as prevalence or incidence of poverty is fraction in the total population living below the poverty line. We have used Foster et al. (1984) index for measuring HCR which takes the following form: q ð1Þ HCR ¼ N where number whose q is the number of population whose consumption expenditures are below state specific poverty line; N is the total number of population. Poverty gap The intensity of poverty reflected in the extent to which the expenditure of the poor lies below the poverty line. It is measured as 1 X Zp Yi =Zp N i¼1 q
PGR ¼
ð2Þ
where Zp denotes the poverty line and Yi is the per capita consumption expenditure of the ith individual below poverty line. Gini index It measures inequality in the distribution of monthly per capita expenditure. Gini coefficients is defined as GI ¼
N X N 1 X Yi Yj 2N 2 Y i¼1 j¼1
ð3Þ
where Y is the mean expenditure of the households and Yi and Yj denote the expenditures of ith and jth households respectively. Rich–Poor Ratio It is the ratio of mean MPCE of richest quintile (top 20 % population) to mean MPCE of poorest quintile (bottom 20 % population) in the population. Ytop 20 % RPR ¼ Ybottom 20 %
ð4Þ
where Y denotes the mean expenditure of the group of households Rank of regions The rank of regions has been computed in a way that region with lowest value of average monthly per capita expenditure is assigned rank 1 and with highest 81. Thus track rank of regions upon average MPCE among all regions of India irrespective of state they belong have been generated. A lower rank indicates lower incidence of poverty and a higher rank indicates higher incidence of poverty.
123
Regional Estimates of Poverty and Inequality in India, 1993–2012
4 Results Table 1 presents the key indicators for regions of India. The number of regions has increased from 78 in 1993–1994 to 88 by 2011–2012 while the mean population size has increased from 10.65 million to 12.60 million during this period. The share of SC and Muslim population has increased while that of ST population has remained similar. The mean household size has declined from 4.8 to 4.4 during this period. The percentage of labourer households has increased marginally over time. However, there has been record increase in LPG coverage and electrification during the same period. The MPCE has increased by 68.78 % over time (at constant price of 1993–1994) indicating that the living standard has improved over time.
4.1 Regional Estimates of Poverty and Inequality in India, 1993–2012 Appendix 2 provides the state and regional estimates of the percentage of the population living below poverty line, i.e. HCR by rural, urban and combined for 1993–1994, 2004–2005 and 2011–2012. The regions are arranged within each state for better presentation and benefit of readers. Maps 1 and 2 presents the percentage of HCR and gini index (combined i.e. rural and urban taken together) for regions of India. An unique code is assigned to each region in Maps 1 and 2 and Appendix 2. The overall rank is provided for combined poverty estimates for all three period. We briefly describe the state pattern in poverty ratio before discussing regional trends. The percentage of population living below the poverty line in India has declined from 45.7 % in 1993–1994 to 22.0 % by 2011–2012. The decline in poverty was faster in urban areas compared to rural areas; declined from 50.2 into 25.4 % in rural and from 31.9 to 13.7 % in urban India. There has been a persistent decline in poverty across the states during 1993–2012 with varying degrees; 13 states/UTs registered a decline of over 60 % and more followed by 11 states with decline of 40–60 %; seven states had 20–40 % decline, two states with a moderate decline up to 20 % percent and remaining two states registered increase in poverty level. A very high decline, over 25 points, was observed for seven states; Andhra Pradesh, Bihar, Dadra Nagar Haveli, Himachal Pradesh, Karnataka, Manipur and Tamil Nadu. Similarly high decline of poverty HCR (20–25 % points) was observed for 10 states of Arunachal Pradesh, Haryana, Jharkhand, Kerala, Maharashtra, Meghalaya, Odisha, Rajasthan, Sikkim and Uttarakhand. Poverty increased for the state of Mizoram and Union Territory of Chandigarh during this period. In 1993–94, among all states and UTs, the highest HCR of 69 % was observed for the UT of Dadra and Nagar Haveli followed by Manipur (65 %) and Jharkhand (61 %) and it was the minimum in the UTs of Andaman and Nicobar Iceland (4 %) and Lakshadweep (10 %). By 2011–2012, the highest HCRs were observed in the states of Chhattisgarh (45 %) followed by UT of Dadara Nagar Haveli (43 %) and Jharkhand (41 %) and lowest for the UTs of Andaman and Nicobar Islands (1 %), Lakshadweep (1.7 %) and Daman and Diu (4.9 %). The variation in estimates of poverty at regional level is higher than the variation at state level. Among all the regions, 34 regions experienced a decline of 60 % or more followed by 21 regions with a decline of 40–60 %, 19 regions with decline 20–40 %, 3 regions with moderate decline up to 20 % and remaining four regions experienced an increase in poverty HCR over this period. A very high decline (more than) 25 points was observed for 31 regions and high decline (20–25 points) was observed for 16 regions followed by moderate decline (\20 points) in 30 regions. The significant reduction in
123
123
9.3
49.3
4.8
% Households using LPG gas
% Households electrified
Mean household size
32
31.5
% Household having agricultural labourer
No of states
11.2
% Muslims
330 (1.56)
8.9
% Scheduled tribes
74
19.3
% Scheduled castes
No of regions
934
Mean MPCE at 1993–1994 prices (SD)
10.65
Sex ratio (F/1000 M)
35
78
380 (4.27)
4.7
65.1
21.8
30.4
12.4
8.6
19.6
942
13.15
35
88
557 (11.55)
4.4
78.4
30.1
27.4
13.6
8.9
19.0
933
12.60
32
74
286 (1.45)
4.9
37.1
1.9
38.2
9.9
10.8
21.1
943
8.01
1993–1994
2011–2012
1993–1994
2004–2005
Rural
Combined
Mean population size (millions)
Indicators
Table 1 Key indicators in regions of India, 1993–2012
35
78
309 (3.36)
4.9
54.8
8.5
37.5
11.1
10.6
20.9
953
9.83
2004–2005
35
88
441 (7.3)
4.6
71.2
13.9
33.0
12.4
11.1
20.8
944
9.00
2011–2012
32
74
464 (3.93)
4.5
82.8
29.6
13.1
15.3
3.2
13.8
907
2.64
1993–1994
Urban
35
78
591 (11.44)
4.4
92.4
57.2
11.5
16.2
2.9
15.6
909
3.32
2004–2005
35
88
848 (32.82)
4.1
96.3
70.6
13.5
16.8
3.5
14.6
906
3.60
2011–2012
R. K. Chauhan et al.
Regional Estimates of Poverty and Inequality in India, 1993–2012
poverty HCR was observed in Costal Southern Andhra Pradesh (91 %), Jhelam Valley of Jammu and Kashmir (88.9 %), Inland North Western Andhra Pradesh (86.1 %) and Inland Southern Karnataka (84.8 %). Figure 1 provides the mapping of regions in poverty estimates in India for 1993–2012. A persistent decline in poverty HCR between 1993–1994 and 2004–2005 followed by decline during 2004–2005 to 2011–2012 has been observed in 58 regions. In one region namely Mizoram there was slight increase in poverty HCR. In 1993–1994 a total of 31 regions had poverty HCR in 50–80 % bracket; in 2011–2012 two of these regions came down to below 20 % level followed by 15 regions had HCR 20–35 %, 12 had 35–50 % and only two regions with poverty level of more than 50 % had similar poverty level. These two regions are Southern region of Odisha and Southern Chhattisgarh. On the other hand, more and more regions are entering the green zone with lower level of poverty by 2011–2012. Looking at concentration of poverty it may be observed that regions falling in demographically backward states of Uttar Pradesh, Bihar, Madhaya Pradesh, Jharkhand, Chhattisgarh and Odisha continue to have high rates of poverty HCR over the period of time. Over the time most of the regions falling in northern, western and southern parts of country are below the median levels of HCR (\35 %). In 1993–1994, while the estimated poverty was maximum in the southern region of Odisha (77 %) it was the minimum (4 %) in Andaman and Nicobar Islands. By 2004–2005, the estimated poverty remain maximum in southern region of Odisha and minimum in Andaman and Nicobar Islands. By 2011–2012 the poverty level was highest in Southern Odisha (58.5 %) followed by Southern Chhattisgarh (55.3 %), South Madhya Pradesh (49.8 %), Hills region of Maninpur (46.8 %) and South Western Madhya Pradesh (43.2 %). Lowest poverty level was observed in Andaman and Nicobar Islands followed by Lakshadweep, Costal Southern Andhra Pradesh, Mountainous region of Jammu and Kashmir and UT of Daman and Diu.
Fig. 1 Percentage of population living below poverty line in regions of India, 1993–2012
123
R. K. Chauhan et al.
The coefficient of variation of HCR has increased over time; from 0.74 in 1993–1994 to 0.88 by 2004–2005 and 1.57 by 2011–2012. This indicates that the poverty level among the regions has widened in last two decades. The rank order correlations of the poverty level in regions of India in 1993–1994 and 2004–2005 was 0.75, and that of 2004–2005 and 2011–2012 was 0.79 It suggests that ranks were maintained to a great extent despite poverty decline charactering vertical declines during the period of 18 years. Rural areas had higher order rank correlations compared to urban areas in both the comparisons. Table 2 presents the mean of poverty level, poverty gap, gini index and rich poor ratio by categories and change during 1993–2012 in each category. In 1993–1994, the mean poverty level in 14 regions was 65 % and by 2011–2012 no region had poverty levels beyond 60 %. In the same time, there were 9 regions with mean poverty level of 17 % in 1993–1994, and it has declined to 11 % by 2011–2012. Similarly nine other regions with Table 2 Poverty reduction in regions of India, 1993–2012 Poverty and inequality measures
No of regions
Percentage HCR, gap (mean) and gini 1993–1994
2004–2005
2011–2012
Absolute decline during 1993–2012
Percentage decline during 1993–2012
Poverty HCR \20 %
9
16.9
15.7
10.9
6.0
35.5
20–30 %
9
28.9
25.4
23.6
5.3
18.3
30–40 %
17
35.2
34.1
35.3
-0.1
-0.2
40–50 %
15
45.0
46.6
45.1
-0.1
-0.2
50–60 %
17
54.8
53.3
57.5
-2.7
-5.0
60%?
14
65.2
66.2
0.0
65.2
100.0
Total
81
45.7
37.8
22.0
23.6
51.8
\3 %
7
2.9
2.4
1.5
1.4
48.2
3–6 %
9
4.3
4.7
4.2
0.1
1.4
6–9 %
22
7.4
7.2
7.3
0.2
2.2
9–12 %
16
10.6
10.8
10.8
-0.3
-2.4
12 %?
27
15.7
14.3
13.0
2.7
17.3
Total
81
11.2
8.4
4.0
7.2
64.1
Poverty gap ratio
Gini index \0.20
6
0.221
0.179
0.196
0.025
11.3
0.20–0.25
24
0.262
0.260
0.265
-0.003
-1.1
0.25–0.30
38
0.291
0.288
0.315
-0.024
-8.2
0.30–0.35
11
0.367
0.357
0.350
0.017
4.6
0.35?
2
0.368
0.388
0.402
-0.034
-9.2
Total
81
0.300
0.347
0.359
-0.059
-19.7
1.80–2.80
14
2.570
2.650
2.690
-0.120
-4.7
2.81–3.80
50
3.400
3.350
3.400
0.000
0.0
3.81–4.80
14
4.100
4.280
4.200
-0.100
-2.4
4.81–5.80
3
5.170
-1.9
5.81–6.80
0
Rich–poor ratio
Total
123
81
3.550
5.280
5.270
-0.100
6.570
6.250
-6.250
–
3.990
4.080
-0.530
-14.9
Regional Estimates of Poverty and Inequality in India, 1993–2012
mean poverty HCR of 29 % in 1993–1994 were at 24 % in 2011–2012. With respect to the absolute decline, the reduction was 6 points and 5.3 points basis in those regions with lower poverty level. In general there has been downward shift in poverty levels and decline is visible in with lower poverty and regions with a highest level of poverty. Similarly the decline in poverty gap ratio is visible in all categories except one. The pattern is not similar in case of gini index. In case of poverty gap ratio, the mean PGR was 15.7 % among categories with PGR of 12 %? and declined to 13.0 by 2011–2012. In case of gini index, the mean level has increased from 0.300 to 0.359. For 64 regions this increase is between two to nine percent. Similarly rich poor ratio has increased from 3.517 in 1993–1994 to 3.994 in 2011–2012. The forward shift in regions is visible and highest category of 5.81–6.80 emerged after 2004–2005.
4.2 Poverty Gap Ratio in Regions of India, 1993–2012 Appendix 3 presents the poverty gap ratio, gini index and the rich–poor ratio for each region within the states for all three period. For India, the depth of poverty was at 11.2 % during 1993–1994 and has declined to 8.4 % in 2004–2005 and 4.0 % in 2011–2012. Among the states and UTs, the highest depth of poverty was observed for Bihar, Dadra Nagar Haveli, Jharkhand, Madhya Pradesh, Odisha and Uttar Pradesh as they kept featuring among top ten states during three periods under consideration following this Arunachal Pradesh, Chhattisgarh, Maharashtra and Manipur featured twice among top ten states. There were eight states and UTs which has shown a decline in poverty gap ratio (PGR) above national average. The highest declines were observed for Maharashtra (10.8 points), Karnataka (10 points) and Tamil Nadu (9.6 points) during 1993–2012. Eleven states and UTs had PGR more than that of national level (4.0 %) in 2011–2012. Among the regions, Inland Central region of Maharashtra had highest depth of 24.2 % in 1993–1994 followed by Southern Odisha (23 %) and South West Madhya Pradesh (22.9 %). In 2004–2005, the region with the highest depth of 29.1 % was noticed for Southern Odisha with an increase from 1993–1994 followed by Northern Odisha (19.1 %) and Eastern Maharashtra (17.6). In 2011–2012, Southern Madhya Pradesh had highest depth of 13.1 % followed by Southern Chhattisgarh (12.9 %) and Southern region of Odisha (12.9 %). Rank correlations between the pairs of ranks of the region on PGR during 1993–1994 and 2004–2005 was 0.734 and 0.727 during 2004–2005 and 2011–2012. This is indicative that rank has not changed a lot and poverty gap has also reduced with time. Among the 81 regions, 15 regions had shown a high decline (10 % points or more) followed by 36 showing a moderate decline (5–10 points), 26 showing a mild decline (\5 points) while as four regions registered an increase in poverty depth.
4.3 Gini Index in Regions of India, 1993–2012 Appendix 3 provides the trends in two measures of inequality namely, the gini index and the rich–poor ratio for states and regions of India over three period of time. Figure 2 also provides the map of gini index in regions of India. These measures are derived from the monthly per capita consumption expenditure. In general we observed that though poverty has declined in most of the states, the economic inequality has increased. Chandigarh had highest gini coefficient of 0.361 in 1993–1994 followed by Maharashtra (0.348) and NCT of Delhi (0.324). In 2004–2005 Dadra and Nagar Haveli became the state/UT with the highest inequality (0.386) followed by Chandigarh (0.381) and Maharashtra (0.381). In
123
R. K. Chauhan et al.
Fig. 2 Inequality in MPCE (gini coefficients) in regions of India, 1993–2012
2011–2012 Chandigarh had the highest value (0.391) followed by Karnataka (0.388), Union Territory of Dadra and Nagar Haveli (0.379) and Kerala (0.379). While 16 states/UTs have shown successive increase in gini coefficients during 1993–2004 and 2005–2012; for the former period 32 states/UTs registered increase and for a later period 19 states/UTs gini coefficients increased. During the period 1993–2012 states/UTs of Daman and Diu, Meghalaya and Pondicherry exhibited decline in inequality and remaining 32 registered an increase. The mean MPCE at constant price and the gini index has increased for most of the regions suggesting increasing economic inequality in the population. During 1993–2012, there were 64 of the 81 regions recorded increase in the gini index while 17 regions had shown a decline in the gini index. In 1993–1994, among the regions, the highest inequality was in Chandigarh (0.361) followed by Costal Northern Tamil Nadu (0.359) and Southern Madhya Pradesh (0.342). Regions with the least inequality were Himalayan Region of West Bengal and Plains and Hill regions of Manipur. In 2004–2005, the regions with the highest inequality were coastal northern Tamil Nadu, Costal Maharashtra and Dadra and Nagar Haveli while as with least were in Hills of Assam and two regions of Manipur. The highest inequality in 2011–2012 were observed for Inland Southern Karnataka (0.409), Costal Maharastra (0.401) and Central Madhya Pradesh (0.393) while the lowest for the hills both the regions of Manipur and Daman and Diu. For 17 of regions there has been a decline in inequality with maximum of 20 % for South Western Madhya Pradesh, 19 % for Inland North Eastern Andhra Pradesh, and 18 % in Inland Central Maharashtra. More than three-fourths of regions displayed an increase in inequality during 18 years.
4.4 Rich–Poor Ratio in Regions of India, 1993–2012 The rich–poor ratio (RPR) for all India was 3.52 in 1993–1994, 3.94 in 2004–2005 and 3.99 in 2011–2012 suggesting widening gap among richest and poorest consumption
123
Regional Estimates of Poverty and Inequality in India, 1993–2012
groups. In 1993–1994, the RPR was highest for NCT of Delhi (5.15) followed by Chandigarh (5.05) and Tamil Nadu (4.19). It was lowest for the north-eastern states of Manipur (2.05), Mizoram (2.31) and Nagaland (2.42). In 2004–2005, the states with highest RPR were Chandigarh (6.23), Kerala (5.34) and DN Haveli (5.09) and lowest were Manipur (2.06) followed by Meghalaya (2.30) and UT of Lakshadweep (2.64). In 2011–2012, Chandigarh again featured as a state/UT with highest RPR with value being as high as 6.53 followed by NCT of Delhi (5.84) and Kerala (5.39). Among the regions, in 1993–1994, the RPR was highest in NCT of Delhi, Chandigarh, coastal northern regions of Tamil Nadu followed by inland central region of Maharashtra and Southern Madhya Pradesh. It was low in plain and hill regions of Manipur and Assam. By 2011–2012, the highest RPR was in Chandigarh (6.53) followed by Southern Kerala (6.11) and NCT of Delhi (5.84) and lowest in Northern Chhattisgarh (2.28), Daman and Diu (2.46) and Sikkim (2.49). There has been a decline in RPR for 22 regions and an increase for 58 regions and it remained unchanged for one region. The highest decline was observed for Inland Central Region of Maharashtra (30 %) followed by South Western Madhya Pradesh (24 %) and Meghalaya (22 %). In general we observed that those regions that are developing faster, the rich–poor ratio is also widening. On the other-hand, in the under-developed regions the rich poor ratio tends to be low irrespective of the state.
4.5 Poverty, Gini Index and Consumption Expenditure in Regions of India Before undertaking multivariate analyses we plot the gini index and MPCE (logarithm) over three point of time (Fig. 3). We found with increase in economic well being, the gini index has also increased. Also with time, both the MPCE and gini index moved rightward. This is indicative that both economic well being and the gini index have increased over time. We have also plotted the gini index against the poverty gap ratio in regions of India (Fig. 4). We found decline in poverty gap level over time but increasing inequality in
.4
67
.3
57
57
.2
Gini coefficient
17 40
33 31
33 39 17 22 7
44 67 36
79
31
13
1
13 22 80 79 67 49 70 20 41 5 29 70 48 15 4 35 72 59 48 39 73 55 14 16 15 64 464173 4 19 61 16 47 44 20 35 55 58 3 2 26 39 46 60 2 45 25 80 68 81 45 61 6 5833 69 79 76 4080 25 49 24 42 4336 1 30 48 29 70 64 23 74 19 4769 5 72 7475 246953 41 38 81 64 3 45 65 56 52 6 76 31 73 78 78 63 60 59 32 37 59 30 29 17 38 65 2024 25 68 58 4256 46 2 19 3 6 40 72 62 68 9 66 21 37 75 30 76 35 23 43 47 26 777 497434 34 43 71 65 32 34 27 78 8 23 6322 75 18 74 38 60 37 61 71 16 15 14 56 1257 421432 54 28 27 9 71 26 77 63 53 66 5 5262 8 66 81 12 62 21 18 12 11 54 8 10 11 11 21 28 9 52 51 28 18 53 50 27 54 10 77 10
51
50
44 13 36 55 1
50
.1
51
5
5.5
6
6.5
7
Ln(MPCE) 1993-94 Fitted 1993-94
2004-05 Fitted 2004-05
2011-12 Fitted 2011-12
Fig. 3 Scatter plot of gini index and MPCE(ln) in regions of India, 1993–2012
123
R. K. Chauhan et al.
.4
33 36 79 1
.3 .2
Gini coefficient
1
67 44
31 55 13 22 36 13
39 4433 13 67 22 79 80
40
31 70
17
17 67
7 20
49
41 5 70 48 354 29 15 48 46 73 59 39 64 55 72 73 16 15 4 61 19 4114 55 44 20 16 58 47 3 2 26 25 45 35 2 60 61 46 39 80 79 81 45 68 58 633 76 40 69 25 24 80 49 1 19 43 36 23 30 29 64 70 48 42 7 74 69 53 72 47 5 4 24 69 38 81 41 3 56 6 52 45 6575 78 64 76 6059 73 78 59 37 32 6519 31 30 46 29 17 72 62 20 3856 68 63 2568 24 58 6 3 2 21 66 9 40 35 37 30 71 75 65 42 23 26 47 77 34 49 27 43 78 8 7 76 34 74 22 43 32 34 63 23 75 18 71 60 74 61 57 37 16 15 14 4238 54 28 27 12 56 32 566 52 62 77 63 719814 53 26 81 62 12 12 66 1821 11 54 10 8 11 11 21 28 2852 9 18 51 50 53 27 54 10 77 50
57
57
51 50
10
.1
51
0
20
40
60
80
Poverty HCR 1993-94 Fitted 1993-94
2004-05 Fitted 2004-05
2011-12 Fitted 2011-12
Fig. 4 Scatter plot of gini index and poverty (HCR) in regions of India, 1993–2012
regions of India. The pattern from both the figures suggests increasing income level, reduction in poverty and increasing inequality over time.
4.6 Association of Poverty and Inequality with Selected Developmental Indicators in Regions of India, 2011–2012 To understand the association of selected indicators in regions of India, we have computed the correlation of poverty HCR, poverty gap ratio, gini index, rich poor ratio, percentage of scheduled caste population, percentage schedule tribe population, percentage of Muslim population, percentage of households labourers, percentage of households using LPG gas, the percentage of households using electricity for lighting, young dependency ratio, old dependency ratio, percent persons literates, percent females literates and mean household size for 2011–2012 data. We found that the correlation coefficient of poverty HCR is positive with young dependency ratio, proportion of ST population and mean household size and negative for household using LPG and electricity, overall and female literacy and old dependency ratio. The poverty HCR is negatively associated with rich poor ratio and gini index indicating that the inequality is low where poverty is high. The coefficients for rural areas were of similarly associated to poverty HCR and with minor variations in urban areas. The patterns are also similar with respect to poverty gap ratios. Gini index was positively correlated with rich poor ratio. Gini index was also positively associated with increase in household using LPG and electricity, and old dependency ratio. It was negatively associated with mean household size, household being labourer and proportion of ST population. Rich poor ratio also display the similar correlation coefficients as done with Gini index, with young dependency ratio also being negatively associated (Table 3).
123
0.403*
0.390*
0.591*
Young dependency ratio
0.546*
-0.530*
0.372*
Mean household size
* Significance level of 95 %
-0.376*
-0.383*
% Persons literates
% Females literates
0.310*
-0.385*
-0.375*
-0.605*
% HH using electricity for lighting
-0.550*
-0.359*
-0.613*
% HH using LPG for cooking
-0.288*
-0.204
-0.359*
-0.269*
% HH being labour
Old dependency ratio
-0.188
% Muslim population
% ST population
-0.149
-0.131
% SC population
-0.165
-0.261*
Rich–poor ratio
-0.091
1
-0.189
0.969*
Gini index
1
Poverty gap
-0.325*
0.098
0.089
0.279*
-0.209
0.252*
0.322*
-0.317*
-0.125
-0.244*
0.164
0.930*
1
-0.302*
0.159
0.145
0.321*
-0.277*
0.2875*
0.297*
-0.308*
-0.306*
-0.309*
0.516*
-0.522*
-0.496*
-0.424*
-0.221* 0.4341*
-0.189
0.449*
-0.217
-0.067
-0.313*
0.951*
1
-0.106
-0.337*
0.206
1
Rich poor ratio
Poverty HCR
Gini index
Poverty HCR
Poverty gap
Rural
Combined
Poverty HCR
Sector
Table 3 Correlation coefficient of selected indicators in regions of India, 2011–2012
0.224*
-0.300*
-0.297*
-0.308*
0.456*
-0.411*
-0.416*
-0.344*
-0.199
0.472*
-0.239*
0.085
-0.262*
1
Poverty gap
-0.195
0.324*
0.328*
0.206
-0.207
0.298*
0.227*
0.152
0.032
-0.123
-0.101
0.296*
1
Gini index
-0.198
0.039
0.014
0.534*
-0.232*
0.255*
0.175
-0.072
-0.201
-0.140
0.062
1
Rich poor ratio
0.451*
-0.339*
-0.302*
-0.152
0.584*
-0.426*
-0.549*
0.013
0.018
0.023
0.019
0.026
-0.233*
0.975*
1
Poverty HCR
Urban
0.406*
-0.285*
-0.256*
-0.108
0.589*
-0.400*
-0.563*
-0.03
0.031
0.011
-0.017
-0.004
-0.208
1
Poverty gap
-0.057
0.006
-0.022
0.038
-0.117
0.031
0.015
0.036
0.145
-0.015
-0.004
0.095
1
Gini index
-0.140
-0.142
-0.163
-0.065
-0.087
-0.242*
-0.149
0.286*
0.011
-0.177
0.170
1
Rich poor ratio
Regional Estimates of Poverty and Inequality in India, 1993–2012
123
R. K. Chauhan et al.
4.7 Factors Affecting Poverty and Inequality in Regions of India To understand the intervening indicators of poverty HCR, poverty gap, Gini index and Rich poor ratio the ordinary regressions analyses were carried out for regions of India. We have pooled the data for generating the estimates for three period of time to generate a sufficient number of cases and capture the role of time in explaining poverty variation. The set of independent variables are percent Muslim population, percent scheduled caste population and percent scheduled tribe population in the regions, percent labourer households (agriculture and other in rural areas and casual in urban areas) and use of electricity for lighting, average household size, female literacy and the SDPP. These variables were used after series of tests of multi-colinearity by observing the correlation matrix and variance inflation factors (VIFs). We first regressed poverty HCR and gini index across time (Table 4) followed by other explanatory variables (Table 5). In both the models place of residence has been used as an indicator variable thus rural and urban estimates have been used. Table 4 presents the beta coefficients and t statistics for poverty head could ratio for three rounds taken together. We found that the coefficient of poverty HCR was -7.10 in 2004–2005 and -18.77 in 2011–2012. In other words, poverty level in 2004–2005 has declined by 7 % and by 2011–2012 by 19 % compared to 1993–1994 level. Both the coefficients are significant indicating that poverty has declined over time. The pattern is similar in case of poverty gap ratio; showing significant decline over time. In case of gini index and rich poor ratio, the regression coefficients are positive indicate that inequality have increased over time. On average the gini index in 2004–2005 was 2.5 % higher than 1993–1994 level and 2.9 % higher in 2011–2012. Similarly rich poor ratio in 2004–2005 was 50 % higher than 1993–1994 and 53 % higher in 2011–2012. All four measures are significant over time. Poverty is positively and significantly related to labourer households, household size, percent ST population and in urban areas while as it is negatively related to percent Muslim population, percent households using electricity, percent SC population, female literacy and SDPP. All the coefficients were statistically significant at 99 % level of significance except for household size and proportion ST population which were significant at 95 %. For the time periods of 2004–2005 and 2011–2012 the direction of coefficients is positive but only coefficient for 2004–2005 is moderately significant. The variables those are significant in explaining poverty HCR are SDPP, household size, young and old dependency ratio, labourer households, households having electricity and Muslim population. All the coefficients are in expected direction. The coefficient of SDPP indicates that 10 % increase in SDPP would lead to 4.6 % decline in poverty. With increase in household size of one, the level of HCR would like to increase by 2.4 %. Similarly, 10 % increase in labourer households would lead to 2.4 % increase in HCR. Though time was a significant predictor in base model (Table 4), it is not so in full model. All these variables explain 57 % variation in the poverty across regions. Results are similar for poverty gap ratio. The significant variables are urban residence, old dependency ratio, labourer households, percentage of households with electricity, percentage Muslims and percent females literate. These variables explain 52 % variation in poverty gap ratio. In case of gini index the variables those are significant are rounds, urban residence, SDPP, and schedule tribe population. These variables explain only 37 % of variation in the model. For rich poor ratio the significant variables were time, urban residence, old dependency ratio, proportion labourer households and mean household size. Except mean household size other coefficients were positive.
123
0.18
486
R2
Number of cases
29.88
-10.31
-18.77
38.46
2012
-3.90
-7.10
486
0.17
9.08
-5.33
-2.15
Regression coefficients
Regression coefficients
t values
Poverty gap ratio
Poverty HCR
Dependent variables
Constant
2004
Independent variables
24.4
-10.12
-4.09
t values
486
0.04
0.256
0.029
0.025
Regression coefficients
Gini index
Table 4 Result of regression equation of poverty HCR, poverty gap ratio and the gini index over time, 1993–2012
55.34
4.39
3.80
t values
486
0.04
3.517
0.526
0.501
Regression coefficients
Rich poor ratio
39.01
4.12
3.93
t values
Regional Estimates of Poverty and Inequality in India, 1993–2012
123
123
0.026
0.237
Percentage labourer households
486
0.569
Adjusted R2
Number of cases
93.852
Constant
-3.62
-0.135
-0.273
Percentage Muslims
Percentage females literate
2.35
0.068
4.70
-7.27
-2.81
-0.198
Percentage scheduled caste
Percentage scheduled tribe
-7.85
-0.279
Percentage households having electricity
4.76
0.91
1.94
2.376
Household size
Old dependency ratio
2.58 -2.47
4.719
Urban (dummy–rural)
1.08
1.77
-4.555
1.974
State domestic product per capita (SDPP) in log form
2.582
2011–2012
486
0.515
15.525
-0.096
-0.027
0.030
-0.054
-0.082
0.093
0.020
0.404
-0.373
2.865
0.293
0.400
Regression coefficients
Regression coefficients
t values
Poverty gap ratio
Poverty HCR
Dependent variables
2004–2005
Time
Independent variables
2.55
-8.41
-2.38
3.43
-2.48
-7.55
6.10
2.31
1.08
-0.66
5.13
0.52
0.90
t values
486
0.370
0.066
0.000
0.000
0.000
0.000
0.000
0.000
0.000
-0.001
0.018
0.058
0.004
0.014
Regression coefficients
Gini index
Table 5 Result of regression coefficient with poverty HCR, poverty gap ratio and gini index in regions of India, 1993–2012
0.82
1.35
0.44
-2.69
-0.93
0.23
-0.38
0.00
-0.29
2.38
7.86
0.51
2.42
t values
486
0.443
3.873
-0.005
0.000
-0.002
0.000
-0.002
0.011
0.008
-0.350
0.010
1.575
0.500
0.511
Regression coefficients
Rich–poor ratio
2.59
-1.61
-0.08
-1.14
-0.06
-0.65
2.92
3.76
-3.81
0.07
11.50
3.64
4.68
t values
R. K. Chauhan et al.
Regional Estimates of Poverty and Inequality in India, 1993–2012
5 Conclusion In last two decades, India has experienced sustained economic growth and reduction in money-metric poverty across states and among socio-economic groups. However, the economic inequality is said to have increased over time and across states. Though there has been increasing interest in estimating poverty and inequality in India, there are a limited number of studies that provides trends in estimates of poverty and inequality at subnational level. Estimating poverty and inequality at sub-national level is useful for national and state government, academia and international organisations. The first step in this direction is to document the extent of poverty and inequality and than explore the determinants of poverty and inequality. We have analysed the unit level data of consumption expenditure of NSSO and made comparable estimates of poverty and inequality in regions of India. We have estimated the incidence of poverty (poverty HCR) and the depth of poverty (poverty gap ratio) to understand the change in poverty in regions of India. Two measures of inequality, namely, the gini index and the rich–poor ratio are also computed to depict the pattern of inequality in regions of India. These estimates are comparable over time as we have used the uniform methodology and made regions comparable by making backward and forward approach. We have following findings. First, our results indicate a significant reduction in poverty level in regions of India. While the poverty head count ratio has decreased in 74 regions, it has remained same in four regions and has moderately increased in three regions. While some regions have spectacular reduction in poverty level, the southern regions of Orissa and Chhattisgarh continued to have higher incidence of poverty. Second, regional disparity in poverty level has increased suggesting divergence in poverty level in regions of India. The spread of poverty head count ratio among regions has increased from 0.38 to 0.64 in study period. Third, not only the poverty level varies among regions in India, it is also higher within the states of India. The poverty level in Eastern Maharashtra is about four times that of coastal Maharashtra. Fourth, reduction in poverty is not accompanied with a reduction in inequality. In most of the regions, economic inequality, measured by gini index and rich–poor ratio has increased in over time. The inequality is more in developed region and low in under-developed regions.
5.1 Limitations We acknowledge few limitations owing the measurement issues of poverty and inequality and the size and volume of work. The official estimation of poverty use consumption expenditure data using a fixed basket of goods and services, fixed threshold limit and the use of price index. This is beyond our scope as these are implicit in the data set. Second, we confined the analyses to a trend analyses and emphasize on documenting the extent of poverty and inequality. We could not explore the reasons of such change and determinants owing to volume of work. The next step is possibly to supplement the reasons of decline or increase and a detailed multilevel analyses on poverty and inequality in India. Despite these limitations, this is the first ever study that provides the comparable estimates of trends in poverty and inequality in regions of India.
Appendix 1 See Table 6.
123
123
State/UT
Andaman and Nicobar Islands
Andhra Pradesh
Arunachal Pradesh
S. no.
1
2
3
1
4
1
4
1
5
1
1
5
1
1
1
0
0
0
Unmatched
Matched
61
50
68
Matching status to 68 round regions
Number of regions
Table 6 Comparison of NSS regions in 50, 61 and 68 rounds
68
1
1
68 Pooled estimates for 55/61 were generated and used against estimates of single region of 68 round
South-Western and Inland Southern region of 50/61 were pooled together to form new region Inland Southern during 68 round
–
2
68
Estimates of Inland Northern region for 55/61 were repeated for two regions of 68
Inland Northern region of 50/61 was also divided into 2 regions Inland North Western and Inland North Eastern
No change
2
68
Estimates of costal region for 55/61 were repeated for two regions of 68
1
Number of resultant regions
Costal region of 50/61 was divided into 2 regions during 68 round— Costal Northern and Costal Southern
Basis of regional classification followed 68
Treatment
–
No change
Remark on comparison
R. K. Chauhan et al.
Bihar
5
Chandigarh
Assam
4
6
State/UT
S. no.
Table 6 continued
1
2
3
1
2
3
1
2
4
1
0
0
0
2
4
Unmatched
Matched
68
50
61
Matching status to 68 round regions
Number of regions
No change
State was divided and bifurcated state of Bihar had two regions Central and Northern regions. Between 50/61 and 66 rounds there were two districts Begusarai and Khagaria were moved from central region to Northern region
The composition of all the three regions namely Plain Western, Plain Eastern and Hills for 50 and 61 rounds got altered by reshuffling of districts. In 50th round districts of Dhemaji, Karimgang and Hailakandi were in Plain western region and in 61st round they were included in Plain Eastern region. Likewise districts of Bongaigaon, Barpeta, Sonitpur and Nalbari of plain eastern and district Kokrajhar of Hill region were included in Plain western in 61 round. While comparing 61 and 68 round it is found that some districts of Plains Eastern and hill region in 61 round were reorganised into two distinct regions namely Catcher Plains and Central Brahamputra Plains in 68 round. Thus regions kept reorganising during three periods
Remark on comparison
1
2
50 For technical reasons of comparability regions of 50th rounds were kept as reference
68
3
50
Since design of 50th round had urban stratum formation at the region level. But keeping regions of 61 or 68 round as reference would mean reorganizing within the regions of 50 round which will not be technically viable. On the other hand in 61 and 68 rounds sample were drawn at the district level so reorganizing them to the equivalent of 50th round would not be a challenge. Newly created districts in 68 round frame were mapped through their parent districts/regions and were allotted accordingly. Thus regions of 50 round were kept as reference
–
Number of resultant regions
Basis of regional classification followed
Treatment
Regional Estimates of Poverty and Inequality in India, 1993–2012
123
State/UT
Chhattisgarh
Dadra and Nagar Haveli
Daman and Diu
Goa
Gujarat
S. no.
7
8
9
10
11
Table 6 continued
123
1
5
5
1
1
1
1
1
1
1
5
1
1
1
3
0
1
1
1
3
5
0
0
0
0
Unmatched
Matched
68
50
61
Matching status to 68 round regions
Number of regions
In 50th round seven districts were partly included in more than one region. Districts of Panch Mahals, Vadodara, Bharuch, Surat and Valsad were concurrently present in two regions namely Eastern and Plains Southern. Likewise Mehsana was part of two regions of Plains Northern and Dry Area and District Sabar Kantha was included in regions of Plains Northern and Eastern regions. Later these seven districts were included in totality like other regions of India in 61 round. Saurashtra region was kept as it is between the periods except few new districts were added vertically in 68 round
No change
No change
No change
One region namely Chhattisgarh of 50/61 round was vertically divided into three regions namely Northern Chhattisgarh, Mahanadi Basin and Southern Chhattisgarh
Remark on comparison
1 2
68 New
1
–
68
1
Thus these four regions can not be made comparable with other rounds as in 50th round parts of the districts were present in each of these rounds. Saurastra was the only region which was comparable. We kept Saurashtra and rest of Gujarat as another region at the place of 5 regions
–
68
3
68
For new regions of 68 round estimates of parent region from 55/61 were repeated
–
Number of resultant regions
Basis of regional classification followed
Treatment
R. K. Chauhan et al.
6
6
2
1
Lakshadweep
Madhya Pradesh
Maharashtra
Manipur
Meghalaya
Mizoram
Nagaland
18
19
20
21
22
23
24
4
1
1
1
2
Karnataka
1
Kerala
Jharkhand
15
3
16
Jammu & Kashmir
14
2
1
2
1
1
1
2
6
6
1
2
4
1
3
1
2
1
1
1
2
6
6
1
2
4
2
4
2
2
1
1
1
2
6
6
1
2
4
1
4
2
0
0
0
0
0
0
0
0
0
0
0
0
0
Unmatched
Matched
68
50
61
Matching status to 68 round regions
Number of regions
17
Haryana
Himachal Pradesh
12
13
State/UT
S. no.
Table 6 continued
No change
No change
No change
No change
No change
Out of seven regions six were intact in all the rounds and seventh became separate state of Chhattisgarh
No change
No change
No change
Southern region of Bihar became state of Jharkhand in 61 round and in 68 round it was further divided into two regions Ranchi Plateau and Hazaribagh Plateau
Out of three regions Mountainous, Outer Hills and Jhelam Valley of 50/61 round first two were intact in 68th round. The third one got vertically divided into two regions of Jhelam Valley and Laddakh
One region of HP in 50/61 was vertically divided into two regions of Central and ‘Trans Himalayan and Southern’ in 68 round
No change
Remark on comparison
–
–
–
–
68
68
68
68
68
68
–
68
–
68 Six were included as it is
–
68
1
1
1
2
6
6
1
2
4
2
68
Estimates of one region Southern/ Jharkhand from 50/61 round were repeated for two regions of 68
–
4
68
For new regions of 68 round estimates of parent region from 55/61 were repeated
2 2
68 68
Number of resultant regions
–
Basis of regional classification followed
One estimate of 50/61 was repeated for the two regions of 68
Treatment
Regional Estimates of Poverty and Inequality in India, 1993–2012
123
123
Sikkim
Tamil Nadu
Tripura
30
32
Rajasthan
29
31
Pondicherry
Punjab
Odisha
26
27
NCT of Delhi
25
28
State/UT
S. no.
Table 6 continued
1
4
1
4
2
1
3
1
1
4
1
4
2
1
3
1
1
4
1
5
2
1
3
1
1
4
1
2
0
1
0
1
0
0
0
3
2
0
3
0
Unmatched
Matched
68
50
61
Matching status to 68 round regions
Number of regions
No change
No change
No change
Districts of Ganganagar, Hanumangarh, Churu and Nagaur of western region and Jhunjhunu and Sikar of North eastern region were later included in Northern region
District Ludhiana switched position from Northern region in 50/61 to Southern region in 68
No change
Three regions of Costal, Northern and Southern experienced a change in composition from 61 to 68 rounds. Districts of Ganjam and Gajapati were in Costal region for 50/61 rounds and were included in Southern region for 68 round. Likewise districts Sonapur and Balangir switched positions from Northern to Southern region
No change
Remark on comparison
–
–
68
68
68
50
Thus regional reference of 50th round was kept
–
68 50
–
1
4
1
4
2
1
3
50
Thus all the regions experienced an alteration in their composition over time. Thus for reasons of comparability regions of 50th round were kept for reference
Thus regional reference of 50th round was kept
1
Number of resultant regions
68
Basis of regional classification followed
–
Treatment
R. K. Chauhan et al.
4
78
Uttarakhand
West Bengal
Total regions
34
35
1
4
Uttar Pradesh
33
78
4
1
4
88
5
1
5
65
5
1
1
23
0
0
4
Unmatched
Matched
68
50
61
Matching status to 68 round regions
Number of regions
State/UT
S. no.
Table 6 continued
Region central Plains of 50/61 round was vertically divided into Central Plains and Southern Plains in 68 round and rest three remained unchanged
No change
There were 5 regions of Uttar Pradesh during 50 round and in 61 round Himalayan region was broadly become state of Uttarakhand except for two districts of Bareilly and Hardwar which switched their positions between Western and Himalayan regions between 55 and 61 rounds. In 68 round western region was reorganised into two regions of Northern Upper Plain and Southern Upper Plain. Kheri District of Central region in 50/61 round was included in Southern Upper Ganga region in 68 round. Likewise Sonebhadra was in Western region in 50th round and was included in Eastern region in 61/68 round
Remark on comparison
82
1 5
68 68
–
4
50
Thus composition of Western, Central and Eastern regions was changed in time period under consideration. So regional classification of 50 round after excluding Himalayan region was kept as reference with consideration that Bareilly fell in UP so was included and Hardwar does not fall in UP so was excluded
For two regions of 68 round estimates of parent region of 50/61 were repeated
Number of resultant regions
Basis of regional classification followed
Treatment
Regional Estimates of Poverty and Inequality in India, 1993–2012
123
8. Dadra Nagar Haveli 9. Daman & Diu 10. Goa 11. Gujarat
6. Chandigarh 7. Chhattisgarh
5. Bihar
3. Arunachal Pradesh 4. Assam
1. Andaman & Nicobar Islands 2.Andhra Pardesh
State
20. Gujarat excl Saurashtra
14. Northern Chhattisgarh 15. Mahanadi Basin 16. Southern Chhattisgarh 17. DN Haveli 18. Daman & Diu 19. Goa
11. Northern 12. Central 13.Chandigarh
8. Plains Eastern 9. Plains Western 10. Hills
2. Coastal Northern 3. Coastal Southern 4. Inland North Western 5. Inland North Eastern 6. Inland Southern 7. Arunachal Pradesh
India 1. Andaman & Nicobar Islands
Regions
1993-94 45.7 4.0 44.9 47.7 47.7 41.7 41.7 44.1 56.0 52.5 44.7 57.3 52.0 60.8 65.2 54.7 14.8 51.3 51.3 51.3 51.3 69.2 17.9 21.3 38.4 40.2
2004-05 37.8 2.3 29.9 22.2 22.2 31.0 31.0 46.0 31.9 35.2 34.6 34.1 56.2 54.6 53.4 56.3 12.7 51.0 51.0 51.0 51.0 58.1 6.6 25.9 32.5 36.4
2011-12 22.0 1.0 11.0 13.4 4.1 5.8 8.3 15.8 35.3 33.9 30.7 32.7 41.2 34.4 31.8 37.5 20.8 44.6 35.2 38.7 55.3 42.9 4.9 5.4 21.5 19.0
1993-94 36
55 56 54 79 8 11
72 60 4
43 64 57
47 46 37 38 41 63
1
50
64 66 65 77 4 26
69 74 8
48 45 73
20 19 36 37 57 40
1
2004-05
Ranks among regions
42
66 71 80 76 5 6
59 68 46
58 62 74
33 3 8 16 37 67
1
2011-12
Combined HCR
Table 7 Trends in estimates of poverty head count ratio in regions of India (1993–2012)
1993-94 50.2 4.8 48.2 50.2 50.2 46.6 46.6 46.7 60.5 55.3 47.5 60.1 55.5 62.5 65.9 57.4 30.7 56.1 56.1 56.1 56.1 71.9 20.1 25.5 43.3 46.3
Rural HCR
41.9 4.3 32.3 23.6 23.6 34.4 34.4 48.2 33.2 36.6 35.9 35.5 58.1 55.7 53.7 58.7 29.4 55.1 55.1 55.1 55.1 63.6 2.4 28.1 39.1 45.0
2004-05
See Table 7.
2011-12 25.4 1.6 5.8 15.9 4.3 8.8 8.8 16.2 38.9 20.6 31.9 34.2 43.2 31.2 31.8 38.6 1.6 24.0 38.9 43.5 56.7 62.6 0.0 6.8 10.2 24.8
31.9 2.0 35.3 40.8 40.8 27.7 27.7 36.8 22.6 27.8 21.5 32.8 13.7 44.8 55.6 38.1 12.4 28.4 28.4 28.4 28.4 34.7 14.6 15.5 28.2 26.9
25.6 0.8 22.7 18.3 18.3 20.9 20.9 38.6 21.1 21.8 21.3 21.2 36.7 43.7 45.3 43.1 10.7 28.4 28.4 28.4 28.4 16.8 14.4 22.2 19.8 18.9
2011-12 13.7 0.0 9.3 7.1 3.5 3.0 6.6 14.7 20.3 32.5 21.0 19.8 23.8 34.1 31.7 31.0 22.3 40.2 2.2 23.6 45.4 15.4 12.6 4.1 17.0 10.3
Urban HCR 1993-94
123 2004-05
Appendix 2
23.7 3.0 33.9 34.3 43.6 35.9 33.4 28.3 20.7 18.6 14.0 24.6 10.8 26.4 33.4 17.2 -6.0 6.7 16.1 12.6 -4.0 26.3 13.0 15.9 16.9 21.2
Change 1993-2012
R. K. Chauhan et al.
18. Lakshadweep 19. Madhya Pradesh
17. Kerala
16. Karnataka
15. Jharkhand
14. Jammu & Kashmir
13. Himachal Pradesh
12. Haryana
State
38. Vindhya 39. Central 40. Malwa 41. South 42. South Western 43. Northern
35. Northern 36. Southern 37. Lakshadweep
31. Coastal & Ghats 32. Inland Eastern 33. Inland Southern 34. Inland Northern
29. Ranchi Plateau 30. Hazaribagh Plateau
26. Mountainous 27. Outer Hills 28. Jhelum Valley
24. Central 25. Trans Himalayan & Southern
22. Eastern 23. Western
India 21. Saurashtra
Regions
1993-94
45.7 32.5 36.0 38.8 31.3 35.0 35.0 35.0 26.7 19.7 50.6 50.6 61.1 61.1 61.1 50.3 25.1 35.9 46.1 61.2 31.6 35.3 29.2 10.1 44.7 44.0 55.8 33.8 49.4 68.4 27.7
2004-05
37.8 18.7 24.2 21.5 29.0 23.0 23.0 23.0 12.6 4.9 32.1 14.2 47.3 47.3 47.3 33.9 29.4 18.4 18.9 49.8 19.3 30.2 12.1 5.1 49.2 54.9 56.0 38.2 59.9 50.1 41.3
2011-12
22.0 9.3 11.6 9.4 14.6 8.5 9.3 6.4 11.5 4.3 24.8 5.6 40.8 34.8 39.6 24.5 12.1 17.7 7.0 34.2 9.2 10.8 6.0 1.7 35.7 42.5 21.1 15.6 49.8 43.2 26.1
1993-94
40 62 24 50 78 14
28 15 2
13 30 44 70
68 69
9 52 51
26 27
35 19
22
2004-05
71 72 52 78 62 53
35 7 3
34 15 17 61
59 58
2 42 9
21 22
18 33
16
75 47 36 79 77 53
28 9 2
31 38 13 63
65 73
4 51 7
22 11
23 34
21
2011-12
1993-94
50.2 32.9 40.1 44.7 33.4 36.9 36.9 36.9 32.6 24.0 58.9 58.9 65.8 65.8 65.8 56.7 29.9 37.9 59.1 64.6 34.0 37.7 31.6 3.6 49.0 46.1 63.8 36.3 56.8 74.0 27.4
Rural HCR
41.9 16.4 24.8 23.0 27.8 25.0 25.0 25.0 14.3 5.0 34.8 15.6 51.9 51.9 51.9 37.5 27.0 17.8 27.5 49.6 19.6 30.0 12.3 0.0 53.6 59.7 64.5 42.1 64.5 53.2 40.1
2004-05
Ranks among regions 2011-12
25.4 8.6 10.3 9.5 14.6 4.3 9.5 7.1 7.2 3.7 26.2 5.0 24.8 38.9 42.1 15.3 12.7 16.9 11.9 34.3 5.0 12.0 6.9 0.0 21.0 43.9 20.2 19.2 57.7 47.2 25.7
31.9 31.7 24.2 24.8 22.5 13.6 13.6 13.6 6.9 7.0 6.8 6.8 41.8 41.8 41.8 34.3 9.0 28.5 25.1 50.5 24.2 27.3 22.4 16.4 32.1 31.0 38.7 28.5 30.7 43.0 28.5
25.6 22.5 22.4 18.2 33.9 4.6 4.6 4.6 6.5 4.7 11.3 8.0 23.8 23.8 23.8 25.7 38.2 20.5 7.9 50.4 18.5 30.9 11.6 10.5 35.1 28.3 36.6 28.6 39.6 39.0 44.5
2011-12
13.7 10.1 11.2 9.2 14.5 8.0 6.6 3.3 10.6 5.6 10.8 7.5 37.5 21.3 28.4 21.2 10.5 20.2 2.5 33.9 8.1 7.2 3.4 3.4 32.0 35.0 22.5 7.4 24.1 28.1 27.4
Urban HCR 1993-94
Combined HCR 2004-05
Table 7 continued
23.7 23.2 24.4 29.4 16.7 26.5 25.7 28.6 15.2 15.4 25.8 45.0 20.3 26.3 21.5 25.8 13.0 18.2 39.1 27.0 22.4 24.5 23.2 8.4 9.0 1.5 34.7 18.2 -0.4 25.2 1.6
Change 1993-2012
Regional Estimates of Poverty and Inequality in India, 1993–2012
123
123
30. Sikkim 31. Tamil Nadu
29. Rajasthan
27. Pondicherry 28. Punjab
22. Meghalaya 23. Mizoram 24. Nagaland 25. NCT of Delhi 26. Odisha
21. Manipur
20. Maharashtra
State
67. Coastal Northern
62. Western 63. North-Eastern 64. Southern 65. South-Eastern 66. Sikkim
60. Northern 61. Southern
56. Coastal 57. Southern 58. Northern 59. Pondicherry
50. Plains 51. Hills 52. Meghalaya 53. Mizoram 54. Nagaland 55. Delhi
44. Coastal 45. Inland Western 46. Inland Northern 47. Inland Central 48. Inland Eastern 49. Eastern
India
Regions
1993-94 45.7 48.6 17.3 42.9 63.3 68.3 65.7 66.5 65.5 65.3 65.7 36.0 13.4 20.6 15.8 59.5 58.0 76.6 52.9 24.9 22.4 17.4 29.6 38.4 35.9 31.7 58.7 47.2 32.0 45.0 49.0
2004-05 37.8 38.9 17.7 27.5 51.9 61.3 49.7 56.5 38.0 27.8 56.4 15.4 17.1 8.3 11.2 57.7 43.6 78.0 66.1 14.5 21.0 15.7 28.4 34.5 37.7 28.9 50.3 28.6 31.1 30.7 31.2
2011-12 22.0 24.2 9.2 9.4 28.7 22.0 25.6 32.7 38.8 31.9 46.8 11.8 22.0 18.7 10.1 35.7 20.3 58.5 37.7 10.0 7.7 8.9 7.4 16.1 13.3 8.8 38.5 20.4 8.8 15.8 18.2
1993-94 49
32 20 67 45 21
7 16
66 81 58 12
73 74 33 3 10 5
6 39 71 77 75 76
2004-05 39
51 32 63 31 38
12 30
55 81 80 10
28 75 11 13 5 6
14 27 68 79 60 76
39
32 17 70 45 18
19 15
44 81 69 25
60 78 30 48 40 27
20 24 55 49 52 61
2011-12
1993-94 50.2 59.3 33.9 46.4 68.6 70.9 72.8 70.4 64.8 63.9 66.2 38.0 16.6 20.1 16.2 63.2 60.2 80.8 57.9 25.6 20.4 14.6 27.8 40.9 40.0 31.0 62.8 49.8 33.0 51.2 60.7
Rural HCR
41.9 47.9 44.0 27.1 54.9 61.7 54.3 63.2 39.1 24.5 56.6 14.0 23.0 10.0 0.0 60.8 44.6 80.7 71.6 22.9 22.1 15.7 29.9 35.8 40.4 27.3 55.0 29.6 31.8 37.5 45.4
2004-05
Ranks among regions 2011-12 25.4 9.1 35.4 10.2 33.4 22.4 28.4 37.7 32.4 32.6 45.9 12.5 35.4 19.9 12.9 17.3 22.1 60.5 40.8 17.1 9.2 7.8 7.5 10.7 14.5 8.5 42.2 19.2 9.9 6.6 30.3
31.9 30.5 9.9 34.3 48.9 59.4 52.6 44.0 67.3 68.1 61.3 23.6 6.5 22.1 15.7 34.5 42.5 40.8 22.9 24.5 27.4 23.3 34.9 30.0 22.1 33.7 26.5 38.0 20.4 33.7 32.6
25.6 25.6 7.9 28.2 44.8 60.3 41.2 31.4 34.5 33.6 51.4 24.7 7.9 4.3 11.7 37.8 37.4 46.4 36.1 9.9 18.5 15.9 24.1 29.7 27.5 33.2 20.5 23.8 26.0 19.7 16.0
2011-12 13.7 17.3 1.9 8.1 20.5 21.1 20.3 11.6 37.1 30.9 91.7 9.3 6.4 16.5 9.8 32.9 12.0 37.7 20.1 6.3 8.2 10.5 7.0 14.8 9.0 9.5 4.8 24.6 3.7 11.7 7.5
Urban HCR 1993-94
Combined HCR 2004-05
Table 7 continued
23.7 24.4 8.1 33.5 34.6 46.3 40.1 33.8 26.7 33.4 18.9 24.2 -8.6 1.9 5.7 23.8 37.7 18.1 15.2 14.9 14.7 8.5 22.2 22.3 22.6 22.9 20.2 26.8 23.2 29.2 30.8
Change 1993-2012
R. K. Chauhan et al.
34. Uttarakhand 35. West Bengal
32. Tripura 33. Uttar Pradesh
State
77. Himalayan 78. Eastern Plains 79. Southern Plains 80. Central Plains 81. Western Plains
72. Western 73. Central 74. Eastern 75. Southern 76. Uttarakhand
India 68. Coastal 69. Southern 70. Inland 71. Tripura
Regions
1993-94 45.7 35.8 50.9 38.6 33.2 48.6 35.9 54.0 55.6 70.1 33.8 40.0 57.7 48.0 29.8 29.8 44.6
2004-05 37.8 23.7 34.1 31.9 41.4 41.1 33.8 34.4 51.2 45.4 32.6 34.9 28.3 54.5 23.7 23.7 36.1
2011-12 22.0 6.6 10.0 7.4 14.9 30.4 20.1 39.2 34.3 29.5 11.4 22.5 24.1 29.3 6.0 18.9 27.9
1993-94 65 48 18 17 42
31 59 61 80 25
29 53 34 23
2004-05 29 70 23 25 49
44 47 67 56 43
24 46 41 54
50 56 10 41 54
43 72 64 57 29
12 26 14 35
2011-12
1993-94 50.2 36.7 55.3 44.7 34.4 51.0 36.6 58.7 57.9 68.4 37.0 42.6 59.4 48.5 32.2 32.2 44.0
Rural HCR
41.9 26.3 37.6 38.4 44.5 42.8 33.7 37.5 52.4 44.7 34.5 38.2 27.8 56.0 26.5 26.5 36.8
2004-05
Ranks among regions 2011-12 25.4 7.8 13.0 7.7 16.2 26.2 19.8 42.2 34.4 30.2 11.7 14.7 25.7 28.2 7.4 18.5 28.5
31.9 32.7 42.3 26.9 25.4 38.4 33.8 36.7 39.8 76.4 20.0 31.3 44.5 44.5 26.2 26.2 50.9
25.6 15.6 28.0 20.9 22.5 34.1 33.9 23.9 41.6 48.2 26.3 24.5 32.2 44.6 19.7 19.7 28.4
2011-12 13.7 3.3 6.1 6.9 7.4 29.5 21.1 30.2 33.8 26.9 10.5 20.4 16.1 37.6 4.6 19.7 23.2
Urban HCR 1993-94
Combined HCR 2004-05
Table 7 continued
23.7 29.2 40.9 31.2 18.3 18.2 15.8 14.8 21.3 40.6 22.4 17.5 33.6 18.7 23.8 10.9 16.7
Change 1993-2012
Regional Estimates of Poverty and Inequality in India, 1993–2012
123
123
7. Chhattisgarh
6. Chandigarh
5. Bihar
4. Assam
3. Arunachal Pradesh
9.2
9.2
4. Inland North Western
5. Inland North Eastern
12.2
8.2
9. Plains Western
10. Hills
11.3
2.9
13.4
12. Central
13. Chandigarh
17.0
11. Northern
15.5
8.6
10.7
15.5
8. Plains Eastern
7. Arunachal Pradesh
10.5
11.7
3. Coastal Southern
6. Inland Southern
11.7
2. Coastal Northern
10.5
0.5
2. Andhra Pradesh
11.2
1. Andaman and Nicobar Islands
12.7
2.8
13.0
12.3
12.6
7.0
6.4
7.2
6.9
7.1
10.7
6.0
6.0
4.9
4.9
6.4
0.2
8.4
8.2
3.9
7.6
5.4
6.3
7.0
5.9
4.9
5.6
8.8
2.3
1.2
0.7
0.4
2.4
1.4
0.1
4.0
0.245
0.361
0.231
0.213
0.223
0.178
0.205
0.219
0.211
0.297
0.272
0.292
0.292
0.272
0.272
0.281
0.301
0.300
0.330
0.381
0.240
0.210
0.223
0.150
0.241
0.233
0.235
0.263
0.309
0.341
0.341
0.319
0.319
0.329
0.373
0.347
2004–2005
0.326
0.391
0.226
0.223
0.225
0.219
0.268
0.261
0.263
0.353
0.285
0.237
0.329
0.286
0.318
0.304
0.345
0.359
2011–2012
1993–1994
2011–2012
1993–1994
2004–2005
Gini index of MPCE (combined)
Poverty gap ratio (combined)
1. Andaman and Nicobar Islands
Region
India
State
Table 8 Trends in estimates of inequality in regions of India, 1993–2012
See Table 8.
Appendix 3
2.88
5.05
2.97
2.83
2.89
2.14
2.49
2.62
2.52
3.90
3.63
3.71
3.71
3.60
3.60
3.65
3.83
3.52
1993–1994
4.17
6.23
2.88
2.73
2.79
1.84
2.92
2.87
2.85
3.56
3.97
4.27
4.27
4.22
4.22
4.20
4.66
3.94
2004–2005
3.90
6.53
2.85
2.88
2.87
2.56
3.17
3.16
3.12
5.23
3.78
2.96
3.96
3.55
4.33
3.76
4.41
3.99
2011–2012
Rich–poor ratio of MPCE combined
R. K. Chauhan et al.
15. Jharkhand
14. Jammu and Kashmir
13. Himachal Pradesh
12. Haryana
6.4
21. Saurashtra
23. Western
6.9
25. Trans Himalayan and Southern
28. Jhelum Valley
29. Ranchi Plateau
11.6
27. Outer Hills
15.5
15.5
2.9
11.6
26. Mountainous
4.8
6.9
24. Central
6.9
8.9
7.3
22. Eastern
8.3
10.1
9.2
4.8
2.8
20.4
20. Gujarat excl Saurashtra
19. Goa
10. Goa
11. Gujarat
17. DN Haveli
16. Southern Chhattisgarh
18. Daman and Diu
11.3
11.3
15. Mahanadi Basin
9. Daman and Diu
11.3
10.4
10.4
1.8
4.6
0.9
1.8
3.9
3.9
3.9
5.8
4.2
4.8
2.9
8.8
7.5
5.1
1.0
16.5
12.7
12.7
12.7
6.5
6.5
0.7
4.4
0.7
1.7
0.7
1.3
1.0
2.6
1.6
2.0
1.0
3.0
2.6
0.7
0.9
11.0
12.9
7.9
5.5
0.277
0.277
0.242
0.242
0.238
0.247
0.275
0.275
0.275
0.298
0.259
0.276
0.209
0.276
0.261
0.274
0.227
0.277
0.245
0.245
0.245
0.300
0.300
0.207
0.192
0.264
0.245
0.305
0.305
0.305
0.255
0.364
0.339
0.229
0.354
0.329
0.328
0.253
0.386
0.330
0.330
0.330
2004–2005
0.336
0.303
0.208
0.261
0.316
0.281
0.315
0.290
0.305
0.265
0.361
0.333
0.268
0.321
0.311
0.297
0.204
0.379
0.324
0.336
0.241
2011–2012
1993–1994
2011–2012
1993–1994
2004–2005
Gini index of MPCE (combined)
Poverty gap ratio (combined)
14. Northern Chhattisgarh
Region
8. Dadra Nagar Haveli
State
Table 8 continued
3.22
3.22
2.62
2.62
2.65
2.64
3.55
3.55
3.55
4.04
3.38
3.64
2.74
3.47
3.28
3.79
2.76
3.37
2.88
2.88
2.88
1993–1994
3.36
3.36
2.57
2.15
3.21
2.80
3.92
3.92
3.92
3.28
5.27
4.60
2.82
4.32
3.93
4.61
2.84
5.09
4.17
4.17
4.17
2004–2005
3.64
3.30
2.64
3.18
4.56
3.31
3.93
3.82
3.87
3.83
4.94
4.59
3.36
3.66
3.59
3.97
2.46
4.16
4.07
4.18
2.28
2011–2012
Rich–poor ratio of MPCE combined
Regional Estimates of Poverty and Inequality in India, 1993–2012
123
123
21. Manipur
20. Maharashtra
19. Madhya Pradesh
18. Lakshadweep
17. Kerala
16. Karnataka
State
Table 8 continued
7.4
11.7
17.0
33. Inland Southern
34. Inland Northern
6.7
14.3
7.7
13.6
22.9
5.3
39. Central
40. Malwa
41. South
42. South Western
43. Northern
10.1
18.4
24.2
19.7
19.7
45. Inland Western
46. Inland Northern
47. Inland Central
48. Inland Eastern
49. Eastern
13.0
3.3
44. Coastal
14.0
9.7
38. Vindhya
11.5
1.7
36. Southern
37. Lakshadweep
8.2
35. Northern
7.3
4.8
32. Inland Eastern
13.2
15.5
5.6
17.6
12.4
16.9
14.6
4.6
4.2
9.7
8.2
10.0
15.5
8.7
15.5
13.2
11.6
1.9
2.4
6.9
4.2
10.0
2.9
2.3
6.9
6.4
10.4
6.4
6.5
6.7
4.8
2.8
5.5
1.1
2.8
3.2
4.2
8.9
13.1
3.4
3.5
10.8
7.2
0.2
1.0
1.9
1.4
5.5
0.9
2.2
1.2
3.2
0.277
0.151
0.262
0.299
0.323
0.274
0.285
0.322
0.348
0.264
0.304
0.342
0.268
0.315
0.243
0.297
0.246
0.298
0.265
0.288
0.264
0.305
0.239
0.277
0.287
0.161
0.355
0.336
0.294
0.331
0.311
0.386
0.381
0.261
0.269
0.289
0.381
0.333
0.290
0.326
0.267
0.362
0.336
0.366
0.260
0.386
0.258
0.373
0.354
0.300
2004–2005
0.200
0.303
0.336
0.264
0.315
0.314
0.401
0.371
0.301
0.244
0.328
0.307
0.393
0.277
0.330
0.278
0.391
0.318
0.379
0.257
0.409
0.278
0.390
0.388
0.266
2011–2012
1993–1994
2011–2012
1993–1994
2004–2005
Gini index of MPCE (combined)
Poverty gap ratio (combined)
31. Coastal and Ghats
30. Hazaribagh Plateau
Region
2.05
3.09
3.77
4.57
3.39
3.64
4.06
3.86
3.45
3.85
4.39
3.46
3.93
3.10
3.66
3.06
4.23
3.68
4.02
3.46
3.69
3.02
3.33
3.47
3.22
1993–1994
2.06
4.43
4.32
3.86
4.35
4.08
5.07
4.47
3.27
3.09
3.25
5.15
4.09
3.39
3.85
2.64
5.56
4.92
5.34
3.12
4.28
3.07
5.37
3.79
3.36
2004–2005
2.57
3.63
4.40
3.20
4.11
3.94
5.33
4.40
3.57
2.93
4.05
3.87
5.61
3.64
3.96
3.27
6.11
4.31
5.39
3.19
5.37
3.25
5.44
4.37
3.03
2011–2012
Rich–poor ratio of MPCE combined
R. K. Chauhan et al.
31. Tamil Nadu
30. Sikkim
29. Rajasthan
28. Punjab
27. Pondicherry
3.2
4.8
5.8
65. South-Eastern
13.9
8.0
13.5
7.9
67. Coastal Northern
68. Coastal
69. Southern
70. Inland
11.5
5.6
12.2
64. Southern
66. Sikkim
6.7
14.8
63. North-Eastern
6.6
62. Western
8.4
3.0
61. Southern
4.1
60. Northern
59. Pondicherry
23.0
13.4
58. Northern
15.1
3.6
57. Southern
25. NCT of Delhi
13.2
54. Nagaland
55. Delhi
24. Nagaland
2.4
6.1
56. Coastal
53. Mizoram
23. Mizoram
26. Odisha
52. Meghalaya
12.3
14.5
51. Hills
3.7
6.9
6.6
3.6
6.6
6.1
5.4
5.3
10.9
5.2
7.7
6.7
5.5
2.2
3.6
2.3
19.1
29.1
9.4
16.3
1.8
0.9
2.5
1.6
9.0
5.4
0.9
1.3
0.9
3.3
1.9
0.9
3.9
8.2
1.6
2.4
2.8
1.1
1.5
1.3
1.8
7.4
12.9
3.4
6.4
1.6
3.1
4.3
1.6
8.6
0.147
0.299
0.290
0.271
0.359
0.318
0.229
0.261
0.330
0.236
0.231
0.252
0.247
0.248
0.251
0.279
0.274
0.266
0.244
0.263
0.324
0.186
0.193
0.285
0.157
0.352
0.307
0.309
0.414
0.364
0.268
0.284
0.287
0.255
0.271
0.269
0.316
0.313
0.318
0.333
0.320
0.307
0.271
0.306
0.332
0.243
0.235
0.204
0.129
0.158
2004–2005
0.340
0.294
0.275
0.375
0.336
0.237
0.277
0.299
0.280
0.236
0.273
0.328
0.280
0.302
0.277
0.309
0.247
0.286
0.299
0.376
0.222
0.294
0.234
0.200
0.196
2011–2012
1993–1994
2011–2012
1993–1994
2004–2005
Gini index of MPCE (combined)
Poverty gap ratio (combined)
50. Plains
Region
22. Meghalaya
State
Table 8 continued
3.84
3.85
3.64
5.00
4.19
2.79
3.47
3.98
3.16
2.91
3.19
3.32
3.27
3.29
3.58
3.31
3.08
3.02
3.13
5.15
2.42
2.31
3.35
2.10
2.03
1993–1994
4.64
3.89
3.70
5.32
4.53
3.26
3.34
3.29
3.17
3.42
3.28
4.26
4.18
4.21
4.43
3.88
3.81
3.46
3.65
4.92
2.74
2.72
2.30
1.87
2.15
2004–2005
4.64
3.89
3.50
4.99
4.38
2.49
3.46
3.29
3.56
2.86
3.28
4.48
3.78
4.08
3.76
3.73
3.00
3.44
3.48
5.84
2.75
3.40
2.61
2.56
2.58
2011–2012
Rich–poor ratio of MPCE combined
Regional Estimates of Poverty and Inequality in India, 1993–2012
123
123
35. West Bengal
34. Uttarakhand
7.7
14.0
21.3
74. Eastern
75. Southern
11.0
10.6
6.4
6.4
8.6
77. Himalayan
78. Eastern Plains
79. Southern Plains
80. Central Plains
81. Western Plains
8.3
6.1
15.6
73. Central
76. Uttarakhand
8.0
12.4
8.2
4.2
4.2
12.4
5.3
7.3
5.5
11.1
11.8
8.0
6.3
8.9
8.8
5.2
3.2
0.7
5.1
3.3
3.4
1.3
6.5
6.8
7.9
3.2
5.6
2.1
0.232
0.313
0.313
0.283
0.176
0.296
0.265
0.254
0.248
0.280
0.276
0.275
0.237
0.289
0.360
0.360
0.280
0.236
0.339
0.282
0.266
0.259
0.334
0.294
0.297
0.265
2004–2005
0.312
0.304
0.389
0.256
0.261
0.347
0.308
0.288
0.295
0.332
0.332
0.324
0.252
2011–2012
1993–1994
2011–2012
1993–1994
2004–2005
Gini index of MPCE (combined)
Poverty gap ratio (combined)
72. Western
71. Tripura
32. Tripura
33. Uttar Pradesh
Region
State
Table 8 continued
2.99
3.98
3.98
3.64
2.19
3.56
3.17
3.36
3.18
3.64
3.73
3.50
3.17
1993–1994
3.93
4.60
4.60
3.36
2.91
4.05
3.47
3.42
3.30
4.34
3.76
3.70
3.13
2004–2005
4.08
3.89
4.88
3.13
2.90
4.00
3.89
3.36
3.88
4.18
4.45
4.16
3.00
2011–2012
Rich–poor ratio of MPCE combined
R. K. Chauhan et al.
7. Chhattisgarh
6. Chandigarh
5. Bihar
4. Assam
3. Arunachal Pradesh
2. Andhra Pradesh
1. Andaman and Nicobar Islands
India
State
3392 3392* 1475
4. Inland North Western
5. Inland North Eastern
6. Inland Southern
14. Northern Chhattisgarh
2125
2125
230
2968
12. Central
13. Chandigarh
3693
11. Northern
5752
200
9. Plains Western
10. Hills
1549 2330
8. Plains Eastern
4079
1304
3685*
3. Coastal Southern
7. Arunachal Pradesh
3685
8552
899
115,354
2796
2796
360
2459
3293
4571
240
1720
2220
4180
1987
1420
3444*
3444
3477*
3477
8341
518
123,356
288
2232
305
2107
2464
34,542
344
1728
1376
3448
1641
1240
1056
1844
1248
1504
6892
560
100,855
0.74
4.26
4.26
24.09
3.19
2.23
1.87
17.05
4.34
6.25
3.66
7.42
5.02
4.13
4.13
3.79
3.79
2.45
26.56
4.28
4.28
26.91
3.31
3.42
2.41
13.43
8.71
7.51
5.45
9.25
5.53
5.41
5.41
6.28
6.28
3.45
49.10
0.88
2004–2005
21.03
6.23
27.19
6.40
7.24
4.95
13.15
8.78
9.52
6.00
9.70
15.59
23.91
18.35
26.25
16.05
8.81
84.52
1.57
2009–2010
1993–1994
2009–2010
1993–1994
2004–2005
Coefficient of variation of poverty HCR (%)
Sample households
2. Coastal Northern
1. Andaman and Nicobar Islands
Region
Table 9 Sample households and coefficient of variation in NSS 50, 61 and 68 rounds in regions of India
See Table 9.
Appendix 4
Regional Estimates of Poverty and Inequality in India, 1993–2012
123
123
16. Karnataka
15. Jharkhand
14. Jammu and Kashmir
13. Himachal Pradesh
12. Haryana
359
640
23. Western
25. Trans Himalayan and Southern
290 290
27. Outer Hills
28. Jhelum Valley
2473*
30. Hazaribagh Plateau 489 530 1858
31. Coastal and Ghats
32. Inland Eastern
33. Inland Southern
5086
2473
29. Ranchi Plateau
2473
1058
26. Mountainous
1348
2275 2275*
24. Central
2275
1097
22. Eastern
2720
1150
21. Saurashtra
4591 3441
19. Goa
10. Goa
318 160
20. Gujarat excl Saurashtra
18. Daman and Diu
11. Gujarat
17. DN Haveli
9. Daman and Diu
2125* 2125*
16. Southern Chhattisgarh
2796*
1840
540
440
5097
3399*
3399
3399
1212
260
919
2391
2543*
2543
2543
960
1760
2620
1071
3174
4245
398
160
240
2796*
1403
464
383
4070
1536
1211
2747
1602
312
799
2713
987
1054
2041
928
1692
9242
864
2560
3424
444
128
192
320
1624
4.26
5.47
10.58
15.42
2.96
3.35
3.35
3.35
10.14
10.14
12.18
9.14
5.88
5.88
5.88
8.90
7.64
6.00
9.65
5.20
4.63
16.94
29.04
9.80
4.26
9.27
15.87
19.30
4.33
3.95
3.95
3.95
12.72
21.31
24.50
11.59
6.49
6.49
6.49
8.46
9.23
6.52
12.20
5.69
5.42
17.74
54.02
15.24
4.28
4.28
2004–2005
23.77
22.21
30.53
7.66
7.24
10.41
6.05
18.61
13.91
28.05
11.48
26.33
19.81
15.89
23.80
17.50
14.73
22.69
9.81
9.13
33.52
39.07
17.08
13.13
7.34
2009–2010
1993–1994
2009–2010
1993–1994
2004–2005
Coefficient of variation of poverty HCR (%)
Sample households
15. Mahanadi Basin
Region
8. Dadra Nagar Haveli
State
Table 9 continued
R. K. Chauhan et al.
41. South
1587
47. Inland Central
48. Inland Eastern
52. Meghalaya
53. Mizoram
54. Nagaland
24. Nagaland
700
1427
1595
490
51. Hills
23. Mizoram
1209
50. Plains
1699
530
1335
46. Inland Northern
49. Eastern
2404 1025
45. Inland Western
3087
9968
1110
44. Coastal
43. Northern
752
1105
40. Malwa
42. South Western
900 1482
39. Central
1072
38. Vindhya
6421
310
2549
36. Southern
37. Lakshadweep
1836
4385
2209
1280
1912
1596
1197
1960
3157
584
1635
1599
1157
2397
2635
10,007
880
760
1040
1353
800
1080
5913
179
2900
2060
4960
2277
1024
1528
1272
672
1886
2558
480
1341
1344
959
1945
1926
7995
672
604
856
1099
668
798
4697
183
2573
1879
4452
1820
16.49
24.38
9.03
8.06
4.29
3.89
6.12
3.17
3.19
4.15
4.71
9.42
2.28
9.34
4.96
6.58
7.95
6.68
6.94
3.04
29.64
5.27
5.65
3.89
3.28
16.73
12.69
11.89
6.62
7.84
5.46
7.67
5.23
4.28
5.76
6.32
9.62
2.73
7.88
8.47
5.36
8.39
5.93
5.24
2.89
44.02
9.16
6.17
5.64
4.43
2004–2005
12.45
12.09
16.70
10.22
6.39
5.90
14.79
10.47
10.90
12.13
16.34
16.67
5.60
14.46
11.71
8.36
17.16
13.04
8.87
4.95
54.29
13.68
12.66
9.46
7.42
2009–2010
1993–1994
2009–2010
1993–1994
2004–2005
Coefficient of variation of poverty HCR (%)
Sample households
35. Northern
34. Inland Northern
Region
22. Meghalaya
21. Manipur
20. Maharashtra
19. Madhya Pradesh
18. Lakshadweep
17. Kerala
State
Table 9 continued
Regional Estimates of Poverty and Inequality in India, 1993–2012
123
123
33. Uttar Pradesh
32. Tripura
31. Tamil Nadu
30. Sikkim
29. Rajasthan
28. Punjab
27. Pondicherry
58. Northern
1648
61. Southern
2047 1866
69. Southern
70. Inland
4984 2478 4801
72. Western
73. Central
74. Eastern
12,863
2090
1340
68. Coastal
71. Tripura
2690
67. Coastal Northern
7943
640
587
65. South-Eastern
66. Sikkim
520
2216
63. North-Eastern
64. Southern
1573
62. Western
4896
2345
60. Northern
3993
390
758 1467
57. Southern
59. Pondicherry
2150
4375
1046
4474
1994
4026
11,173
2320
1998
2160
1479
2639
8276
1120
679
640
2022
1830
5171
1821
2457
4278
720
1755
1000
2258
5013
1122
901
3310
1504
3475
8993
1856
1624
1784
1248
1982
6638
768
544
480
1676
1436
4136
1367
1748
3115
576
1439
896
1695
4030
2.51
3.95
3.99
1.87
8.51
5.65
4.49
6.66
5.53
2.91
13.18
9.23
7.68
5.99
5.96
3.72
5.87
8.32
5.09
17.81
5.12
3.43
4.29
2.73
32.38
2.66
5.32
4.63
2.19
4.63
7.41
5.40
8.26
6.20
3.43
8.78
13.64
8.66
7.00
5.09
3.87
6.66
8.45
5.53
21.92
3.43
3.83
5.09
2.72
17.72
2004–2005
4.90
5.80
7.17
3.40
12.46
17.47
15.36
21.24
11.01
7.84
24.10
19.69
12.96
12.47
18.04
8.70
16.76
14.58
11.07
23.70
7.67
5.60
10.11
5.14
28.26
2009–2010
1993–1994
2009–2010
1993–1994
2004–2005
Coefficient of variation of poverty HCR (%)
Sample households
56. Coastal
55. Delhi
25. Delhi
26. Odisha
Region
State
Table 9 continued
R. K. Chauhan et al.
600
1720 4098 4098* 1320
79. Southern Plains
80. Central Plains
81. Western Plains
680
7818
598
679
1298
3859*
3859
1980
700
7837
2195
704
1144
1344
1662
1568
608
6326
1779
4.36
5.65
5.01
5.01
4.15
6.40
2.78
10.63
6.84
6.42
6.42
3.71
12.48
3.18
6.18
9.39
2004–2005
10.29
11.71
17.21
9.14
16.17
5.59
14.83
14.23
2009–2010
1993–1994
2009–2010
1993–1994
2004–2005
Coefficient of variation of poverty HCR (%)
Sample households
78. Eastern Plains
77. Himalayan
76. Uttarakhand
75. Southern
Region
* Estimates/sample size repeated for seven regions in 50/61 rounds owing to vertical division of these regions during later period, details provided in Appendix 1
35. West Bengal
34. Uttarakhand
State
Table 9 continued
Regional Estimates of Poverty and Inequality in India, 1993–2012
123
123
7. Chhattisgarh
6. Chandigarh
5. Bihar
4. Assam
3. Arunachal Pradesh
2. Andhra Pradesh
5. Inland North Eastern
6. Inland Southern
6.57
19.65
9. Plains Western
10. Hills
5.26
6.24
24.70
12. Central
13. Chandigarh
3.92
11. Northern
3.18
10.72
8. Plains Eastern
5.69
12.76
6.20
7.11
4. Inland North Western
7. Arunachal Pradesh
5.19
6.20
3. Coastal Southern
5.19
2. Coastal Northern
3.48
1.07
31.37
1. Andaman and Nicobar Islands
1.21
6.63
34.31
4.43
4.76
3.31
23.69
10.04
9.76
6.98
13.32
7.45
7.12
7.12
8.84
8.84
4.61
54.80
2.15
9.57
35.66
8.47
9.67
6.50
19.55
12.43
11.10
8.10
12.15
19.22
26.06
24.66
30.96
21.99
11.75
72.16
0.51
2.21
6.46
1.84
1.80
1.28
6.30
2.16
3.32
1.83
3.14
2.31
1.74
1.74
1.90
1.90
1.14
3.13
2.99
4.49
3.82
1.63
2.04
7.06
3.08
3.82
2.50
2.92
2.95
3.22
3.22
2.47
2.47
1.75
8.69
0.50
2004–2005
3.58
5.32
3.88
3.15
2.45
6.54
3.37
5.53
2.94
2.08
3.08
4.00
4.06
3.42
2.92
1.83
4.44
0.57
2011–2012
1993–1994
2011–2012
1993–1994
2004–2005
Coefficient of variation of GI (%)
Coefficient of variation of PGR (%)
1. Andaman and Nicobar Islands
Region
India
State
12.76
53.97
11.45
10.78
7.85
45.90
14.97
19.39
11.55
30.60
13.97
12.23
12.23
9.49
9.49
6.77
17.41
2.24
1993–1994
13.77
43.10
14.88
11.12
9.05
41.43
17.68
16.63
11.86
22.77
17.29
13.76
13.76
11.37
11.37
7.91
29.79
2.36
2004–2005
16.31
46.69
15.37
16.75
11.88
37.44
19.25
21.02
13.50
21.20
19.23
19.31
16.57
18.45
15.97
8.11
25.60
2.83
2011–2012
Coefficient of variation of RPR (%)
Table 10 Coefficient of variation of gini index, poverty gap ratio and rich poor ratio in NSS 50, 61 and 68 rounds in regions of India
See Table 10.
Appendix 5
R. K. Chauhan et al.
15. Jharkhand
14. Jammu and Kashmir
13. Himachal Pradesh
12. Haryana
12.93
21. Saurashtra
23. Western
9.64
25. Trans Himalayan and Southern
28. Jhelum Valley
29. Ranchi Plateau
17.31
27. Outer Hills
5.25
5.25
18.53
17.31
26. Mountainous
14.79
9.64
24. Central
9.64
10.49
13.31
22. Eastern
8.32
6.87
6.24
24.27
51.42
13.60
20. Gujarat excl Saurashtra
19. Goa
10. Goa
11. Gujarat
17. DN Haveli
16. Southern Chhattisgarh
18. Daman and Diu
6.24
6.24
15. Mahanadi Basin
9. Daman and Diu
6.24
5.58
5.58
17.79
37.70
31.72
16.74
8.74
8.74
8.74
11.47
11.96
8.51
14.14
7.70
7.42
21.39
46.76
21.46
6.63
6.63
6.63
12.82
7.96
24.48
17.68
31.19
14.66
34.67
22.43
18.95
25.76
23.37
17.54
26.36
12.58
11.82
39.04
32.02
27.16
19.73
11.33
34.57
1.87
1.87
5.47
5.47
6.17
4.94
2.30
2.30
2.30
5.19
2.45
2.75
3.06
1.60
1.47
4.49
7.54
5.02
2.21
2.21
2.21
2.69
2.69
2.85
7.84
3.68
2.36
2.53
2.53
2.53
2.89
8.44
7.31
3.59
2.18
2.01
6.57
11.35
4.82
2.99
2.99
2.99
2004–2005
4.67
3.42
3.40
4.76
5.21
2.67
3.60
3.59
2.56
4.31
3.24
2.84
5.11
2.30
2.10
9.08
10.31
7.67
8.32
4.16
6.79
2011–2012
1993–1994
2011–2012
1993–1994
2004–2005
Coefficient of variation of GI (%)
Coefficient of variation of PGR (%)
14. Northern Chhattisgarh
Region
8. Dadra Nagar Haveli
State
Table 10 continued
13.76
13.76
28.92
28.92
20.60
17.66
14.36
14.36
14.36
25.85
18.25
15.19
18.97
12.41
10.45
25.65
39.21
45.95
12.76
12.76
12.76
1993–1994
12.11
12.11
14.67
37.24
19.14
11.44
11.62
11.62
11.62
15.76
29.17
22.30
18.87
13.06
11.03
27.65
44.63
41.46
13.77
13.77
13.77
2004–2005
24.23
14.57
15.49
22.13
19.44
10.65
20.87
18.49
13.89
24.84
21.22
16.94
23.63
14.24
12.26
29.70
55.63
45.17
46.50
18.73
41.11
2011–2012
Coefficient of variation of RPR (%)
Regional Estimates of Poverty and Inequality in India, 1993–2012
123
123
21. Manipur
20. Maharashtra
19. Madhya Pradesh
18. Lakshadweep
17. Kerala
16. Karnataka
State
Table 10 continued
17.40
7.29
5.47
32. Inland Eastern
33. Inland Southern
34. Inland Northern
6.64
9.46
7.80
12.99
40. Malwa
41. South
42. South Western
43. Northern
7.07
7.33
5.22
4.51
9.24
45. Inland Western
46. Inland Northern
47. Inland Central
48. Inland Eastern
49. Eastern
6.34
12.67
44. Coastal
3.30
9.44
12.39
39. Central
9.28
38. Vindhya
4.42
41.43
36. Southern
37. Lakshadweep
8.24
35. Northern
5.23
21.44
4.48
5.25
7.43
11.35
6.77
6.07
9.76
8.51
14.51
3.94
11.45
11.45
9.48
10.80
8.13
7.31
4.12
51.10
12.50
9.44
8.00
7.08
11.31
18.44
23.43
6.25
5.58
7.98
22.47
14.12
13.28
19.07
16.30
25.85
8.87
21.06
16.87
11.63
30.26
15.44
12.83
7.31
61.99
17.72
17.85
12.95
9.42
30.52
23.67
32.47
9.19
10.02
2.14
3.80
2.18
3.88
2.75
2.07
1.44
0.88
2.89
3.00
17.15
5.51
4.62
2.85
4.30
6.51
2.24
2.52
1.72
1.88
1.75
4.02
4.64
1.19
1.87
2.16
3.90
3.27
3.29
2.86
2.29
1.80
0.99
5.52
6.48
4.09
3.41
4.22
3.33
2.03
7.52
2.14
3.27
1.73
3.77
2.70
4.10
5.67
2.05
2.69
2004–2005
2.76
7.46
5.35
4.09
4.76
4.42
3.19
1.95
5.94
5.12
3.24
4.75
6.57
5.69
2.45
7.77
2.63
3.23
2.07
3.68
3.90
10.09
6.14
3.38
4.59
2011–2012
1993–1994
2011–2012
1993–1994
2004–2005
Coefficient of variation of GI (%)
Coefficient of variation of PGR (%)
31. Coastal and Ghats
30. Hazaribagh Plateau
Region
16.88
29.19
15.22
17.38
20.02
13.43
13.51
6.98
17.83
24.01
26.70
16.97
28.18
18.14
9.31
39.15
10.41
12.83
8.11
14.25
13.89
22.69
23.95
8.59
13.76
1993–1994
13.90
28.83
16.28
17.97
22.59
13.17
14.70
7.38
24.72
25.45
21.31
23.84
21.50
19.57
10.20
48.43
10.59
12.97
8.32
16.17
17.44
22.82
41.66
10.87
12.11
2004–2005
13.67
29.75
20.01
17.13
22.42
17.40
18.55
9.28
26.46
25.68
24.13
20.43
28.76
24.54
10.54
38.65
10.86
12.74
8.39
15.82
33.50
36.76
28.87
19.39
17.26
2011–2012
Coefficient of variation of RPR (%)
R. K. Chauhan et al.
31. Tamil Nadu
30. Sikkim
29. Rajasthan
28. Punjab
27. Pondicherry
21.29
7.61
61. Southern
65. South-Eastern
9.88
7.65
7.87
68. Coastal
69. Southern
70. Inland
6.97
67. Coastal Northern
4.24
16.60
12.37
64. Southern
66. Sikkim
8.07
11.31
63. North-Eastern
8.27
62. Western
5.41
12.01
60. Northern
6.90
24.31
7.78
58. Northern
59. Pondicherry
7.17
57. Southern
4.16
34.67
5.93
25. NCT of Delhi
11.54
36.13
56. Coastal
54. Nagaland
55. Delhi
24. Nagaland
26. Odisha
52. Meghalaya
53. Mizoram
23. Mizoram
7.08
12.07
51. Hills
9.50
7.38
10.34
8.32
4.64
11.84
23.41
12.28
8.81
7.94
5.46
8.71
11.16
7.31
26.14
5.08
5.98
7.26
4.07
19.35
24.29
18.37
15.40
9.61
11.07
8.57
22.43
19.48
29.15
15.51
11.42
28.25
28.32
18.03
17.37
29.71
12.64
24.84
21.22
16.25
30.40
11.53
9.29
12.49
7.05
33.82
17.69
23.20
24.38
13.48
2.77
3.32
7.58
2.64
2.45
2.06
3.10
4.98
25.70
2.00
2.20
3.80
2.19
2.01
1.49
5.18
2.63
4.06
2.16
1.55
3.09
3.42
2.55
21.12
3.12
2.52
3.04
3.31
2.39
1.57
3.73
6.09
4.36
3.73
3.30
2.12
2.90
2.70
1.98
4.13
2.93
3.14
3.03
1.80
3.41
3.05
1.99
3.66
3.17
2.84
2004–2005
4.11
4.68
2.80
2.41
1.81
3.83
6.17
4.26
3.69
3.29
2.29
4.48
2.57
2.61
4.90
3.29
4.59
3.63
2.27
4.73
3.33
2.73
2.99
5.16
3.40
2011–2012
1993–1994
2011–2012
1993–1994
2004–2005
Coefficient of variation of GI (%)
Coefficient of variation of PGR (%)
50. Plains
Region
22. Meghalaya
State
Table 10 continued
14.69
17.52
16.28
21.04
10.09
24.39
21.56
35.77
13.35
13.11
8.79
13.52
13.88
10.06
28.62
17.27
24.35
14.33
10.08
35.88
29.75
22.49
27.22
32.93
19.54
1993–1994
15.21
13.41
16.27
15.49
7.99
20.53
30.18
23.57
16.45
13.65
9.65
14.59
12.66
9.64
22.50
15.62
23.54
15.82
10.31
23.67
16.64
14.89
18.28
21.19
17.70
2004–2005
19.74
17.24
17.47
17.78
9.42
20.78
28.26
28.60
14.78
17.67
10.03
17.09
13.77
10.83
23.99
19.26
22.01
17.65
11.75
27.23
19.20
15.36
18.27
30.23
13.90
2011–2012
Coefficient of variation of RPR (%)
Regional Estimates of Poverty and Inequality in India, 1993–2012
123
123
35. West Bengal
34. Uttarakhand
3.41
7.17
74. Eastern
75. Southern
6.42
7.21
7.21
7.86
78. Eastern Plains
79. Southern Plains
80. Central Plains
81. Western Plains
8.90
77. Himalayan
3.91
13.00
5.69
73. Central
76. Uttarakhand
5.63
2.61
11.19
9.26
7.97
7.97
5.29
18.21
4.23
7.62
12.56
3.91
6.78
5.66
2.91
6.58
14.35
13.41
25.02
11.13
31.72
7.45
17.28
21.31
6.25
8.97
9.16
4.55
15.10
2.98
1.83
1.83
14.14
3.17
3.30
4.38
5.07
1.47
2.31
1.56
0.97
2.14
3.71
2.60
2.60
3.70
3.86
1.90
2.89
6.78
2.29
4.14
3.80
2.05
2.91
2004–2005
5.74
2.96
3.02
3.73
3.94
1.87
4.47
10.78
3.63
5.17
3.11
2.08
2.56
2011–2012
1993–1994
2011–2012
1993–1994
2004–2005
Coefficient of variation of GI (%)
Coefficient of variation of PGR (%)
72. Western
71. Tripura
32. Tripura
33. Uttar Pradesh
Region
State
Table 10 continued
15.89
11.25
11.25
19.55
21.59
8.20
23.02
25.27
9.08
14.57
10.17
6.10
17.40
1993–1994
17.25
11.68
11.68
13.47
23.36
7.77
14.84
24.97
8.52
17.12
12.61
7.13
13.53
2004–2005
21.19
16.24
15.84
18.11
27.27
8.65
20.64
30.91
11.63
17.61
14.29
8.26
16.12
2011–2012
Coefficient of variation of RPR (%)
R. K. Chauhan et al.
Regional Estimates of Poverty and Inequality in India, 1993–2012
References Ahluwalia, M. S. (1978). Rural poverty and agricultural performance in India. Journal of Development Studies, 14(3), 298–323. Atkinson, A. B. (1970). On measurement of inequality. Journal of Economic Theory, 2, 244–263. Basu, D., & Das, D. (2014). Poverty–hunger divergence in India. Economic and Political Weekly, 49(2), 22–24. Bhandari, L., & Khare, A. (2002). The geography of post-1991 Indian economy. Global Business Review, 3(2), 321–340. Chaudhuri, S., & Gupta, N. (2009). Levels of living and poverty patterns: A district-wise analysis for India. Economic and Political Weekly, 44(9), 94–110. Chaudhury, P. (2007). Alternative reference periods in measuring household consumption: The implications for poverty estimation. In Processing of ‘National Seminar on the Survey Results of NSS 61st Round’ organized at New Delhi during October 29–30, 2007 (p. 231). Chauhan, R. K. (2008). Gains and challenges in pooling state and central sample NSS data: Case of Uttar Pradesh for 61st (2004–2005) Round. In Proceedings of National Seminar on NSS 61st Round Survey Results. NSSO: New Delhi. Chelliah, R. J., & Shanmugam, K. R. (2007). Strategy for poverty reduction and narrowing regional disparities. Economic and Political Weekly, 42(34), 3475–3481. Deaton, A., & Dreze, J. (2002). Poverty and inequality in India: A re-examination. Economic and Political Weekly, 37(36), 3729–3748. Deaton, A., & Kozel, V. (2004). Data and dogma: The great Indian poverty debate. New Delhi: Macmillan. Dubey, A. (2009). Intra-state disparities in Gujarat, Haryana, Kerala, Orissa and Punjab. Economic and Political Weekly, 44(26/27), 224–230. Foster, J., Greer, J., & Thorbecke, E. (1984). A class of decomposable poverty measures. Econometrica, 52(3), 761–766. Galbraith, J. K. (2012). ‘‘Pay inequality and world development’’ in inequality and instability. Oxford: Oxford University Press. Galbraith, J. K., & Chowdhury, D. R. (2007). The European Wage Structure, 1980–2005: How much flexibility do we have? Austin: UTIP Working Paper No. 41. Gangopadhyay, K., & Singh, K. (2013). Extent of poverty in India: A different dimension. Economic and Political Weekly, 48(6), 75–83. Guruswamy, M., & Abraham, R. J. (2006). Redefining poverty: A new poverty line for a New India. New Delhi: Centre for Policy Alternatives. Himannshu. (2007). Recent trends in poverty and inequality: Some preliminary results. Economic and Political Weekly, 42(6), 10–16. Himannshu, & Sen, K. (2014). Revisiting the Great Indian poverty debate: Measurement, patterns, and determinants, BWPI Working Paper 203, Brooks World Poverty Institute, The University of Manchester. Jensen, R. & Miller, N. (2010). A revealed preference approach to measuring hunger and undernutrition. NBER Working Paper No. 16555. Jha, R., Gaiha, R., & Sharma, A. (2010). Mean consumption, poverty and inequality in rural India in the 60th round of the National Sample Survey. Journal of Asian and African Studies, 45(5), 485–503. Jha, R., & Sharma, A. (2003). Spatial distribution of rural poverty. Economic and Political Weekly, 38(47), 4985–4993. Joe, W., Mishra, U. S., & Navaneetham, K. (2009). Inequalities in childhood malnutrition in India: Some evidence on group disparities. Journal of Human Development and Capabilities: A Multi-Disciplinary Journal for People-Centered Development, 10(3), 417–439. Kannan, K. P., & Raveendran, G. (2011). India’s common people: The regional profile. Economic and Political Weekly, 46(38), 60–73. Kijima, Y. & Lanjouw, P. (2003). Poverty in India during the 1990s: A regional perspective. World Bank Policy Research Working Paper 3141. Washington DC: World Bank. Kuznets, S. (1955). Economic growth and economic inequality. American Economic Review, XLV, 45(1), 1–28. Litchfield, J. A. (1999). Inequality: Methods and tools, Text for World Bank’s Web Site on Inequality, Poverty, and Socio-economic Performance. http://www.worldbank.org/poverty/inequal/index.htm. November 04, 2014. Mukhopadhyay, S. (2011). Using the mean of squared deprivation gaps to measure undernutrition and related socioeconomic inequalities. Journal of Human Development and Capabilities: A Multi-Disciplinary Journal for People-Centered Development, 12(4), 535–556.
123
R. K. Chauhan et al. Murgai, R., Suryanaryana, M. H., & Zaidi, S. (2003). Measuring poverty in Karnataka: The regional dimension. Economic and Political Weekly, 38(4), 404–408. Murthi, M., Srinivasan, P., & Subramanian, S. V. (2001). Linking Indian census with National Sample Surveys. Economic and Political Weekly, 36(9), 783–792. National Sample Survey Organisation, Ministry of Statistics and Programme Implementation, Government of India. (1996). Level and pattern of consumer expenditure, 5th Quinquennial Survey (1993–1994). Report No. 402: New Delhi. National Sample Survey Organisation, Ministry of Statistics and Programme Implementation, Government of India. (2006). Level and Pattern of Consumer Expenditure, 2004–2005 NSS 61st Round (July 2004– June 2005). Report No. 508(61/1.0/1): New Delhi. National Sample Survey Organisation, Ministry of Statistics and Programme Implementation, Government of India. (2014). Level and Pattern of Consumer Expenditure, 2011–2012 NSS 68th Round (July 2011– June 2012). Report No. 555(68/1.0/1): New Delhi. Ogwang, T. (2014). A convenient method of decomposing the gini index by population subgroups. Journal of Official Statistics, 30(1), 91–105. Panagariya, A., & Mukim, M. (2014). A comprehensive analysis of poverty in India. Asian Development Review, 31(1), 1–52. Pathak, D. C., & Mishra, S. (2011). Poverty estimates in India: Old and new methods, 2004–05 WP-2011015. IGIDR: Mumbai. Piketty, T. & Saez, E. (2003). Income inequality in the United States, 1913–1998. The Quarterly Journal of Economics 118(1), 1–39. Planning Commission, Government of India. (2009). Report of the expert group to review the methodology for estimation of poverty. New Delhi: Government of India. Planning Commission, Government of India. (2013). Press notes on poverty estimates, 2011–12. New Delhi. Rahman, L., & Rao, V. (2004). The determinants of gender equity in India: Examining Dyson and Moore’s thesis with new data. Population and Development Review, 30(2), 239–268. Reserve Bank of India. (2014). http://www.rbi.org.in/home.aspx. Accessed on June 22, 2014. Sastry, N. S. (2003). District level poverty estimates—Feasibility of using NSS household consumer expenditure survey data. Economic and Political Weekly, 38(4), 409–412. Sen, A. K. (1976). Poverty: An ordinal approach to measurement. Econometrica, 44(2), 219–231. Sen, A. K. (1997). From income inequality to economics inequality. Southern Economic Journal, 64(2), 384–401. Sen, K., & Palmer-Jones, R. (2001). On India’s poverty puzzles and statistics of poverty. Economic and Political Weekly, 36(3), 211–217. Singh, N., Bhandari, L., Chen, A., & Khare, A. (2003). Regional inequality in India: A fresh look. Economic and Political Weekly, 38(11), 1069–1073. Singh, N., Kendall, J., Jain, R. K. & Chander, J. (2013). Regional inequality in India in the 1990s: A further look. Department of Economics, UCSC, UC Santa Cruz, Working Paper. Available at SSRN: http:// ssrn.com/abstract=2394310. Sundaram, K., Jain, L. R., & Tendulkar, S. D. (1988). Dimensions of rural poverty: An inter-regional profile. Economic and Political Weekly, 23(45–47), 2395–2408. Sundaram, K., & Tendulkar, S. D. (2003). Poverty among social and economic groups in India in 1990s. Economic and Political Weekly, 38(50), 5263–5267. Thorat, A. (2010). Ethnicity, caste and religion: Implications for poverty outcomes. Economic and Political Weekly, 45(51), 47–53. United Nations. (2013). Inequality matters, Report of the World Social Situation 2013. Department of Economic and Social Affairs, ST/ESA/345, New York. World Bank. (2011). Perspectives on poverty in India: Stylized facts from survey data. Report No-57428: Washington, DC. World Bank. (2014). http://www.worldbank.org/en/topic/poverty/overview. Accessed on June 22, 2014. World Bank. (2015). http://databank.worldbank.org/data/home.aspx. Accessed on February 22, 2015.
123
