Table 1 indicates that lack of financial capital and human capital pushes a household in deprivation trap or interchangeably one can say into poverty trap also it highligh[r]
(1)1
The paper discussed below is not yet completed and still in working stage Few tables presented here has to be converted in Maps through GIS technique as well as the researcher has requested for the welfare expenditure data to BBMP Bengaluru but due to political instability in state I have not yet received the data, therefore the section on policy implications is not included here where I will discuss about the Place Based Policies in details
(Presentation on)
“The Place Based Policies: The Way Forward to Alleviate Poverty from Cities
A Study of Bengaluru India”Submitted by: Jamadar Mudassar Mahamad Centre for Research in Urban Affairs (CRUA), ISEC, Bengaluru
Introduction
(2)2
Such developments in understanding of poverty help to prove that poverty is not a static concept and it is multidimensional in nature But unlike measurement and estimation issues; the identification issues of poor are less discussed It took four long decades after independence to India to conduct their first BPL (below poverty line) census in 1992 and even in that the urban poor were completely excluded It is true that scholars argued to have a separate identification criterion for urban poor, but it took a long time and only came into existence with Hashim committee‟s recommendations in 2012, where they proposed three stage criteria to identify urban poor If the suggested criterion has been used for the poverty census in urban areas, it will be generate the information of spatial distribution of poverty and with the help of this much needed information; the government will be in better position to deliver schemes and services which meant for welfare of the urban poor
But historically what has found that the development plans have been failed to address the issues of the marginalisation of the urban poor, and often led to their spatial exclusion They are pushed out of city, where services are poor and investments are low or in other way this development failure leads to form a poverty pockets within cities, and these poverty pockets or corridors not only experiencing the low levels of income but also lower education levels, and higher isolation (Singh, 2014) In recent years to identify such poverty pockets the technique of poverty mapping is used widely
Poverty Mapping
“Poverty mapping provides a means for integrating biophysical information with socioeconomic indicators to provide a more systematic and analytical picture of wellbeing and Equity.”- Henninger M and Snel M (2002)
The technical definition of poverty mapping is available on Wikipedia with the reference of Nawar, A H (2007), “Poverty mapping is the methodology for providing detailed description of the spatial distribution of poverty and inequality within a country It combines individual and household (micro) survey data and population (macro) census data with the objective of estimating welfare indicators for specific geographic area as small as village or hamlet.”
(3)3
Geographical Information System (GIS) has to be mentioned especially because it is the tool which makes it possible to overlap wide range of information and data sets on a single map to provide a comprehensive picture of actual situation in study or reference area Poverty maps are widely being used for Regional planning, to formulate social and economic policies, and it will also help to allocate funds for wellbeing of poor Here are some examples of application of poverty mapping, the poverty maps are used for safe water and disease mapping in South Africa Nicaraguans, Guatemalans and Cambodians used poverty maps to guide expansion of health services, road transportation networks and food aid respectively also in Brazil poverty maps were used to redistribute state-wide tax revenues, in Panama poverty maps helped government officials to resist the political pressure who actually wanted to alter the funding allocations once they had been made (Tzavidis N, 2010 and Henninger, N., & Snel, M 2002)
Though the poverty maps have extensive list of applications, the present chapter is not dealing with poverty maps There are some constraints which limit the decision to come up with poverty map The major constraint is the quality of data input because it requires census and survey data both to build a poverty map And it is already assumed that both the data sets are actually representing the same population with no significant time period difference between these two data sets but if there is a problem with either data set, it will create significant problems in disseminating poverty maps Second, these maps not imply causal relationships, third what methodology a researcher is following to build a poverty map It includes issues of compatibility of census and survey data, appropriate technical and statistical skills and the knowledge of mapped area to explain the poverty map (Bedi, et al 2007)
(4)4
is to identify those wards which may have poor outside the slums Here with the use of deprivation mapping such wards has been identified
Deprivation Mapping
Generally the term deprivation is used interchangeably with poverty But more specifically deprivation is defined by Townsend (1993) as a “state of observable and demonstrable disadvantage relative to the local community or the wider society to which an individual, family or group belongs.” On the other hand, poverty is understood multidimensional in nature which restrict or making deprived to access things or services which insure sustainable livelihood (Rahman, M H and Rana, M M P 2015 cited Townsend, 1993:79 and Alam, 1989) Caroline Moser has given an asset vulnerability framework whether she categorised the assets which people have in five major groups such as, Labour (workers who are getting paid for their work), Human Capital (Education and skills), Productive assets (e.g housing), household relations and finally, social capital (the support networks presented within communities) Here those households lacking in above categorised assets are actually vulnerable to become poor Later Mitlin and Satterthwaite 2004 lists poverty itself as an eighth deprivation; and other deprivations include,
i Inadequate and unstable incomes,
ii Inadequate, unstable or risky asset bases, iii Inadequate provision of public infrastructure, iv Inadequate provision of basic services,
v Limited safety nets for those who unable to pay for services,
vi Inadequate protection of poorer groups through laws and rights, and
vii Powerlessness of poorer groups within political and bureaucratic system (Baud, Et al 2008 cited Mitlin and Satterthwaite, 2004)
Later in 2008 Baud Et al (2008) form a new “Index of Multiple Deprivations” (IMD) based on inputs from Moser (1998) and, Rakodi and Lloyd-Jones (2002) where she grouped all the assets in four major capitals specifically for urban areas,
i Human capital (health, education and training, employment)
ii Financial capital (savings and assets e.g jewellery and other capital goods) iii Physical capital (housing and basic services) and,
(5)5
With the help of above mentioned index, Baud and other authors have mapped the deprivations for some Indian megacities such as Delhi, Mumbai and Chennai It is useful to identify or map the poverty hotspots in given cities Similarly the efforts have been made here to find out the most deprived wards in Bengaluru
Methodology
The criterion used by Baud et al (2008) to identify deprivations has been given below
Source: Baud et al (2008) “Model of criteria used to map multiple deprivations.”
(6)6
In
d
ex of M
u
ltip
le D
ep
rivation
Deprived Capital Indicators of Deprivation
Social Capital % SC population % ST population Human Capital % Illiterate person
% Marginal workers Financial Capital % HH not availing banking
services
Physical Capital
% HH lives in kutcha houses % HH using unsafe drinking water % HH having no toilet
% HH having no proper bathroom % HH using unclean fuel for cooking
Source: Index of Multiple Deprivation based on Baud et al (2008)
In the above index though the variables are simple enough to understand, here to capture the social capital deprivation SC and ST population in ward are taken as an indicator Both these communities are from socially humble background and due to prevailing caste system in society they are vulnerable to many atrocities in their day to day life To avoid such situations they used to live together in certain pockets of city Same is the case with religious minorities and specifically with Muslim population but unavailability of the data at ward level restrict the analysis and forgo the inclusion of minority dimension in calculating social deprivation Here consideration of SC and ST population as indicator of social capital deprivation does not mean that SC‟s and ST‟s are always socially deprived They have strong social networks and social bonding within their own communities, but at a larger level these people found it hard to connect with other hierarchically upper groups in caste and income and also discriminated in access to basic amenities, education, health services, employment and other opportunities to raise their standard of living The Karnataka fourth state finance commission considers the proportion of SC/ ST as a measure of backwardness for the BBMP, as may be seen in its questionnaire
(7)7
The human capital is defined by Moser (1998, p 4) according to her the health situations and the kind of skills and education that household members have are the human capital, because it determines people‟s capacity to work and the returns to their work respectively “Human capital is labour resources available within the household.” (Baud, 2008 cited Rakodi, and Jones, 2002) There is no data available in census about health situation within household, therefore the focus has been shifted to education and employment in the household and to capture the human capital deprivation illiteracy (no education at anytime) and marginal workers (no formal work) has taken as representative indicators Here illiteracy is no education at all therefore the person is considered unskilful because s/he does not have training It is empirically evident that person with low skills or education are availing low paid jobs and after fulfilling all their necessities they find it hard to save money Same is the case with informal workers; they are unemployed for the considerable period of time in a year and due to unemployment they have to work on minimal wages Another important thing here is that in most of the cases these marginal workers are not having any benefits like main workers are availing such as paid leave, pension, provident fund; loans etc., hence are vulnerable
Availing banking services is the good indicator of household‟s financial situation and it is well evident with the central governments scheme “Jan Dhan Yojana” where government expects that every household must have bank account Therefore percent HH‟s not availing banking services is taken as indicator to capture financial deprivation Finally, the indicators of physical capital deprivation are tried to cover all the constraints that the HH‟s face in their daily routine life such as housing, drinking water, sanitation and cooking fuel The explanation on some definitional terms used here is given below,
For Human capital, the percentage of marginal workers is calculated by no of marginal workers to no of total workers (and not to total population) into hundred
(8)8
water as well as the information of households which are using other resources for drinking water are not very clear about if these resources are clean sources of drinking water or not therefore other resources also not considered in definition
Households who not have toilets are considered together those households who use public toilets or defecate in open And households with no proper bathroom means households having bathroom like enclosure but without roof and those households who are completely not having any bathroom facility The unclean cooking fuel considered here is use of firewood, crop residue, cow dung cake, coal, lignite, charcoal and kerosene for cooking Based on above mentioned index the analysis has been done for Bengaluru urban district by using census data of 2011 This analysis is helpful to identify that which wards are most deprived and in which capital But before interpreting the table we have to understand that how the analysis has been done here
For the analysis part deprivation is calculated in four different capitals social capital, human, financial and physical capital To capture capital deprivation, different variables are assigned to every capital e.g to capture social capital deprivation variables assigned here are % SC and % ST population But what has been found in analysis is that those wards which have highest percentage of SC population not necessarily having the high ST population percentage Therefore the confusion arises as to which ward is socially deprived Hence we‟ve taken the sum of SC and ST population to indicate deprivation in social capital
The simple solution to identify most deprived wards is taking averages of the variables used to measure each capital and arranging these average scores in ranks e.g to identify socially deprived wards the variables i.e percent SC and percent ST population are arranged ward wise Here higher the score (average) shows how worst is the situation The arrangement of scores from high score to low score with their respective wards indicates the wards are arranged in worst to least deprivation The process is repeated for each capital deprivation except financial capital, because in financial capital only one variable is assigned to capture the deprivation
(9)9
of high to low scores Here highest overall average score represents lowest rank, which means it is the most deprived, and vice versa
Results and Findings
Table: 1.Multiple Deprivation in the wards of Bengaluru, 2011
Rank
Capital specific deprivation in wards Most Deprived ward
(In all capital)
Social Capital Human Capital Financial Capital Physical Capital Score Ward
no Score
Ward
no Score
Ward
no Score
Ward no
Final
Score Ward no 26.66 138 27.91 118 87.40 135 26.18 118 34.03 118 22.51 95 24.04 135 81.00 47 24.38 11 33.51 138 19.56 137 23.13 144 73.90 136 23.44 130 32.76 47 19.35 118 22.33 47 70.90 138 23.42 82 30.16 135
5 18.70 79 21.76 48 69.10 48 22.32 54 28.93 95
6 18.45 139 20.70 60 65.50 70 21.50 40 28.03 136 16.49 80 20.20 139 64.30 180 21.22 138 27.74 48 16.11 115 20.12 131 62.70 118 20.88 27.60 11 15.90 114 20.11 38 62.40 122 20.16 198 27.28 139 10 15.75 97 19.45 180 60.30 137 20.16 196 26.32 40 11 15.37 11 19.43 157 59.60 95 19.84 194 26.07 70 12 14.75 147 19.26 53 59.10 30 19.80 172 26.03 137
13 14.60 60 19.26 26 58.70 40 19.22 70 25.52 60
14 13.73 16 19.21 95 58.10 23 18.68 12 25.37 42
15 13.06 88 19.19 136 57.90 131 18.14 69 25.37 131 16 12.99 62 18.85 61 57.20 121 18.12 47 24.97 180
17 12.93 59 18.57 96 57.00 42 17.82 26 24.36 144
18 12.73 90 18.52 24 55.90 120 17.68 53 23.89 196 19 12.54 51 18.37 22 55.80 134 17.64 192 23.65 23
(10)10
Source: Census of India 2011 and Author‟s calculations
Table depicts the picture of most deprived wards among different kinds of capital in Bengaluru based on census 2011 data Bengaluru has 198 wards as of census 2011 but it would not be convenient to show the calculations for all the wards therefore for each capital deprivation almost 10% of total wards of Bengaluru are arranged according to the severity of respective deprivation Ward no 138 is deprived in social capital with the score of 26.66 while ward no 118 (score- 27.91) deprived in human capital Ward no 135 (score-87.40) and ward no 118 (score- 26.18) are deprived in financial and physical capital respectively And again Ward no 118 (score- 34.03) is coming out as the most deprived ward in Bengaluru Further the column of most deprived wards found among top twenty most deprived wards have 14 wards common to financial capital deprived wards and 13 with human capital deprivation Social capital deprivation and physical capital deprivation have wards common to the overall deprived wards
Table indicates that lack of financial capital and human capital pushes a household in deprivation trap or interchangeably one can say into poverty trap also it highlights that lack of physical and social capital is the least important cause for poverty This situation indicates that providing basic amenities to the areas where poor are concentrated might not be that effective to eradicate poverty but creation of new jobs are definitely be helpful to eradicate poverty
Table: 2.Most deprived non-slum wards with their respective slum population percentage and overall deprivation rank for Bengaluru 2011
Sr no
Most deprived ward
(non slum) % Slum population Final Score Deprivation Rank
1 47 32.76
2 135 30.16
3 48 27.74
4 40 4.50 26.32 10
5 196 23.89 18
6 23 4.46 23.65 19
7 30 2.07 23.30 23
8 61 23.29 24
9 122 22.72 26
10 121 0.51 21.59 33
Mean 1.15 25.54
(11)11
Most of the wards in Bengaluru already have notified or non-notified slum population On the average, each ward has 9.44% of slum population (authors‟ calculation) For purposes of the table above, wards with less than five percent of slum population are considered as non slum wards
The table no shows that ward no 47 (Devrajeevanahalli) is the most deprived non-slum ward with no slum population recorded and similar to that ward no 135, 48, 196, 61, and 122 have not recorded any slum population but they are showing the high degree of deprivation The mean shows as low as 1.2% slum population in each ward and average deprivation score is 25.54 We find that the ward deprivation list is no doubt dominated by wards with slums; among the top 33 most deprived wards, while 23 wards have significant slum population, 10 wards have no/ negligible slum population (less than 5%)
Table no.3: Top five most deprived non-slum wards and their determining causes of deprivation or poverty in Bengaluru 2011
Most deprived ward (non-slum)
Deprived
Capital Determining cause of deprivation or poverty
Ward no 47 Devarajeevanahalli
(ODR- 03)
Social Capital Human Capital
Financial Capital Physical Capital
18.14% SC population 32.22% illiterate population 12.45% Marginal workers
81% HH‟s not using banking facilities 4.5% HH‟s defecate in open
7% HH‟s have no proper bathroom 52.7% HH‟s have no access to clean fuel
Ward no 135 Padarayanapura
(ODR- 04)
Social Capital Human Capital Financial Capital
Physical Capital
Socially less deprived ward (0.34%) 35.38% illiterate population
Almost 13% marginal workers
87.40% HH‟s not availing banking services (highest among all wards)
40% HH‟s are using unclean cooking fuel Ward no 48
Muneshwaranagar (ODR- 07)
Social Capital Human Capital
(12)12 Financial Capital
Physical Capital
14.33% marginal workers
69% HH‟s not availing banking services 36.60% HH‟s uses unclean cooking fuel
Ward no 40 Doddabidarakalu
(ODR- 10)
Social Capital
Human Capital Financial Capital Physical Capital
4.89% ST population in ward Almost 1/4th
illiterate population
59% HH‟s not availing banking services 66.4% HH‟s using unsafe drinking water 35.2% HH‟s uses unclean cooking fuel
Ward no 196 Anjanapura
(ODR- 18)
Social Capital Human Capital Financial Capital Physical Capital
Less social deprivation (5.09%) 30% illiterate population
52.40% HH‟s not using banking services 2.60% HH‟s lives in kutchcha houses
57% HH‟s have no access to safe drinking water
5% HH‟s have no toilet facility
6% HH‟s not having proper bathroom facility
Source: Census of India 2011 and Author‟s calculations
(13)13
households who are not availing any banking services made their place in top five non-slum capital deprived wards Table is the snapshot of the deprivations that are present in selected non-slum wards and the analysis of this kind is very much helpful in disseminating welfare benefits with the targeted approach
Inferences
Governing authorities, scholars and urban planners all over the world are struggling to end poverty and inequality The increasing issues of poverty, deprivation and inequality in urban areas need to be addressed The spatial understanding of spread of such issues might help to all concerned authorities and people to improve the situation The present study deals with four types of capital deprivation such as social, human, financial and physical capital Based on the analyses, we infer that beyond financial crunch, the lack of human capital is another important cause of urban deprivation in society The lack of education and no skills make people illiterate and unemployed It is the main cause for minimal and irregular earnings The physical capital deprivation is found the overrated cause of deprivation or poverty; it may actually be an outcome of human capital deprivation The governing authorities typically take the effort to provide the basic amenities to its citizens; literature suggests that poor people are not ready to invest in improvement of existing infrastructure simply because of fear of evictions Poor people chose to live in dilapidated housing conditions therefore providing basic amenities might help poor to improve their quality of life but it does not help poor to that extent to come out of poverty This study, based on the preliminary findings, argues that the social capital deprivation is the least important cause to push people in poverty trap It is the positive sign for policy makers that the social welfare schemes should benefit more to poor people who rather are deprived in human capital
(14)14 References
Baud, I S A., Sridharan, N., & Pfeffer, K (2008) Mapping urban poverty for local governance in an Indian mega-city: the case of Delhi Urban Studies, 45(7), 1385-1412
Bedi, T., Coudouel, A., & Simler, K (Eds.) (2007) More than a pretty picture: using
poverty maps to design better policies and interventions World Bank Publications
Davis, B (2003) Choosing a method for poverty mapping Food & Agriculture Org
Henninger, N., & Snel, M (2002) Where are the poor? Experiences with the development and use of poverty maps
http://www.sfckarnataka.mrc.gov.in/sites/sfckarnataka.mrc.gov.in/files/GOK_-_partwise_BBMP_questionnaire_Final_27.6.2016.0.PDF
Moser, C O (1998) The asset vulnerability framework: reassessing urban poverty reduction strategies World development, 26(1), 1-19
Nawar, A H (2007) From Marina to Kom-Ombo: A Note on Poverty in Egypt Manuscript
Cairo University
Rahman, M H., & Rana, M M P (2015) Mapping Urban Poverty and Deprivations: The Case of Rajshahi City The Journal of Geo-Environment, Vol 11 PP 84-97
Sen, A (1981) Poverty and famines: an essay on entitlement and deprivation Oxford University Press
(15)15 Appendix
Table A: Multiple Deprivation in the wards of Bengaluru, 2011
Rank
Deprivation capital Most Deprived
ward Social Capital Human Capital Financial Capital Physical Capital
Score Ward
no Score
Ward
no Score
Ward
no Score
Ward no
Final Score
Ward No
26.66 138 27.91 118 87.40 135 26.18 118 34.03 118
2
22.51 95 24.04 135 81.00 47 24.38 11 33.51 138
3
19.56 137 23.13 144 73.90 136 23.44 130 32.76 47
4
19.35 118 22.33 47 70.90 138 23.42 82 30.16 135
5 18.70 79 21.76 48 69.10 48 22.32 54 28.93 95
6
18.45 139 20.70 60 65.50 70 21.50 40 28.03 136
7
16.49 80 20.20 139 64.30 180 21.22 138 27.74 48
8
16.11 115 20.12 131 62.70 118 20.88 27.60 11
9
15.90 114 20.11 38 62.40 122 20.16 198 27.28 139
10
15.75 97 19.45 180 60.30 137 20.16 196 26.32 40
11
15.37 11 19.43 157 59.60 95 19.84 194 26.07 70
12
14.75 147 19.26 53 59.10 30 19.80 172 26.03 137
13
14.60 60 19.26 26 58.70 40 19.22 70 25.52 60
14
13.73 16 19.21 95 58.10 23 18.68 12 25.37 42
15
13.06 88 19.19 136 57.90 131 18.14 69 25.37 131
16
12.99 62 18.85 61 57.20 121 18.12 47 24.97 180
17 12.93 59 18.57 96 57.00 42 17.82 26 24.36 144
18
12.73 90 18.52 24 55.90 120 17.68 53 23.89 196
19
12.54 51 18.37 22 55.80 134 17.64 192 23.65 23
20
12.24 50 18.33 40 55.10 31 17.46 23.47 116
21
(16)16 22
11.13 112 18.17 11 54.10 61 17.34 190 23.37
23
10.83 144 18.10 116 54.00 139 17.24 191 23.30 30
24
10.64 94 17.97 166 53.90 96 16.92 38 23.29 61
25
10.54 49 17.95 153 53.10 60 16.90 22.80 79
26
10.53 48 17.92 159 52.50 11 16.62 71 22.72 122
27 10.48 38 17.91 52.40 16.48 139 22.50 96
28
10.33 56 17.90 196 52.40 196 16.44 149 22.44 130
29
10.15 83 17.77 42 51.70 41 16.42 131 21.82 198
30
9.90 87 17.73 191 51.70 72 16.32 72 21.82 194
31
9.88 116 17.61 122 51.60 144 16.16 83 21.73 38
32
9.83 12 17.49 62 49.70 71 16.04 56 21.69 82
33
9.68 146 17.20 198 49.30 141 16.04 84 21.59 121
34
9.57 47 17.17 190 48.40 69 15.94 13 21.56 72
35
9.41 74 17.05 47.20 15.86 21.51 31
36
9.40 170 17.03 23 46.00 74 15.82 25 21.49 41
37
9.25 61 16.97 44.90 190 15.80 39 21.38 69
38
9.23 44 16.89 33 44.40 102 15.60 129 21.36 120
39 9.18 96 16.82 25 44.30 103 15.54 79 21.18 190
40
8.79 16.79 30 44.10 92 15.46 81 21.10 12
41 8.73 53 16.74 149 44.10 194 15.40 52 21.02 54
42
8.72 28 16.67 158 43.80 73 15.18 184 20.96 71
43
8.71 149 16.64 134 43.20 130 15.16 42 20.49 134
44
8.71 148 16.60 49 42.70 198 15.00 20.27 53
45
8.48 136 16.59 32 42.30 55 14.58 20.13
46
8.28 55 16.57 31 42.00 12 14.40 55 20.02 191
47
(17)17 48
8.15 26 16.48 54 41.40 14.38 195 19.85 115
49
8.10 63 16.46 41.20 166 14.24 16 19.65 55
50
8.07 54 16.45 133 40.80 39 13.80 85 19.54 50
51
8.05 169 16.44 40.40 82 13.74 10 19.32 74
52
8.00 191 16.43 184 39.40 38 13.74 14 19.22 141
53 7.92 82 16.41 124 39.20 128 13.66 60 19.17 97
54
7.88 120 16.39 171 39.00 97 13.60 51 19.13 26
55
7.81 20 16.22 174 38.00 50 13.58 41 19.03 51
56
7.78 21 16.20 150 37.90 83 13.56 23 18.94 192
57
7.76 194 16.18 57 37.20 54 13.54 87 18.90 39
58
7.67 86 16.15 121 37.20 115 13.46 57 18.76 147
59
7.59 124 16.13 141 37.10 171 13.34 150 18.75 62
60
7.58 130 16.12 52 37.10 191 12.96 193 18.58 73
61
7.58 151 16.08 41 36.20 192 12.64 114 18.34 24
62
7.54 111 16.00 185 36.00 33 12.56 188 18.10 84
63
7.47 153 15.97 85 36.00 147 12.14 62 17.93 166
64
7.47 36 15.93 74 35.50 51 12.12 50 17.75 149
65 7.46 30 15.93 35.40 24 12.04 24 17.62 56
66
7.42 121 15.79 50 35.40 53 12.02 94 17.53 114
67 7.42 24 15.74 83 34.90 91 12.00 73 17.27 157
68
7.27 25 15.73 147 34.50 84 11.96 197 17.20 49
69
7.22 198 15.71 34.50 157 11.96 17.17 184
70
7.17 15.68 27 34.40 44 11.88 189 17.15 25
71
7.11 15.66 193 34.40 189 11.86 144 17.02 128
72
7.05 31 15.58 183 34.30 185 11.74 33 17.01 94
73
(18)18 74
6.96 133 15.55 130 33.90 158 11.52 158 16.90 158
75
6.96 129 15.47 189 33.20 114 11.48 15 16.80 33
76
6.85 27 15.47 127 32.70 28 10.98 116 16.73 52
77
6.84 34 15.42 84 32.60 124 10.98 61 16.59 102
78
6.84 173 15.41 187 32.50 161 10.80 115 16.39
79 6.80 150 15.37 80 32.40 62 10.78 86 16.34 189
80
6.78 32 15.35 169 32.30 49 10.66 175 16.22 16
81
6.74 105 15.32 21 31.80 175 10.54 136 16.21 103
82
6.73 40 15.29 115 31.60 75 10.48 180 16.20 44
83
6.69 43 15.28 94 31.50 129 9.96 16.07
84
6.69 89 15.28 79 31.30 26 9.86 30 16.05 92
85
6.61 177 15.27 88 31.20 56 9.76 159 15.87 13
86
6.59 184 15.27 138 31.10 37 9.60 157 15.71 185
87
6.58 18 15.12 188 30.50 184 9.58 48 15.63 28
88
6.57 93 15.03 82 30.10 94 9.48 137 15.61 124
89
6.49 15.02 119 29.60 14 9.36 49 15.56 175
90
6.46 13 14.96 97 29.60 117 9.26 128 15.46 87
91 6.44 84 14.90 18 29.10 127 9.24 176 15.43 153
92
6.44 64 14.80 137 29.10 149 9.00 185 15.33 59
93 6.41 113 14.79 28 29.00 52 8.88 135 15.23
94
6.39 52 14.73 58 28.70 25 8.62 17 15.09 14
95
6.31 14.71 128 28.60 13 8.54 147 15.05 43
96
6.12 14.68 164 28.50 59 8.34 96 15.04 171
97
5.99 58 14.53 17 28.30 8.20 177 15.01 150
98
5.97 81 14.51 69 28.20 153 8.14 36 14.98
99
(19)19 100
5.94 104 14.48 45 27.90 7.88 44 14.79 159
101
5.90 23 14.47 51 27.20 22 7.82 166 14.58 37
102
5.87 14.46 197 26.90 98 7.70 37 14.42 22
103
5.86 77 14.44 70 26.90 170 7.70 120 14.37
104
5.86 106 14.41 81 26.40 160 7.64 112 14.36 86
105 5.85 17 14.32 146 26.30 16 7.50 63 14.26 117
106
5.64 180 14.30 162 26.20 159 7.48 58 14.23 160
107
5.62 14.29 175 25.70 7.46 22 14.10 80
108
5.60 37 14.25 78 25.10 119 7.38 187 14.10 170
109
5.56 35 14.19 123 25.00 183 7.32 31 13.93 193
110
5.53 157 14.13 105 24.80 87 7.06 151 13.74 91
111
5.50 175 14.10 170 24.50 86 7.06 174 13.66 81
112
5.50 158 14.08 24.40 20 6.96 97 13.62 90
113
5.40 192 14.07 160 24.40 146 6.86 59 13.42 127
114
5.38 193 13.99 117 24.30 15 6.82 141 13.40 146
115
5.31 190 13.99 102 23.90 90 6.54 32 13.39
116
5.29 13.97 120 23.80 123 6.54 88 13.38 172
117 5.28 159 13.96 39 23.70 150 6.54 122 13.36 161 118
5.25 29 13.93 145 23.60 169 6.50 18 13.34 88
119 5.24 174 13.93 43 22.60 99 6.40 134 13.28 169 120
5.16 85 13.92 151 22.10 46 6.36 145 13.10 188
121
5.15 197 13.92 186 21.80 140 6.32 20 13.10 57
122
5.15 45 13.91 37 21.70 32 6.32 28 12.93 75
123
5.10 70 13.90 12 21.70 193 6.14 183 12.90 32
124
5.09 196 13.83 165 21.60 77 6.12 169 12.73 15
125
(20)20 126
5.03 39 13.75 181 21.30 5.98 170 12.52 17
127
5.01 73 13.69 68 21.20 145 5.92 74 12.50 195
128
4.98 101 13.67 129 21.20 195 5.84 124 12.18 119
129
4.90 128 13.66 72 21.10 17 5.78 21 12.03 63
130
4.84 188 13.63 55 20.80 5.64 103 12.01 183
131 4.83 152 13.60 87 20.70 106 5.64 19 11.89 21
132
4.74 166 13.51 73 20.40 68 5.60 121 11.82 18
133
4.73 160 13.36 155 20.40 105 5.56 43 11.71 151
134
4.67 78 13.31 44 20.30 187 5.54 161 11.69 36
135
4.66 22 13.29 156 20.00 126 5.48 127 11.68 85
136
4.64 57 13.22 63 19.90 188 5.46 27 11.65 77
137
4.64 46 13.15 75 19.30 18 5.44 46 11.64 145
138
4.63 141 13.14 71 19.30 63 5.42 113 11.53 105
139
4.62 172 13.14 163 18.80 81 5.36 77 11.46 187
140
4.60 41 13.03 59 18.70 21 5.36 164 11.36 10
141
4.56 15 12.94 29 18.70 29 5.26 117 11.21 133
142
4.55 72 12.92 56 18.70 36 5.22 90 11.20 46
143 4.46 69 12.81 178 18.70 181 5.20 146 11.03 123 144
4.39 71 12.80 161 18.50 45 5.16 102 10.98 112
145 4.36 14 12.68 113 18.50 80 4.98 173 10.89 98
146
4.35 176 12.67 176 18.50 88 4.94 133 10.88 177
147
4.33 122 12.67 89 18.30 151 4.86 105 10.71 45
148
4.31 67 12.66 14 18.20 155 4.84 93 10.70 58
149
4.05 99 12.63 46 18.10 57 4.82 35 10.62 27
150
3.95 119 12.61 90 17.90 156 4.78 78 10.45 174
151
(21)21 152
3.77 178 12.47 92 17.40 104 4.72 45 10.26 68
153
3.72 110 12.46 36 17.30 177 4.70 148 10.24 140
154
3.62 168 12.36 140 17.10 172 4.66 119 10.21 29
155
3.61 127 12.35 20 16.80 4.48 154 10.20 106
156
3.59 189 12.33 132 16.60 100 4.46 91 10.17 99
157 3.53 185 12.27 91 16.50 133 4.42 75 9.98 164
158
3.50 164 12.07 143 16.40 10 4.34 111 9.93 148
159
3.43 19 12.07 64 16.40 164 4.30 155 9.78 126
160
3.37 92 12.02 195 16.30 152 4.26 92 9.67 155
161
3.31 91 12.01 103 16.00 34 4.16 171 9.67 176
162
3.29 98 11.99 172 15.80 143 4.14 126 9.61 181
163
3.25 143 11.98 100 15.50 19 4.12 140 9.56 104
164
3.24 132 11.92 154 15.00 148 4.08 132 9.51 34
165
3.12 134 11.89 126 14.90 107 4.00 99 9.35 186
166
3.11 126 11.83 19 14.80 108 4.00 143 9.30 100
167
3.10 123 11.55 111 14.60 58 3.98 101 9.13 173
168
3.01 181 11.53 125 14.50 27 3.98 68 9.11 152
169 2.96 68 11.44 112 14.40 182 3.96 152 9.10 19
170
2.90 167 11.44 67 13.90 142 3.96 167 9.08 156
171 2.90 186 11.41 177 13.70 112 3.94 29 9.03 113 172
2.89 103 11.40 34 13.70 132 3.82 142 8.82 89
173
2.83 155 11.34 152 13.60 110 3.80 182 8.78 143
174
2.82 102 11.32 148 13.60 173 3.78 34 8.66 64
175
2.77 108 11.28 107 13.30 174 3.74 162 8.48 111
176
2.75 187 11.26 104 13.10 109 3.68 179 8.40 78
177
(22)22 178
2.63 182 11.00 101 12.50 89 3.56 125 7.81 110
179
2.59 33 10.86 106 12.40 176 3.54 109 7.78 107
180
2.58 161 10.80 179 12.30 154 3.42 64 7.76 182
181
2.55 75 10.60 16 12.00 76 3.42 89 7.73 154
182
2.53 171 10.58 15 11.80 85 3.42 98 7.70 108
183 2.44 142 10.52 110 11.60 113 3.40 110 7.55 142 184
2.40 195 10.44 108 10.50 111 3.38 106 7.21 93
185
2.34 107 10.37 76 10.40 163 3.28 168 7.19 35
186
2.27 125 10.35 109 9.90 78 3.22 165 7.10 165
187
2.22 66 10.23 182 9.40 178 3.16 156 7.07 163
188
2.20 154 10.02 99 9.30 165 3.16 163 7.03 178
189
2.03 165 10.02 142 9.10 35 3.04 123 6.95 162
190
2.03 76 9.96 98 8.40 93 3.00 186 6.92 109
191
1.97 156 9.69 167 8.30 125 2.96 181 6.66 76
192
1.81 65 9.37 10 8.20 162 2.78 108 6.43 67
193
1.59 163 9.29 35 7.80 167 2.66 65 6.42 125
194
1.56 162 9.04 93 7.70 66 2.58 107 6.09 167
195 1.55 179 8.64 66 7.50 67 2.48 67 5.56 168
196
1.33 183 8.40 114 7.30 65 2.34 66 5.28 179
197 0.69 109 8.32 168 7.00 168 2.24 76 5.23 66
198
(http://www.sfckarnataka.mrc.gov.in/sites/sfckarnataka.mrc.gov.in/files/GOK_-_partwise_BBMP_questionnaire_Final_27.6.2016.0.PDF). http://www.sfckarnataka.mrc.gov.in/sites/sfckarnataka.mrc.gov.in/files/GOK_-_partwise_BBMP_questionnaire_Final_27.6.2016.0.PDF http://hummedia.manchester.ac.uk/institutes/methods-manchester/docs/povertymapping.pdf