The Place Based Policies: The Way Forward to Alleviate Poverty from Cities A Study of Bengaluru India

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]

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

There is no second thought that the poverty is biggest enemy of humanity and every thought, effort and support made to defeat this enemy has to be appreciated The concept of Poverty, though tricky to define, has well understood through the long and rich debate around it The eager among the governments to know the numbers of poor in a country and region has convinced scholars to work on issues related to measurement and estimation of poverty According to Sen (1981) scholars are largely using economic approach, anthropological interpretations and somewhat capability approach to explain the characteristics of poverty The economic approach is easy to understand through income poverty line where if HH‟s income falls below a particular threshold amount that household considered as a poor, and then with calorie consumption norms where specific amount of calories decided necessary for

an individual separately in rural and urban areas and whose consumption/ intake falls below the given norm is considered poor other than that anthropological interpretations are based on people‟s own conception of disadvantage, and capability approach is defined by its choice of focus upon the moral significance of individuals‟ capability of achieving the kind of lives they have reason to value Later asset vulnerability framework has been given by Caroline Moser in 1998 This is the first time in history where poor are assessed based on what they have rather than what they do not have, simply in this approach the focus of the assessment is based on people‟s assets (Moser, 1998)

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.”

According to a famous saying, “Maps are equal to a thousand words.” And thanks to a recent developments of new statistical methodologies which made easy the small area estimations with an extensive use of powerful statistical software and computing power The role of

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 do 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)

It is evident popular opinion that urban poor are largely concentrated in slums of cities That‟s why all the welfare programmes for poor targets slum areas to distribute the benefits

of welfare schemes However, in this welfare distribution process many of the urban poor are getting excluded because there is lack of information about their existence to governing authorities The simple solution to avoid such omission is to map the poverty hotspots outside the slum areas But the census data alone is not enough to cover the multidimensionality of poverty It also needs the comprehensive survey to gather all the required information The decision of conducting a survey has its own constraints such as time, money, and other resources Therefore, by assuming that most of the poor are capital deprived; the most capital deprived wards have been identified based on census data The main objective of this chapter

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,

iv Social capital (extent of collective organisation and social networks)

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.”

Here as per the need of the study researcher has added or replaced some other important variables in Index to capture the poor areas in Bengaluru The IMD used by researcher is given below,

Deprived Capital Indicators of Deprivation

Social Capital % SC population

% 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

(http://www.sfckarnataka.mrc.gov.in/sites/sfckarnataka.mrc.gov.in/files/GOK_-_partwise_BBMP_questionnaire_Final_27.6.2016.0.PDF)

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

For Physical capital, the „Kutcha Houses‟ are defined based on the kind of material used for roof If the roof of house is made up of any of the material such as grass, thatch, bamboo, wood, mud, plastic or polythene that house is considered as kutcha house Here water is considered unsafe for drinking if it comes from any of the resources like tap water from un-treated source, uncovered well, hand pump, tube well and borehole Percentage of households using spring, river, canal, tank, lake, pond as main source of drinking water are negligible in Bengaluru therefore these water sources are kept aside from definition of unsafe drinking

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 do 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

To calculate overall deprivation, the average values of each capital are arranged ward wise and final average score is calculated For example, the final average score for ward no 1 is 15.23 this is the average of all four capital deprivations average score like social (5.62), human (17.05), financial (28.30), and physical (9.96) The final scores are arranged in order

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

Source: Census of India 2011 and Author‟s calculations

Table 1 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 7 wards common

to the overall deprived wards

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 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

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 2 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

 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

 20% SC population

 29% illiterate population