Towards a slum free city-strategies and policies: the case of Delhi

Towards a slum free city-strategies and policies:the case of Delhi

Kanhaiya Singh • Kaliappa Kalirajan

Published online: 22 February 2015� Institute for Social and Economic Change 2015

Abstract This study articulates that the objective of slum free Delhi is less likely to be

achieved through the methods of in situ upgrading or by clearing and relocation. On the

other hand in situ resettlement in high rise modern buildings is more efficient. This is

demonstrated by developing better understanding about the resistance of slum dwellers to

move away for settlement, the willingness to pay towards better housing, and economics of

land use occupied by the slum dwellers. It is concluded that given the opportunity cost of

the land occupied by the slum dwellers, it is pragmatic and at the same time economically

feasible to rehabilitate them in situ with quality accommodation. The cost analysis indi-

cates that such program would be viable solution towards twin objective of obtaining a

slum free city and affordable housing for the slum dwellers.

Keywords India � Delhi � Slums � Willingness to pay � Willingness to move �Rehabilitation

JEL Classification � R0 � R2 � I3

Introduction

Pragmatic strategy to prepare developmental plans for slum free city would require two

pronged strategy namely rehabilitation of existing slums and prevention of city from future

encroachments and formation of slums. However, such effort can be greatly facilitated by

in-depth analysis of the following broad issues: (1) issues related to the socio-economic

conditions of migrants, (2) issues related to resistance/unwillingness to move to reha-

bilitation schemes at far off locations even if highly subsidised, (3) willingness and

K. Singh (&)National Council of Applied Economic Research, New Delhi, Indiae-mail: [email protected]

K. KalirajanCrawford School of Public Policy, The Australian National University, Canberra, Australia

123

J. Soc. Econ. Dev. (2015) 17(1):66–89DOI 10.1007/s40847-015-0003-6

capacity to share cost of rehabilitation, and (4) relative strengths of alternative models of

development of slum areas and measure needed to prevent slum formation.

Key argument and objective

The paper articulates that the objective of slum free city is less likely to be achieved

through the methods of in situ upgrading or by clearing and relocation. On the other hand

in situ resettlement in high rise state-of-art modern buildings is more efficient. This is

demonstrated by developing better understanding about the resistance of slum dwellers to

move away for settlement, their willingness to pay towards better housing, and economics

of land use occupied by the slum dwellers. It is concluded that given the opportunity cost

of the land occupied by the slum dwellers, it is pragmatic and at the same time eco-

nomically feasible to rehabilitate them in situ with quality accommodation. The cost

analysis indicates that such program would be viable solution towards twin objective of

obtaining a slum free city and state of art housing for the slum dwellers.

Data for the analysis

The primary data for this paper is obtained from Centre for Global Development Research

(CGDR), which conducted a study1 for the Planning Commission of India during 2010–2011

(CGDR 2011).2 The dataset contains listing of 10,000 households and detailed survey of 2000

households randomly selected from a sample of slum clusters which were selected using

stratified random process. The stratification was done based on geographical location, size of

cluster, and year of existence of clusters. In all 477 slum clusters (Table 1) have been identified

by physical verification of each locality in Delhi and these are approximately equivalent to 860

JhuggiJhopari (JJ) clusters reported by the Municipal Corporation of Delhi (MCD), which has

been arrived on the basis of the slums demarcated by location as well as land owning depart-

ments of central and state governments.On the other hand, theCGDRSurveydifferentiates land

ownership in termsof government ownedorprivateownedonly.Thishas led to reducednumber

of clusters.However, the total numbers of JJ households comeout approximately similar in both

cases. Incidentally, only two clusters are located in private land. Some of the oldest clusters,

which came up prior to independence during 1900–1947 are located in Central Delhi.

Structure of the paper

The rest of the paper is organised in five sections. ‘‘Slums’’ section discusses growth and

profile of slums and people living in slums of Delhi; ‘‘Towards slum free city: options’’

section deals with the options for slum-free city. A proposal for slum-free Delhi is dis-

cussed in ‘‘Key issues in making slum-free Delhi’’ section, and a case is developed in

favour of in situ resettlement with high quality high rise accommodation in ‘‘Economics

of in-situ rehabilitation for delhi: a win-win model’’ section. Concluding remarks are

presented in ‘‘Conclusions’’ section.

1 The data was collected for the study ‘‘socio-economic analysis of slum areas in Delhi and alternativestrategies of rehabilitation’’ 2010–2011. We acknowledge the support of SER Division of Planning Com-mission of India provided to the CGDR for the study. However, all the views expressed in this paper pertainto the authors and it should not be associated with the Planning Commission of India.2 There are other sources of data namely National Sample Survey (NSSO) which mainly concentrates onhousing conditions in slum. However, the NSSO data lack the details required for this study.

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Slums

3The key factors behind the growth of slums are migration of disadvantaged rural

population to economically more affluent and growing cities in search of jobs and liveli-

hood. Rural to urban migration is also propelled by the demand of unskilled or semiskilled

labour in cities. Such migrants, finding it difficult to afford accommodation in regular areas

of cities tend to occupy space in unattended government land and existing slums adding

more pressure on urban space. Rapid urbanization feeds to the growth and density of such

population on unauthorised encroached land, particularly, in absence of transformation of

the cities in terms of availability of affordable and adequate infrastructure and

accommodation.

Stokes (1962) presents a theory of slum and defines slums as slums of hope and slums of

despair. Such theory is important in the sense that one can see and defines the role played

by the government and society in pushing in or pushing out a slum from category of hope

to despair and vice-a-versa. Stokes diagram is presented in Fig. 1 with some modifications.

The horizontal axis distinguishes slums of ‘‘hope’’ and slums of ‘‘despair,’’ and vertically,

escalator and non-escalator classes. An escalator class is a group of people who can be

expected, barring unusual circumstances, to move up through the class structure. A non-

escalator class is one which is denied in some way the privilege of escalation. Stokes

escalators and non-escalators are also constrained by the categories of jobs which may put

restrictions based on caste/racial/religious discrimination. However, in an equal opportu-

nity society such restrictions do not exist. On the contrary there may be a policy of

affirmative action as in the case of India, which gives better and preferential opportunities

to certain class of society considered to be deprived historically. Such opportunities may

work towards eliminating slums if applied in right earnest.

It is in this context that this paper presents fact associated with slums in Delhi that

categorise them to be slums of hope and it argues for in situ rehabilitation, which is

demonstrated to be highly feasible and at the same time remunerative for the government

under certain assumption as spelt out in Sect. 4.

Growth of slum population in Delhi

As per the CGDR exploratory survey 2010, the number of Jhuggi households was esti-

mated at 434 thousand with a population of 2.21 million during 2010. Many slums are as

old as 90 years and they serve as source of domestic and other labour for elite population

3 Discussion in this section is based on the information contained in CGDR Report (2011).

Table 1 Distribution of slumclusters and estimated house-holds by zone

Source CGDR Survey 2010

Regions Slums Slum HHs

Numbers Share (%) Number Share (%)

Central 61 12.8 23,662 5.5

East 87 18.2 85,408 19.7

North 68 14.3 79,128 18.2

South 128 26.8 140,164 32.3

West 133 27.9 105,376 24.3

Total 477 100.0 433,738 100.0

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and markets. Such slums are very well connected with infrastructure and enjoy most of the

facility including water, electricity and roads. With this estimate the share of population

living in slums appears to have come down to 14.5 % even though the absolute number of

people living in slums has increased when compared to data obtained from Census of India

2001. As per Census 2001, Delhi State had 420 thousand slum (JhuggiJhopri or JJ)

households with a population of 2.15 million (Fig. 2). This means during 2001 about

16.88 % of the Delhi population lived in slums. But this is an improvement over 1997

status when more than a quarter of city’s populations lived in slums. The situation appears

to have improved over time in terms of percentage of population living in slums.

Duration of slum occupancy by the slum dwellers

Figure 3 presents the distribution of households by number of years of stay in the slum.

About 1/3 households (30.3 %) are staying in the slum from 16 to 20 years, 16.9 %

21–25 years, 20 % for 26–30 years. About 67.2 % households are staying in slums from

16 to 30 years. Any resettlement plan of the governments requires fixing a cut-off period,

which at times becomes politically sensitive issue. With each round of election the cut year

get affected and with passing time, slum dwellers become more resistive to dislocation.

General condition of slums in Delhi

Despite several efforts and claims by the governments, most slums in Delhi suffer from

inadequate garbage disposal system, sanitation, healthcare and law and other problem

(Table 2). Slums are also marked by social problems arising out of illiteracy, gambling,

quarrel on petty matters, and threat by government officials including police, eve teasing,

and use of abusive language.

People and social structure in slums of Delhi

Slum households have migrated from 237 districts spread over 20 states; 61.49 % of the

households have migrated from 68 districts of Uttar Pradesh (UP) and 23.7 % from 36

districts of Bihar. Seventy per cent of the slum migrants come from 35 backward districts.

SlumHOPE DISPAIR

Class of Dwellers

BArotalacsE

Non-Escalator

C D

Fig. 1 Slums of hope and slums of despair

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At the district level, highest percentages of households have migrated from Balia (UP)

followed by Azamgarh (UP) and Deoria.

Majority of the slum population belongs to deprived class of the society and they are

landless people migrated from rural areas.

Fig. 2 Growth of slum population in Delhi. Source (basic data) Slum Department, Municipal Corporationof Delhi (figures from 1951 to 2001) cited in city development plan Delhi, 2006, Department of UrbanDevelopment Government of Delhi; Census 2001; and CGDR survey 2010

Fig. 3 Distribution of slum population by stretch of their stay in slums

Table 2 Infrastructure facilities in slum clusters

Sl.nos.

Zones Percentageof slumshavingstreet light

Percentageof slumswith toilet

Percentageof slumshavingwatersupply

Percentageof slumfacingirregularsupply ofdrinkingwater

Percentage ofslums havingregular visits ofMCD sweepersfor cleaning andpicking upgarbage

Percentageof slumwithcommondust binprovided bythe MCD

1 Central 54.10 83.61 93.44 49.18 70.49 73.77

2 East 59.77 59.77 95.40 36.78 43.68 43.68

3 North 57.35 58.82 92.65 67.65 47.06 52.94

4 South 52.34 82.81 98.44 53.91 57.03 68.75

5 West 14.29 78.95 94.74 66.92 16.54 9.02

All 44.03 74.21 95.39 55.77 43.61 45.91

Source (basic data) CGDR Survey 2010

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Occupations of household heads

About 90 professions can be enumerated in which slum dwellers of Delhi are found to be

engaged with. These include inter alia accountants, artists, doctors, non-government or-

ganisation (NGO) worker, auto driver, maid, barber, beautician, black smith, cooks, small

traders, mechanics, plumber, mason, hawkers, sweepers, household help, rickshaw puller,

teacher, and transport worker, etc.

Dependency ratio

Across Delhi slums, the average dependency ratio works out to be 3.54. The high de-

pendency ratio also creates economic constraints on slum dwellers and at times reflects

poor awareness about family planning. However, this also indicates that there are large

numbers of empty hands who may indulge in unsocial/unlawful activities. A higher de-

pendency ratio is also an indication of the future problems the slum dwellers are likely to

face if population from the slums are not absorbed elsewhere.

Economic gains to slums migrants

About 95 % of the households think it was a right decision to have moved out of their

native place. These households were asked about the ways in which they have gained after

leaving their native place. About 98 % of them said that they have gained by way of

improving their financial condition; 52 % better education of children; better food reported

by 61.3 %; 33.8 % reported better health.

Table 3 presents percentage of HHs by ownership of HH assets during current period and at

the time of leaving native place along with corresponding average percentage of household

reported to hold these assets during 2011 census for states of Bihar and UP fromwhere most of

the slum dwellers come. It may be observed that there is amuch larger change in the ownership

of assets by the HHs. Importantly, the Census 2011 results show much lower average per-

centage of households having the same assets in states of UP and Bihar. This clearly shows that

migration by the slum dwellers has been helpful in improving their economic condition.

Towards slum free city: options

Making cities slum free is an international agenda although many would consider it as a

utopian idea (see for example Gilbert 2007). Towards meeting the goal of slum free cities,

Table 3 Percentage of households by ownership of household assets

Household assets Percentage of householdreporting ownership

Census 2011 rural Census 2011 urban

Current Before(at native place)

UP Bihar UP Bihar

Television (color) 87.2 0.5 23.54 10.20 66.30 50.87

Mobile phone 82.8 0.4 59.44 50.07 67.22 64.43

Bicycle 73.8 8.8 71.54 48.78 55.11 48.35

Radio/transistor 44.1 5.1 24.98 25.81 23.80 25.61

Source (basic data) CGDR Survey 2010 and Census 2011

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and international initiative—‘‘Cities without Slums’’ action plan has been under imple-

mentation under the garb of Cities Alliance4 which has active support and participation of

European Union, UN-HABITAT and the World Bank. The action plan was inaugurated by

Nelson Mandela at Cities Alliance meeting in Berlin in December 1999 and the same was

endorsed by the 150 heads of state and government attending the UN Millennium Summit

in September 2000.5 The goal is: ‘‘By 2020, to have achieved a significant improvement in

the lives of at least 100 million slum dwellers as proposed in the ‘Cities Without Slums’

initiative.’’ Progress in achieving this goal will be monitored through two indicators: (i) the

proportion of people with access to improved sanitation; and (ii) the proportion of people

with access to secure tenure.6

Motivation to move towards the goal of slum free city stems from successful solution of

housing problems in cities such as Singapore, Hong Kong, Shanghai and Guangzhou which

have worked on vertical expansion, extensive development of infrastructure and civil

services. With vertical expansion same land can provide much better accommodation to

several times more households with desired standard of sanitation. It also leaves enormous

space on the ground for infrastructure development. World Development Report (WDR)

2009 reports a number of slum infected cities of yesteryears which have become today’s

world-class cities (see WDR 2009, p. 69 and box 1.7). Therefore, if cities are to remain

slum-free, it is important to have a positive conviction that slum-free cities are possible and

then proceed towards this goal with pragmatically planned and carefully designed alter-

natives with long terms perspective.

Broadly speaking there are three basic options for policies regarding slums: in situ

upgrading, clearance and resettlement, and in situ resettlement. Of course, there are other

options also such as housing vouchers and incentives to upgrading dwellings but these can

be considered as part of broader approach of in situ upgrading itself. The motive behind

these programs is to take out slum dwellers out of impoverishment.

In situ upgrading

In situ upgrading involves provisioning of basic services such as water and sanitation,

drainage, roads, etc. These projects do not involve house construction (World Bank and

UNCHS Habitat 2000, p. 14). The incremental development of homes in this model is

expected to lead to Tokyo like development which is characterised by low rises, high

density, small buildings supported by excellent infrastructure (Echanove 2008).

However, in developing countries, generally, the slum up-grading programs are funded

by international agencies and implemented through NGOs. These programs have limited

success when scrutinised at the ground level (see for example Verma 2002; Davis 2006,

p. 79; Kumar 2009).

With increasing size of the slum and congestions within the existing slums, it becomes

far difficult to improve the living condition in slums. For example, the congestion has

increased in Delhi slums from about 150 ft2/household to just over 100 ft2/household

between 1997 and 2011. With increasing congestion there is no way slum improvement

programs would be able to provide independent toilets and kitchen; and sanitation to slum

dwellers. The only possible way out is to use vertical space for housing more people per

4 http://www.citiesalliance.org/about-cities-alliance.5 http://www.un.org/millennium/sg/report/.6 City Alliance: City without Slum Action Plan: http://www.citiesalliance.org/cws-action-plan.

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unit land available and prevent further formation of slums. Thus effort towards in situ

upgrading can be termed as the case of inefficient land use and temporary dressing up.

Housing vouchers and subsidies

Some countries have experimented with housing vouchers and subsidies as instrument of

resettlement program. However, analysing the case of US Duncan and Ludwig (2000) finds

it too controversial and complicated, while for some it seems like ‘‘social engineering,’’

which violates their sense of fairness and may, in their view, reduce the incentives for poor

families to work hard (Duncan and Ludwig 2000). In the context of developing countries,

another important question is about where the poor in developing countries are to find

adequate housing. Who would be the landlords and how would they finance their housing

investments (Hoek-Smit 2008). It is also feared that such vouchers may be misused by

selling them and the beneficiary may return to another slum.

In the context of Chile and perhaps South Africa, where housing subsidies are claimed

to have reduced housing problems, questions are raised about its worth given the preva-

lence of high unemployment, and widespread poverty (Gilbert 2004). In similar context it

is argued that housing subsidies need to complement other social policy instruments, such

as family assistance, and livelihood programmes (Hall and Pfeiffer 2000).

In many countries housing subsidies are often delivered through politically appealing

programs that please the ‘‘housing sector lobby’’, but carry little relevance to any identi-

fiable social housing goals as few low-income households qualify for mortgage loans

(Hoek-Smit 2008). Housing subsidy is also faced with problem of variation in cost across

cities and across locations within the same city (Hills 2001) making it more complicated

instrument.

Clearing and relocation

Clearing and relocation involves moving slum-dwellers from present location to other

places. However, often than not such resettlements are located at far off places with poor

infrastructure and transport facility making life of displaced people worst. Thus, even if the

new housing is available, evicted slum-dwellers may not be keen to move into it (Davis

2006). In the context of famous Chilean approach of resettlement Smit (2006) notes that

the net effect of new housing projects in Santiago are often a 2 h trip away from the city

centre. As a result, although people now have better housing, many of them lose their jobs,

and they are faced with increased expenditure on transport and difficulties with access to

facilities such as schools and clinics (Smit 2006). People resist relocation also because poor

households prefer to live in communities that consist of people sharing common socio-

demographic characteristics (Kapoor et al. 2004).

In 2007, Delhi Government came out with a flagship program called Rajiv Ratan Awas

Yojana under JNNRUM for the resettlement of squatter families in Delhi. However, the

2011–2012 report of Comptroller and Auditor General (CAG) of India notes that only

10,684 dwelling could be completed during the mission period and out this only 85 could

be allotted to beneficiaries during the mission period (CAG 2013).

In terms of quality of such housing the walls have started peeling, roofs are leaking and

seepage is leading to fungal growth (see for example Menon-Sen 2011). This is one of the

major disadvantages of low cost houses. The maintenance cost may be unaffordable in

course of time.

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With expansion of city these areas with all shabbiness and poorly managed facilities

would become part of main city defeating the objective of transforming Delhi into world

class modern city. In fact, past experiments of forcible resettlements in Delhi have resulted

in similar outcomes of extreme congestions, encroachment, unauthorised unsafe con-

struction and filthiness.

In situ resettlement

In situ resettlement aims at changing the landscape of the existing slum settlement while

ensuring rehabilitation of entire population at almost the same locality in modern state-of-

the-art housing complexes. Such programs have been success in countries like Republic of

Korea, Singapore, Hong Kong and other developed countries. Among these, Singapore

experiment of resettlement is considered to be one of the most successful one (see Yuen

2004; Yusuf and Nabeshima 2006), thanks to high quality of construction and degree of

standardisation. Singapore constructed about 14,000 housing units/year during the period

of 1959–1969 with uniform height of about 12 floors, which was later increased to

25-storey.

Recently, there are efforts to develop slums in Mumbai by the Slum Redevelopment

Authority (SRA) which is also a part of Mumbai Metropolitan Region Development

Authority (MMRDA) and under different projects about 52,728 tenements have already

been constructed (Chandrashekhar 2011).

However, the MMRDA and SRA schemes are criticized by many for its bad quality of

work leading to seepages, broken down lifts and caving walls. For some of them, life is

worse than what it was when they lived in slums (Sharma 2006). Similar observation is

made by Siddhaye (2011). The problem is that the developers in these cases do not pay

much attention to quality of construction and provisioning of civic infrastructure such as

drainage, water or sanitation.

Key issues in making slum-free Delhi

The foregoing discussion suggests that in situ upgrading and resettlement at outskirt of city

will not achieve the objective of the Millennium Development Goal towards a slum free

society. In addition, there are other issues with respect to availability of land, resistance to

move and poor affordability of slum dwellers in term of willingness to pay that need to be

understood for making slum-free city an achievable agenda. We discuss these issues in

greater detail in this section. The issues are posed as the following:

(1) That the slums occupy land in areas with very high space value, (2) there are reasons

behind resistance/unwillingness of slum dwellers to move to far off location, and (3) there

is limited willingness and affordability of slum dwellers to contribute towards resettlement.

We provide exposure to these issues, which are expected to be helpful in getting the insight

about the need of in situ resettlement and at the same it would also provide validity to the

idea of high-rise high-quality accommodation proposed in this paper.

High value land locked in slum areas

Over time, with the expansion of city, most of the slums have become part of prime

locations in Delhi, which are well connected with infrastructure of Delhi. In these areas,

there is little land available for sale. The localities of slums command huge prices for

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commercial property, which were anywhere in the range of INR 7000/ft2 to INR 90,000/ft2

during 2010–2011. The region-wise average prices for commercial floor during 2010–2011

are presented in Table 4 along with rental for two room sets in those areas. The data in

Table 4 clearly shows that the lands occupied by slum dwellers are gold mines given the

growing scarcity of land per capita in Delhi.

The average monthly rent for a 2 BHK flat with representative covered area of about

900 ft2 in the surrounding area of the slum was estimated to be INR 7346 during 2010,

which would be comparable to good localities and it may improve further with conversion

of slums into better locality.

On the other hand the average rent per month for a Jhuggi was reported to be INR

847/month. Considering, average floor area of slum house to be 100 ft2 (as reported in

survey data), the per-foot rental works out to be INR 8.5, which is quite close to the market

rate.

However, ownership of a slum house is not as costly given the uncertainties associated

with the continuance of slums. The average cost of purchasing a Jhuggi in a Delhi slum

during 2010–2011 was reported to be INR 40,243 which varies between INR 48,279 and

INR 28,496 across five zones. Considering, again average floor area of slum house to be

100 ft2, the per square foot cost of owning works out to be about INR 285/ft2 to about INR

483/ft2, which is extremely cheap by any standards for Delhi. However, this information

suggests about the average capacity/affordability of slum dweller to pay if he/she were to

pay towards resettlement shelter, while keeping him viable to survive in Delhi.

Resistance to move away from present location to far off subsidized housing

On the issue of rehabilitating the slum dwellers it is advocated from several quarters

specially the social activists that the slum dwellers should be rehabilitated in the same area

or in a close proximity on the plea that they earn their livelihood by working at places close

to their slum. In case they are thrown off to far flung area they would lose their livelihood

or have to spend a lot of time and money on travelling (see Mitra 2010 for issue on urban

employment for slum dwellers).

The survey data indicates that the industrial areas, local markets, and residential areas

are major employers for slum dwellers. The distribution of HH head by distance of their

place of work from the slum assumes importance. It is found that 11.0 % of the HH head

Table 4 Average commercial property price, average cost (INR) of purchasing one room in slum; averagerent (INR) for one room in slum and average rent (INR) of 2 BHK in the surrounding slum locality

Sl. nos. Zones Average commercialproperty price(INR/ft2 floor)

Rent for 2 BHKin surroundingarea (INR)

Cost ofone roomin slum

Rent forone roomin slum

1 Central 50,948 6018 48,279 1054

2 East 7624 6213 43,471 648

3 North 59,000 7947 44,603 952

4 South 36,922 8273 44,109 938

5 West 16,007 7457 28,496 740

All 30,914 7346 40,243 847

Source CGDR Survey 2010

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appear to be working next door. About 45.8 % travel 1–5 km distance, 2.4 % 6–10 km

distance. Thus, distance of work place is important criteria in willingness to move.

Given the nature of job the slum dwellers are engaged in, relocating them in suburban

areas would be too costly for their survival. At present there is a synergy between the

means of livelihood, current locations of slums and the job markets. Therefore, it is

legitimate to ask slum dwellers, whether they would be willing to move to a faraway place

under any resettlement plan of the government. In line with expectations, about 89 % of

the households are not willing to move to a faraway place. The underlying fear is job

insecurity, which they would find hard to get. The new place may or may not be conducive

to the kind of job they do. However, there are 11.0 % people who said that they can opt for

an accommodation at faraway place from their present location, which leads to a possi-

bility of creating options with differential pricing, whereby some people can be motivated

to take up resettlement at the outskirts of city. It is also possible that this percentage could

increase under better offers such as larger accommodation or higher subsidy.

Explaining the resistance to move: effects of distance, income and social grouping

It is important to explain the reasons of resistance to move out to new site and identify the

characteristics of respondents who are not willing to move. Such information would be

helpful in correlating the rehabilitation policy with the welfare schemes of the government.

In order to understand the characteristics of those not willing to move a simple econometric

decision model with limited dependent variable is estimated using the survey data. Here,

the choice problem is as follows: given options to choose between (1) a rehabilitation

program in which the slum dweller is offered a highly subsidised flat in a far off location

and (2) stay back in the existing slum. This decision problem can be solved by estimating a

bivariate probit model. Let the decision to opt for moving out of the slum in favour of

rehabilitation program by a slum dweller i at time t be given by:

I�it ¼ Zitdþ wit; ð1Þ

where I�it is a variable that reflects an individual option if choice is available, Z is a vector

of determinants of choosing such option, d is the corresponding vector of coefficients, and

w is a normal random variable with mean zero and a unit variance. Variable I�it is unob-servable, but a dummy variable Iit is observed and defined by:

Iit ¼ 1 if I�it � 0 ðopt for rehabilitation program at far off locationÞ;Iit ¼ 0 otherwise ðopt for stay back if choice is availableÞ: ð2Þ

Equations (1) and (2) facilitate the working out the probability of choice model for the

slum dwellers:

Prob Iit ¼ 1ð Þ ¼ Prob wit � � Zitdð Þ ¼ Prob wit � Zitdð Þ: ð3Þ

The probability of selecting to stay back in existing slum is equal to [1 – Prob.

(wit B Zitd)]. Equations (1) and (2) constitute a simple probit model. Thus, the decision

probability can be represented as a linear function of the determinants of willingness to

move out of existing slum in favour of rehabilitation at a far off location, which can be

estimated using statistical software.

The results presented in Table 5 clearly indicate the following factors playing important

role in decision process.

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Income of household The probability of choosing to move to a far off locality for re-

habilitation reduces with increasing income of household head. This means that households

that have attained some kind of stability in income due to local opportunities and economic

environment do not want to be disturbed. Their efforts are further complemented by the

fringe benefits provided by the government in slum areas. They are fearful of losing both.

Deprived class Probability of choosing to move also reduces if the household belongs to

scheduled caste. It may be noted that this group of people are offered almost free housing

under welfare program and yet they are not willing to move. This clearly shows that

employment and other opportunities provided by the location are paramount.

Permanent structure of dwelling Probability of choosing to move also reduces if the

household has built permanent house or a separate toilet. Permanent house and separate

toilet are also indicators of the fact that the household is progressive and fall under the

category of elevators.

However, the probability of choosing to move increases with increasing size of occu-

pied floor area if house is still temporary (see the interaction term ‘intpuccaarea’, as also if

household is landless or belongs to Muslim community. Such people may be classed as less

capable early settlers who occupied larger area but could not improve their condition. For

such people it does not matter whether they remained at current location or at a far off

place. Nevertheless intervention for such people would require both in terms of housing as

also capacity building.

Distance of work One of the interesting results is about the effect of distance of work

place. Distance of work has non-linear relationship with willingness to move. With in-

creasing distance of current work place willingness to move increases but if distance is

Table 5 Willingness to move to a far off location of rehabilitation: probit regression

Dependent Willingness to move (yes = 1) W_Move

Regressors Symbol Coefficient SE z P[ |z|

Household annual income incm_hh_th -0.0074 0.0024 -3.1300 0.0020

Distance of work distanc_work 0.4974 0.1408 3.5300 0.0000

Square of distance of work distance2 -0.0818 0.0227 -3.6100 0.0000

Toilet toilet -0.9569 0.4737 -2.0200 0.0430

Whether landless landless 0.3279 0.1309 2.5000 0.0120

Floor area area_floor 0.0086 0.0013 6.5500 0.0000

Permanent room 9 floor area intpuccaarea -0.0056 0.0010 -5.3400 0.0000

Whether scheduled cast sc -0.2798 0.1106 -2.5300 0.0110

Whether Muslim mus 0.4809 0.1348 3.5700 0.0000

_cons -2.4343 0.2950 -8.2500 0.0000

Number of observations 1457

Pseudo R2 0.17

Likelihood -394.49

LR v2(12) 159.7

Correctly classified 90.3

J. Soc. Econ. Dev. (2015) 17(1):66–89 77

123

beyond a threshold (which works out to be about 6 km), willingness to move starts

reducing. For persons working too far away places rehabilitation at far off place may not be

an important constraint as they already are coping with the distance. Optimal distance

works out to be about 6 km, which can be covered on bicycle or foot. It may be noted that

all the resettlement localities chosen by the government are distances as far as 20–40 km

from the central city areas as compared to the critical 6 km circle.

To summarise the characteristics of people not willing to move include persons be-

longing to weaker section who on account of affirmative action qualify for almost free

housing, and those who have shown considerable effort in changing their economic con-

ditions. Such population can be classified as hopefuls who are constrained by the cost of

city accommodation. A solution to their shelter may be able to unleash their potential for

higher ladder of living conditions of city life.

Willingness to pay and limit of affordability to pay towards resettlement

The lack of security of tenure of the land is associated with uncomfortable uncertainties,

which has a cost, and the same is reflected in restrained expenditure on dwellings. In order

to come out of this uncertainty, the slum dwellers should be ready to pay either in terms of

lump sum payment or monthly instalments for a given benefit which brings certainty in

their living conditions.

The households were asked as to how much amount slum dwellers could afford towards

a resettlement scheme for a built up one room flat of 25 yards area. About 67.6 %

households report that they can pay below INR 500/month with average for this group as

INR 419 (Table 6). Another 27.25 % people could pay between INR 501 and INR 1000

with average value of INR 910. Thus, about 95 % households report a monthly capacity of

below INR 1000 with average value of INR 610. About 4.1 % households can afford to pay

between INR 1001 and INR 2000 with an average of INR 1591. There is small minority of

people who could pay even more.

Distribution of households reporting amount a household can afford to pay as one-time

payment on an average towards resettlement scheme is presented in Table 6. About 67.1 %

households report that they can pay below INR 5000 with average for this group as INR

3574 (Table 7). Another 30.03 % people could pay between INR 5001 and INR 10,000

with average value of INR 9840. Thus, about 97 % households report a monthly capacity

of below INR 10,000 with average value of INR 5519. However, there is small minority,

who could afford anything up to INR 100,000. Possibly, this is the latter groups who would

be even willing to move out of their own. The important message is that there is difference

in capacities and people would like to make choices if available. However, compared to

this amount, the demand of INR 60,000 by the Delhi Government looks to be exorbitant.

Thus, despite willingness to pay the real capacity is very low.

Factors affecting willingness to pay

Given the large variation in amount that the slum dwellers are willing to contribute towards

resettlement cost, it is a pertinent question to ask whether these amounts have any sig-

nificant relation with the economic and social conditions of slum dwellers. If there is some

valid relationship, then it would also be legitimate to consider the revelations on afford-

ability to be genuine. It would also provide some argument for the government if it has to

differentiate the housing structure based on difference in capacity of slum dwellers to

contribute. It is also helpful in understanding the response of social group.

78 J. Soc. Econ. Dev. (2015) 17(1):66–89

123

To answer these questions, a simple econometric model is estimated and the

heteroscedasticity corrected regression results are presented in Table 8. The R2 of the

regression is small, yet it can be used to make inference given the large number of

observations (over 10,000) and cross-sectional nature of data. There are number of sig-

nificant variables of interest and the results clearly indicate the following.

Table 6 Distribution of households by monthly instalment a household on an average can pay

Distribution of affordability with respect to monthly installments

Affordability (INR) Central East North South West All

Installment (INR) ranges Average

1–500 419 67.92 59.00 71.58 68.89 69.75 67.59

501–1000 910 24.92 35.40 24.22 25.68 25.52 27.25

1001–1500 1404 3.37 1.03 2.71 3.19 3.82 2.84

1501–2000 2000 1.45 2.17 1.00 1.74 0.20 1.30

2001–2500 2500 0.00 0.23 0.00 0.00 0.00 0.04

2501–3000 3000 0.00 0.00 0.00 0.15 0.18 0.09

3501–4000 4000 0.00 0.23 0.00 0.00 0.18 0.09

4501–5000 5000 1.52 0.69 0.25 0.07 0.35 0.38

5501–6000 6000 0.00 0.23 0.00 0.00 0.00 0.04

6501–7000 7000 0.00 0.29 0.00 0.14 0.00 0.10

9501–10,000 10,000 0.00 0.51 0.00 0.14 0.00 0.15

14,501–15,000 15,000 0.00 0.23 0.00 0.00 0.00 0.04

19,501–20,000 20,000 0.81 0.00 0.25 0.00 0.00 0.09

All 681 100 100 100 100 100 100

Source CGDR Survey 2010

Table 7 Distribution of affordability with respect to down payment for 25 yards flat

Distribution of affordability with respect to down payment for 25 yards flat

Affordability (INR) Central East North South West All

Down payment (INR) Average

1–5000 3574 97.31 65.72 84.85 60.32 63.64 66.71

5001–10,000 9840 0.00 23.31 13.63 36.28 34.04 30.03

10,001–15,000 14,627 0.00 5.77 1.52 2.58 0.47 1.77

15,001–20,000 20,000 0.00 2.75 0.00 0.00 0.00 0.18

20,001–25,000 25,000 2.69 2.45 0.00 0.38 0.00 0.48

25,001–30,000 28,000 0.00 0.00 0.00 0.00 0.43 0.15

35,001–40,000 40,000 0.00 0.00 0.00 0.00 0.94 0.33

45,001–50,000 50,000 0.00 0.00 0.00 0.00 0.47 0.17

95,001–100,000 100,000 0.00 0.00 0.00 0.44 0.00 0.18

All 6160 100 100 100 100 100 100

Source CGDR Survey 2010

J. Soc. Econ. Dev. (2015) 17(1):66–89 79

123

Effect of income With increasing income the slum dwellers demonstrate ness to pay

higher amount in both options of monthly instalment or lump sum amount. Such will-

ingness can be exploited to design different quality of housing with contributions from the

slum dwellers.

Number of years in slum Number of year after arrival is a variable that indicates survival

instinct in Delhi and the regression result shows that dwellers with longer duration of stay

are willing to pay higher amount as instalment but a lower amount as lump sum.

Education of household head Education years of household head have positive effect on

the willingness to pay for rehabilitation and it increases with the year of education. Clearly,

this demonstrates that Delhi slums are slums of hope and education has paid dividend in

terms of increasing the capacity and willingness to pay for better accommodation. How-

ever, it may be seen from earlier discussion that the sums proposed by the slum dwellers

for payments towards rehabilitation are too little for Delhi to get any place without ad-

ditional support.

Land ownership Whether slum dweller is landless (dummy variable) has negative effect

on the amount a slum dweller is willing to pay either as instalment or lump sum.

‘Rented’ dwelling Whether dwelling is rented (dummy variable) has negative effect on

the amount because the slum dweller may not be entitled to any such benefit in absence of

proof of ownership. Therefore, his commitment is full of risk.

Table 8 Least square estimate for amount willing to pay towards rehabilitation

Dependent variables White heteroskedasticity-consistent standard errors and covariance

Variable (code) WTOP_LUMPSUM WTOP_MNTHLY

Included observations 10122 10123

Variables Coefficient Prob. Coefficient Prob.

C 5509.64 0.00 480.57 0.00

Monthly income of the household HH_CUR_Y_MONTHLY 0.26 0.00 0.03 0.00

Number of year after arrival HH_YEAR_ARRIVAL -12.98 0.05 2.53 0.00

Education years of householdhead

HHH_EDU 110.36 0.00 3.15 0.01

Whether slum dweller is landless LANDLESS -2241.65 0.00 -95.79 0.00

Whether dwelling is rented RENTED -1188.30 0.00 -117.77 0.02

Whether dwelling has toilet TOILET -465.01 0.03 -57.96 0.06

Age of household head AGE 19.74 0.00 -0.75 0.09

Whether occupant is otherbackward caste

OBC -16.85 0.07

Whether occupant is Muslim MUS -806.81 0.00

R2 0.05 0.05

F-statistic 60.9 65.50

Prob.(F-statistic) 0 0.00

80 J. Soc. Econ. Dev. (2015) 17(1):66–89

123

Age of household head Age of household head has negative effect on the monthly in-

stalment but it has positive effect on the lump sum payment. It may be because of the fact

that many young persons have higher income and they can pay larger monthly instalments

but they do not have requisite credibility to get loans or have accumulated savings which

could be used to pay in lump sum. On the other hand monthly income of older persons may

not be enough and that is why they would like to exchange their savings with new shelter.

Presence of separate toilet Presence of separate toilet (whether dwelling has toilet-

dummy variable) in the slum house has negative effect on the amount a slum dweller is

willing to pay. Having separate toilet is indicative of progressive household but it also

indicates sunken investment. It is also possible that such slum dwellers are more estab-

lished and have realised over time the constraint faced by government in displacing them.

Therefore, they do not want to pay more even if they could.

Social group Social grouping of the occupant also affect the amount a slum dweller is

ready to pay. It comes out that a person belonging to other backward class tend to agree for

smaller amount as instalment while a person belonging to Muslim community tend to agree

for smaller lump sum amount.

The above exercise validates the fact that there are explanations and hence valid reasons

for slum dwellers to resist dislocation and at the same time their capacity to pay is limited

although there is willingness to contribute. Therefore, towards meeting the objective of

slum-free modern city, the government need to make wise policy given the value of space

in slum areas is very high. The estimates presented below would demonstrate that it would

be good bargain to rehabilitate slum dwellers in situ in high rise spacious buildings.

Economics of in situ rehabilitation for Delhi: a win–win model

Considering the employment avenues and flexibility required for modern planning in situ

rehabilitation has better potential. In addition, growing urbanisation with flat (low rise)

structure consumes large agriculture land at greater pace leading to a situation of food

insecurity. By adopting strategy of vertical expansion of cities enormous agriculture land

can be saved. However in the case of Delhi a sizable number of slums are located closer to

railway lines and severe lines, and these are not good cases for in situ rehabilitation. Such

slums can be merged with other slums in the vicinity for rehabilitation. Accommodation in

modern high rise apartment is flexible as it can be made spacious, with centralised supply

of water, electricity and communication. Enough space is left on the ground for roads,

hospitals, schools and other infrastructure. With larger space for accommodation, it is

easier to negotiate with the slum dwellers to move out for resettlement. A detailed eco-

nomic analysis presented in the following section would reveal that accommodation as

large as 800 ft2 is possible even free of cost if buildings are allowed to acquire sufficient

height. However, it is cautioned against temptation of planning free housing. Rather,

affordable fee should be charged to generate funds for community healthcare, education

and maintenance.

The basic premise of proposition is centred on pragmatic concerns such as scarcity of

land, market value of commercial floors, capacity of slum dwellers to pay and need of high

J. Soc. Econ. Dev. (2015) 17(1):66–89 81

123

quality accommodation fitting into the concept of modern capital city of Delhi. It is

demonstrated below that the returns from the sale of surplus space that can be created in

the land occupied by the slums under feasible assumptions is huge enough to take care of

good accommodation as well as all other welfare benefits that can reasonably be thought

of. The basic assumptions and survey results applicable for the estimations are as follows:

(1) Most of the land occupied by the slum dwellers belongs to different organs of central

and state government and there would be no problem in transferring these lands to

one implementing agency. Since, these lands are anyway occupied for decades;

there is no reason to believe that those are not transferable or have strategic value.

Had it been so, slum would not have been allowed to crop up.

(2) The other important assumption is that the government is competent and willing to

re-examine the land use pattern and increase the floor space index (FSI) in line with

several world class cities. This is very critical and globally accepted strategy. With

this assumption it is possible to calculate several options with respect to floor area to

be allocated to slum dwellers.

(3) Cost of construction (excluding the cost of land) is assumed to be INR 1800/ft2,

which is about 60 % of average selling price of quality high rise residential property

in NCT region. This is one of the expensive construction costs and the same is

assumed to cover the provisioning of sanitation, ventilation, hygiene and light in the

same way as it is the case in any modern day high rise residential complex.

(4) The total ground area covered by the 477 slum clusters under consideration can be

arrived at by multiplying the estimated number of households with average floor

area of 100 ft2 and a factor of 1.1 to take into account walk ways and other common

space. This translated into an effective ground area of 443 ha covered by the slums

with an inhabitation of 433,738 households. This is highly conservative estimate

compared to overall slum affected areas estimated by the government which is

reported to be of the order of 700 ha.

(5) For the purpose of this analysis, it has been assumed that only 40 % of the occupied

land can be used for construction leaving aside 60 % space to meet statutory needs,

roads, dispensary, community centre, shops, etc. Also this would take care of some

of the slums which cannot be rehabilitated due to space constraints. Thus, effective

plinth area to be used for in situ construction would be about 177 ha.

(6) As discussed earlier, the average market price of floors in commercial buildings

around the slum clusters is estimated as INR 30,900/ft2. This allows estimation of

the value of commercial construction generating saleable floor.

(7) Finally, for simplicity it is assumed that the height of commercial and residential

blocks would be similar and that these blocks could be separate or mixed as per

convenience and location mainly being determined by the saleability of the

commercial space. The value of commercial floors is assumed to be the average for

all floors and all localities, which in fact, may vary significantly across regions. It is

also important to know that the cost of construction of commercial building would

be much less as compared to the assumed value, which is applicable to residential

buildings. The analysis throws a wide range of options and even if commercial floor

are lesser in number than the residential floor, the conclusion holds because

surpluses are huge. It is easy to calculate the zero surplus cases, which would show

82 J. Soc. Econ. Dev. (2015) 17(1):66–89

123

the minimum number of commercial floors that would be required to construct but

such results are abstracted for the brevity of presentation.

Benefits under alternative options

With above assumption calculation of net benefit to government is calculated under several

alternatives heights of building with varying FSI and different payments terms for slum

dwellers including free supply. The details of two model calculations with offered floor

area of 270 and 800 ft2 are presented in Appendix Tables 10 and 11, while a range of

simulated options are summarised in Table 9.

With assumption of utilising 40 % of slum area, the available ground for rehabilitation

works out to be about 19.1 million ft2. Next the total floor area required for accommodating

433,738 households is calculated. This is fixed by the unit floor area decided to be offered.

In this case it is 275–800 ft2. With this range the floor area to be distributed for residents

works out to be 117.1 million–347.0 million ft2, respectively.

With different FSI the floor area that can be constructed is indicate in Appendix

Tables 10 and 11 for two example cases. Out of this area, the area to be given to slum

dwellers is subtracted to obtain the floor area that would be available to government for

sale. Another source of revenue is assumed to be the contribution made by the slum

dwellers. With the cost of construction assumed to be INR 1800/ft2 which is reasonable for

high quality construction, the net benefit to government is calculated by subtracting cost of

construction from sale realisation of the surplus floor area and adding the contribution from

slum dwellers. The same is presented in bottom rows of Appendix Tables 10 and 11 for

two selected cases. For number of additional (but not exhaustive) cases the amount of

surpluses are estimated and presented in Table 9.

Clearly, the net benefit to government increase with height of building and it reduces

with increasing floor size to be offered to dwellers. The amount of surpluses are substantial

running in thousand crore of rupee. For example even with free supply of 800 ft2 dwelling,

government could generate a surplus of INR 608 thousand crore7 if the building height is

30 floors. These calculations are indicative of the possibilities of land use and the welfare

gain that can be promised to society. Many more alternatives can be worked out after

assessing the engineering feasibilities about the building design. Even heights of

residential and commercial buildings can be differentiated based on engineering options

available.

Thus, it is also feasible to give accommodation to slum dwellers even free of cost,

which of course is not a desired proposition given the fact that most slum dwellers have

some capacity to pay. However the fund collected through contributions from slum

dwellers and other surpluses can be pooled to create a corpus that can be used to for

maintenance of the building, payments towards group health insurance and other fa-

cilities such as education for the residents of rehabilitated society for ever. The contri-

bution from the beneficiaries can be collected as rental or a lump-sum fee towards right

to live. The basic land right for the area occupied by the beneficiaries may rest with

government agencies while rights of commercial floors would have to be transferred to

buyers.

7 One crore = 10 million.

J. Soc. Econ. Dev. (2015) 17(1):66–89 83

123

Table

9Summaryofadditional

alternatives

obtained

throughsimulatedsurplusgenerationwithchangingFSIandfeasible

buildingheightfordifferentfloorareasof

dwellingsandcontributionfrom

slum

dwellers

Sim

ulatedsurplusgenerationwithchangingFSIandfeasible

buildingheightfordifferentfloorareasofdwellingsandcontributionfrom

slum

dwellers

(INR000crore,1

crore

=10million)

Alternative

plan

Dwellingfloor

area

(ft2)

ContributionIN

R/ft2

byslum

dwellers

7-Floors

buildings

11-Floors

buildings

16-Floors

buildings

21-Floors

buildings

25-Floors

buildings

30-Floors

buildings

FSI

2.8

4.4

6.4

8.4

10

12

Contributionbyallslum

dwellers

inaffordable

range

270

125

26.86

242.14

511.23

400

125

73.68

342.77

611.87

Freedwellings

270

025.40

240.67

509.76

400

071.51

340.61

609.70

600

080.36

349.45

564.73

800

089.21

304.48

573.58

Dwellingsat

verynominal

rate

ofIN

R100/ft2

270

100

26.57

241.84

510.93

400

100

73.25

342.34

611.43

600

100

82.97

352.06

567.33

800

100

92.68

307.95

577.05

Dwellingsat

verynominal

rate

ofIN

R500/ft2

270

500

31.26

246.53

515.62

400

500

80.19

349.28

618.37

600

500

93.38

362.47

577.74

800

500

106.56

321.83

590.92

Dwellingsat

nominal

rate

of

INR1000/ft2

270

1000

37.11

252.38

521.47

400

1000

88.86

357.96

627.05

600

1000

106.39

375.48

590.75

800

1000

123.91

339.18

608.27

84 J. Soc. Econ. Dev. (2015) 17(1):66–89

123

Implementation: high financial stakes and need for careful planning

Given the possibility of huge surpluses arising out of the in situ settlement program, the

financial stakes are very high and there is apprehension of involvement of vested interests

and land grabbers. Market forces may not always work in the interest of slum dwellers and

therefore leaving them to market would be detrimental to rehabilitation plan (see for

example Dafe 2009). City land is costly and scarce and it provides ample opportunity for

those who have vested interest and profit motives. Therefore, a more transparent system

with adequate government intervention and participation of NGOs and local community

may be essential.

Choice of model of implementation is important. Any model that has profit motive,

whether private centric or in the public–private partnership mode, may not deliver full

benefit. What is needed is the participation of philanthropists under a program that may be

called pro-poor philanthropic public–private partnership (P-6). A P-6 model of this kind

would ensure that the surpluses generated are utilised for welfare programs. It is essential

to take out profit motive from the program. Therefore, such model may even be imple-

mented entirely by the government itself in mission mode with time bound and transparent

approach. Here, Singapore experience can be useful insight. Another approach could be

through a cooperative society or government promoted autonomous body.

Sometimes planners tend to leave everything to market forces for slum resettlement. But

they fail to realise that market forces have no welfare motive for slum dwellers and slum

dwellers have no capacity to fight with the developers. In absence of assurance of genuine

intervention and monitoring by the government, any rehabilitation program would be

viewed with suspicion leading to failure.

It is also important to change the mind-set of the government and the developers, who

tend to discriminate in quality parameters under a biased attitude about the perspective

inhabitants. The fact that such rehabilitation is planned for slum dwellers should not lead to

compromises with respect to investment and selection of design, and monitoring of quality

and quantity of material used for construction. In order to have access to the best possible

design of flats and eco-system for slum rehabilitation, academic institutions, students,

professional bodies and individuals from civil society could be involved by inviting

competitions, organising seminars and conferences, etc. An award based invitation may be

motivating factor in this effort.

Conclusions

Survey results clearly show that slum dwellers are not interested in going back to their

native places. They wish to continue in Delhi and benefit from the fruits of future de-

velopment of Delhi. On the issue of resettlement by government, majority of slum dwellers

are not willing to move to a far off place from the present location in the fear of losing their

source of livelihood, children’s education, and access to basic amenities. It is also im-

portant information that majority of slum dwellers are willing to make contribution to-

wards resettlement plan albeit nominal and such contribution has wide variations. Such

variation provides additional tool to differentiate between the type and location of the

resettlement according to the difference in willingness to pay.

The calculation of in situ rehabilitation in high rise buildings with modern design

indicates it is one of the highly feasible solutions of rehabilitation. However, to make any

slum rehabilitation program a success story, meticulous planning and participation of

J. Soc. Econ. Dev. (2015) 17(1):66–89 85

123

community is essential. In India, FSI norms are very small as compared to countries such

as Malaysia, Singapore, and China. Modifications in these norms are essential to imple-

ment efficient strategies. The net benefit to government increase with floor height of

building and it is substantial amount running in thousands of crore rupee. These calcula-

tions are indicative of the possibilities of land use and the welfare gain that can be

promised to society. It is also feasible to give accommodation to slum dwellers even free of

cost or alternatively a corpus can be created to maintain health insurance and other fa-

cilities such as education for the residents of rehabilitated society for ever.

However, given the financial stakes and fear of vested interest the implementation of the

project should be dome done through a P-6 model without profit motive. Such P-6 mode of

participation of private sector with government would require bringing in philanthropic

approach by private sector where surpluses are allowed to be used for social welfare.

Alternatively, the entire project would be better off under a cooperative society or gov-

ernment promoted autonomous body or the government itself.

The objective of slum-free city cannot be met without concerted effort to stop breeding

of new slums. Despite several attempts of resettlement programs for slums during post-

independence period, mushrooming of slums went unabated across the entire city of Delhi,

which indicates serious negligence and apathy on the part of local administration including

local police and MCD/DDA officials.

It is a well-known proverb, ‘prevention is better than cure’. However, prevention

strategy must be based on sound knowledge about the source, symptoms, and quantum of

the problem. Migration of rural labour to cities should be recognised as an essential evil

and it will increase with increasing industrialisation and services sector. Therefore, any

planning process for the industrialisation and services sector must include the issue of

accommodation for labour as an integral part of development.

Therefore, along with implementing rehabilitation and resettlement schemes it is

essential to take strong and effective measures to check further growth of slums by fixing

responsibility and provisioning strong punishment for those who show negligence to the

duty assigned for the purpose. It is beyond comprehension that slums could develop and

continued to flourish without protection of powerful lobby of vested interests.

It is also suggested to motivate and encourage industrial complexes to build accom-

modation for labour staff quarters. Every industrial city should have a well-planned labour

colony attached to it. Indian Railways is an outstanding example of accommodation

provider for almost all its staff. A similar model can be developed with private sector

participation for workers in each industrial estate. These accommodations could be owned

by a cooperative of industrialists in the region.

Appendix

See Tables 10 and 11.

86 J. Soc. Econ. Dev. (2015) 17(1):66–89

123

Tab

le10

Indicativecostandbenefitsofresettlementunder

alternativestructure

ofbuildingswithlimited

variablesonly

(exam

ple-1)

Alternativeconstructionforrehabilitation

Details

Units

Values

7-Floors

buildings

11-Floors

buildings

16-Floors

buildings

AAssumptions

1Estim

ated

number

ofhouseholds

N433,738

2Averagefloorarea

covered

byslum

dwellers

ft2

100

3Factorto

cover

unconstructed

area

Ratio

1.1

4Estim

ated

area

ofgroundcovered

byslums

ft2

47,711,180

5Groundcover

forconstruction

Ratio

0.4

6Groundarea

available

forconstruction

ft2

19,084,472

7Cost

ofconstructionofgoodqualityflat

INR/ft2

1800

8Averagemarket

price

ofcommercial

floorin

slum

areas

INR/ft2

30,000

9Contributionfrom

slum

dwellers

atIN

R/ft2

125

10

Floorarea

tobegiven

toslum

dwellers

atft2

270

11

Approxim

ateaverageFSI

Index

2.8

4.4

6.4

BEstim

ates

1Number

offloors

tobeconstructed

A7

11

16

2Floorarea

available

inbuilding

ft2

133,591,304

209,929,192

305,351,552

3Floorarea

tobegiven

toslum

dwellers

ft2

117,109,260

117,109,260

117,109,260

4Floorarea

leftforsale

ft2

16,482,044

92,819,932

188,242,292

5Cost

ofconstructionofentire

area

at‘‘A’’

INRcrore

24,046

37,787

54,963

6Realizable

valuefrom

saleable

floorarea

INRcrore

49,446

278,460

564,727

7Realizable

valuefrom

slum

dwellers

INRcrore

1464

1464

1464

8Benefitto

governmentavailable

forsocial

expenditure

andsharingwiththedevelopers

INRcrore

26,864

242,136

511,227

Shareofarea

sold

12.34

44.21

61.65

J. Soc. Econ. Dev. (2015) 17(1):66–89 87

123

Table

11

Indicativecost

andbenefitsofresettlementunder

alternativestructure

ofbuildingswithlimited

variablesonly

(exam

ple-2)

Alternativeconstructionforrehabilitation

Details

Units

Values

21-Floorbuildings

25-Floorbuildings

30-Floors

buildings

AAssumptions

1Estim

ated

number

ofhouseholds

N433,738

2Averagefloorarea

covered

byslum

dwellers

ft2

100

3Factorto

cover

unconstructed

area

inslums

Ratio

1.1

4Estim

ated

area

ofgroundcovered

byslums

ft2

47,711,180

5Groundcover

forconstruction

Ratio

0.4

6Groundarea

available

forconstruction

ft2

19,084,472

7Costofconstructionofgoodqualityflat

INR/ft2

1800

8Averagemarket

price

ofcommercial

floorin

slum

areas

INR/ft2

30,000

9Contributionfrom

slum

dwellers

atIN

R/ft2

1000

10

Floorarea

tobegiven

toslum

dwellers

atft2

800

11

Approxim

ateaverageFSI

Index

8.4

10

12

BEstim

ates

1Number

ofstoreyto

beconstructed

A21

25

30

2Floorarea

available

inbuilding

ft2

400,773,912

477,111,800

572,534,160

3Floorarea

tobegiven

toslum

dwellers

ft2

346,990,400

346,990,400

346,990,400

4Floorarea

leftforsale

ft2

53,783,512

130,121,400

225,543,760

5Costofconstructionofentire

area

at‘‘A’’

INRcrore

72,139

85,880

103,056

6Realizable

valuefrom

saleable

floorarea

INRcrore

161,351

390,364

676,631

7Realizable

valuefrom

slum

dwellers

INRcrore

34,699

34,699

34,699

8Benefitto

governmentavailable

forsocial

expenditure

and

sharingwiththedevelopers

INRcrore

123,910

339,183

608,274

Shareofsold

area

13.4

27.3

39.4

88 J. Soc. Econ. Dev. (2015) 17(1):66–89

123

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