This document summarizes key points from a presentation on informal settlements in India. 1) A larger share of people live in slums in larger cities, but most slum dwellers are in smaller cities. Over time, this pattern has remained valid. 2) Regardless of whether slums are officially notified, a certain level of public services are provided to slums, and the situation is improving over time, supplemented by self-provision. 3) Industries that employ slum residents are not much different from the rest of the city, but occupations differ, with fewer managers/professionals and more craftspeople in slums. This implies different grades of workers live in different city neighborhoods.

1. Working Group II: Session III
Hippocrates and the Beatles
Lessons for Informal Settlements
Partha Mukhopadhyay
Centre for Policy Research

2. Basic Facts in India
• A larger share of people live in slums in the larger
cities but the larger share of slum dwellers are in the
smaller cities
– This pattern is valid over time
• While much is made of “non-tenable” locations, it
does not seem to affect notification (recognition)
– Perhaps an issue in larger cities
• Regardless of whether they are notified, a certain
level of public services is provided to slums
– Situation improving over time
– Supplemented by self-provision, especially in big cities
2

3. In Slums: Similar Industries of employment
3
Difference of proportion of employment in slums and other areas by Industry
-20%
-15%
-10%
-5%
0%
5%
10%
15%
20%
Foodmanufacture
Clothing&footwear
Machinerymanufacture
Othermanufacture
PublicUtilities
Construction
Govt.Services
TraditionalServices
ModernServices
SocialServices
HouseholdServices
Million Plus Non Million Mumbai
Note: Positive difference implies higher proportion employed in slums.
Data Source: NSS 65th Round Housing Conditionsand Amenitiesin India 2008-09

4. But, different jobs
4
-20%
-15%
-10%
-5%
0%
5%
10%
15%
20%
Managers
Professionals
Technicians
Clerks
Serviceandsales
Craftandtrades
Machineoperators
Elementary
Occupations
Others
Million Plus Non Million Mumbai
Lower
share in
slums
Higher
share in
slums
Difference of proportion of employment in slums and other areas by occupation
Note: Positive difference implies higher proportion employed in slums.
Data Source: NSS 65th Round Housing Conditionsand Amenitiesin India 2008-09

5. Take-away
• Industries of employment of slum residents not much
different from the rest of the city
– Clothing and Footwear is more “slum-intensive”
e.g., see Pani and Singh (2010)
• Employs a lot of the richer slum residents
– Construction employs a lot of poorer slum residents
• Traditional Services, i.e., trade, hotels, retail and
transportation is a big employer
– Household services not a huge number, despite the popular
perception
• Slums are important for the city, not just for the personal comfort of
richer city dwellers
• Modern services is not insulated from employees who live
in slums
5

6. Take-away
• Occupations of slum residents differ somewhat from
the rest of the city residents
– Fewer managers, professionals and technicians and more
craftsmen, tradesmen and elementary occupations
among slum residents
• Coupled with similarity in industries of employment,
this implies that different grades of workers in the
same industry live in different types of city
neighborhoods
– Deep interlinking, where no industry is insulated from
actions that affect slum neighborhoods
• Reinforces the integral nature of slums to the
economy of the city, whether larger or smaller
6

7. Private (Individual sector) Slum development
• Slum residents undertake a
significant amount of
construction
– Conforms to census data
showing rise in number of in-
house latrines and drinking
water connections
• Households in notified
slums spend more than
those in non-notified slums
– De Soto vindicated?
• But, notified slums have
richer households
Notified
Slum
Non-
notified
Slum
Squatter
Settlement
Other
areas
10% 850 500 600 1200
25% 2000 2000 2000 3600
50% 7200 5500 5000 15000
75% 32000 25000 15000 50000
90% 150000 70000 50000 175000
7
In notified slums, half the households
spend less than Rs. 7,200 but 10% spend
more than Rs. 150,000 per year
For the top 10%, slum households spend
more per sq. ft. than non-slum households
Distribution of construction
expenditure by type of area

8. Imagining the Indian City: The Chinese Model?

9. If China can do it…

10. Conclusion and Implications

11. Reasons for slum removal do not hold
Untenable
• Slums in “non-tenable” areas are notified
and provided services
– Assumption that these sites cannot be
provided services is invalid
– Services improving over time
• Difficult to defend the argument that the
locations are unfit for human habitation
• Untenability is not a valid reason for slum
removal in many cases
– If notified, regardless of location,
Located in an area classified as
“Others (non-Hazardous/Non-
Objectionable)”, even if not notified
If at least 10% of households in the
slum report having patta, possession
certificateor occupancy rights, even if
it is not notified and not located in an
area classified as “Others (non-
Hazardous/Non-Objectionable)”.
– Only 4.1% are left ‘untenable’
Unproductive
• Slum residents work in similar
industries as non-slum residents,
albeit in different occupations in
the industry
– Integral to city’s productivity
• Both non-notified and notified
slum residents invest in housing
proportionately more than non-
slum residents
• Unproductivity is not a valid
reason for slum removal
– Slums residents are largely
productive investing citizens
11

12. Hippocrates and Beatles
• There is a case for looking
to Hippocrates and Beatles
– Never do harm
– Let it be
• The extent of service
provision in slums is better
than popular perception
and (more importantly) can
be and is being improved
– Slum improvement is an
ongoing (and viable?)
strategy
• Inconsistencies in the
process of notification send
out confusing signals about
what is tenable
– Induces a sense of (false?)
promise and prompts more
self-investment, which can
increase reluctance to
change location later
• Land based financing
ignores the contribution of
existing use of land
12

13. Local / National
• Less policy, more politics
– Local solutions
– Variation in the nature of the
problem
• A smaller city focus on
improvement may have
more bang for the buck
• More tractable scale
• Higher need for better
amenities
– Lower abilityto self-
provide
• Problem: Local does not
control much
– Where does change start?
• New cities
– Governance
• Non-Elected
– Private land and public
goods
• Earmarking by regulation?
• Implications for land
acquisition
– Keeping the settlements out
of the acquisition?
• lal dora, gaothan
– Current Chinese practice
13

14. Going forward…
• What is the slum the solution to and what would
slum-free-ness be the solution to?
• I owe the phrasing of this question to Raka Ray of Berkeley
• Recognize slum ≠ poor ≠ unproductive
– Focusing on slums leaves out much of the poor
– Understanding the slum economy and its linkages
• Livelihood related social protection issues
– Functionality of the city
• What is the nature of housing that is being
demanded?
– Quality
– Rental
14

15. Thank You
partha@cprindia.org
Pillars do not make cities, people do
A construction site is never a tidy place

16. Comparing form in India and China
© theswankytraveler.com

17. Comparing form-1
© Rafiq Maqbool/AP Photo

18. Urban growth under
rural administration is a
national phenomenon
This Census town
phenomenon is not confined
to a few states, though it is
much more in some states
(where administrative
thresholds for becoming
urban are high) than others.
It is not clear what planning
standards to use for them
Only a third of these census
towns are close to a large
(more than 100,000) city – it
is not just a periphery issue
18
India: 32.8%
97%
69%
45%
39%
39%
33%
30%
24%
22%
21%
21%
18%
14%
13%
13%
10%
4%
0% 20% 40% 60% 80% 100%
Kerala
West Bengal
Jharkhand
Orissa
Tamil Nadu
NCT of Delhi
Andhra Pradesh
Punjab
Uttar Pradesh
Rajasthan
Maharashtra
Haryana
Bihar
Gujarat
Karnataka
Madhya Pradesh
Chhattisgarh
Shareof urban growthdueto censustowns
Source: Census of India 2011, 2001
Informal settlements in Indian Cities Coimbatore Sept 2016

19. Gorard’s Index of Segregation
% of Households that need to move across wards for a uniform distribution across wards
Gender
Male
Literacy
SC/ST
In-house
drinking
water
In-house
latrine
Two
wheeler
Delhi 1.0% 9.7% 25.3% 35.9% 47.8% 12.0%
Mumbai 1.6% 7.6% 19.6% 21.4% 17.7% 16.0%
Bangalore 1.1% 8.3% 20.2% 34.5% 35.9% 11.0%
Hyderabad 0.6% 8.7% 22.8% 32.1% 43.1% 8.5%
Ahmedabad 0.8% 7.7% 28.2% 24.2% 35.4% 13.3%
Chennai 0.7% 8.6% 27.7% 27.9% 43.7% 9.9%
Kolkata 2.3% 16.6% 35.0% 24.3% 37.3% 15.5%
Surat 3.4% 6.6% 28.8% 39.0% 37.9% 19.2%
Pune 1.2% 9.4% 25.0% 29.2% 36.5% 8.3%
Jaipur 0.6% 12.7% 25.0% 41.3% 53.1% 10.0%
The level of ‘segregation’ for SC/ST is less than that observed for race in the United States
‘Segregation’ is even higher for amenities like in-house latrines and water

20. The Indian Model…

21. State-led: Ten Inequality Producing Actions in Delhi
• First, DDA builds for the relatively rich
and not for the poor
• Second,people cannot formally develop
land for housing
• Third, courts often do not recognise
rights of residents of JJCs. By one
reading, courts in Delhi have been a
demolition machine
• Fourth, the state uses the law to
constrict employment options, by
relocation of industry
• Fifth,it impedes the progress of even
the few relocated JJC residents by
peripheralising the location and
reducing the plot size in RCs
• Sixth,services remain poor in RCs,
despite being legal and planned
settlements,
• Seventh,in some UACs, the residents
have to depend on an extensive private
piped network; distributing water from
borewells, which is more expensive,
poorer in quality and limited in supply
• Eighth, JJCs in Delhi that are often
demolished to ostensibly build
infrastructure like roads, flyovers and the
Delhi metro rail bear the brunt of the
costs, but the benefits disproportionately
accrue to privileged households
• Ninth, agencies like DJB exclude existing
UACs and JJCs from their network plans,
due to their ‘illegal’ status
• Tenth, transport investment in Delhi is
skewed towards the metro railway, which
accounted for 86% of the plan investment
in sector in 2013-14
21
Source: StateProducedInequalityin an IndianCitySeminarAugust 2015 PATRICK HELLER and PARTHA MUKHOPADHYAY

22. People-led transport: smart?
Bus services uncommon
Paratransit is a common mode
of public transport
Usually licensed by
district authorities
Little organisation
Shared use, per seat fare
instead of per vehicle fare
Usually, detested by
authorities
Does not have to be this way
Kolkata started with
metered auto rickshaws
Soon moved to point to
point service
Organized into point to
point routes by unions
Routes recognised by
transport authorities

23. People-led employment: Work
Similar industriesofemployment…
-20%
-15%
-10%
-5%
0%
5%
10%
15%
20% Million Plus Non Million Mumbai
…but, differentjobs
-20%
-15%
-10%
-5%
0%
5%
10%
15%
20% Million Plus Non Million Mumbai
Source: NSS 65th Round Housing Conditions and Amenities in India 2008-09
Note: Positive difference implies higher proportion employed in slums.

24. 24
Where do urban men work? Formal and Informal
0%
5%
10%
15%
20%
25%
30%
35%
40%
M
iningM
anfufacturing
U
tilitiesC
onstruction
TradeFood
service
Transportand
Com
m
unications
FinancialInterm
ediation
R
ealEsate
G
overnm
ent
Education
H
ealth
O
therC
om
m
unity
Private
H
ouseholds

25. 25
Where do urban women work? Formal and Informal
0%
5%
10%
15%
20%
25%
30%
35%
40%
M
ining
M
anfufacturing
U
tilitiesC
onstruction
TradeFood
service
Transportand
Com
m
unications
FinancialInterm
ediation
R
ealEsateG
overnm
ent
Education
H
ealth
O
therC
om
m
unity
Private
Households

26. People-led: Housing (45 cities of more than 1mn)
One room or no room Two or less rooms
2
13 15
9
6
0
2
4
6
8
10
12
14
No.ofCities
PercentageofHouseholds
In43or45cities,more
thanhalfthehouseholds
liveintwoorlessrooms
3
14
13
10
5
0
2
4
6
8
10
12
14
No.ofCities
Percentageofhouseholds
Informal settlements in Indian Cities Coimbatore Sept 2016
Source: Census of India 2011

27. Putty or Protest…

28. Is this Idealistic?
• Planning and especially, Architecture, are professions
– Is it worth looking at households who will not be clients?
• Responses at a number of levels
– Simplest is to think of public agencies as clients
• Compared even to cities in China, where planning is a relatively
recent discipline, public agencies in India are very small and
poorly staffed – this can change…
– Singapore Housing and Development Board, Shenzhen Urban
Planning and Design Institute
– Economic growth requires this mixture of population
• “Clients” would not exist without this population
– Moral

29. Professional relevance
• Is the profession relevant
for :
– A household in a two-room
house
+ Sharing the house with
another couple
+ Sharing a toilet with another
household
+ In an area that is not planned
+ In which three fourths of the
population lives
• Or for
– A household in a “village”
that has given up farming,
but is relatively far from a
large town
• This is as much an issue of
analysis
– What is driving these forms
of urbanisation
• Within the city?
• In the census towns?
• As design
– Can we do in-situ service
provision (not just demolish
and redevelop on site) of
settlements?
– Can we work with non-
network solutions that build
on individual’s investments?
• How do you deal with rising
investment in septic tanks?

30. So,…
Pieces of Putty
• Can cities be remoulded?
• If so, by whom?
– SPVs
– Chief Ministers
– Municipality
– Or…
• If so, how?
– Planning
– Investment in
infrastructure
– Or…
Places of Protest
• Protesting by Voice
– Estamos presentes
• The right to stay put in
Mumbai
• Protesting by Action
– By building
• Unauthorised colonies
in Delhi
– By providing services
• Paratransit in Kolkata
– By working

31. partha@cprindia.org
A construction site is never a tidy place

32. Does “Chindia” matter/ make
sense?
To keep the planet warming more
than 2 degrees, we have a budget of
roughly 3700 bn. tons of CO2
emissions. We have spent 2200 bn.
Currently, the world is emitting 35 bn.
tons a year – which means we exhaust
our budget around 2060…
85% of China’s emissions and 55% of
India’s emissions are from cities
Numbers may hide as much as they
reveal. Consumption and population
(China)
0
5
10
15
20
25
CO2 emissions per capita
May not be as high
May not be as low

33. Measuring differences
5.05
3.30
2.44 2.32
1.50
1.98
0.00
1.00
2.00
3.00
4.00
5.00
6.00
GDP at market
prices (current
$)
GDP at market
prices
(constant $)
GDP, PPP
(constant 2011
international
$)
GDP per
capita, PPP
(constant 2011
international
$)
GDP per
worker, PPP
(constant 2011
international
$)
Shanghai to
Mumbai GDP
(current PPP $)

34. ‘Reasons’ for Slum Removal
Untenable
• Slums are on land unfit for
human habitation
– Hazard for slum dwellers and
public health
• Implicit assumption that site
cannot be provided services
• Q. Is this true and what is
happening on the ground?
Unproductive
• Land is needed for more
productive use
– Implicit assumption of slum use
being low/ zero productivity
• Use of land after slum
removal
• Q. Who lives in slums and are
they productive?
34

35. Plan of Presentation
• Definitions and Data Sources
– Comparability of different sources
• Tenability
– Where are the slums?
• Location
– Amenities in slums
• Do services differ by tenability/ notification?
• Productivity
– Who are the people living in slums?
– What do they do?
• Occupation
– How do they view their future?
• Investment in housing
• How well do the reasons for removal hold?
35

36. Definitions and Data Sources
• Slum: A slum is a compact area …with a collection of poorly built
tenements, mostly of temporary nature, crowded together usually with
inadequate sanitary and drinking water facilities in unhygienic
conditions... Such an area will be considered as a slum if at least 20
households live in that area for the purpose of this survey. Certain areas
notified as slums by the respective municipalities, corporations, local
bodies or development authorities will be treated as ‘notified slums’.
Slum will be considered in urban areas only. An area having at least 20
households of notified slum …will always be considered as a slum.
• Squatter settlement: Sometimes an area develops into an unauthorised
settlement with unauthorised structures put up by “squatters”. Squatter
settlement will include all slum like settlements which do not have the
stipulated number of 20 households to be classified as a slum
36

37. Slum Households: Diverse ‘Truths’
37
Census
2001
NSS 58th Round 2001-02 NSS 65th Round 2008-09
Characteristics
of Slums
Housing
Conditions
Characteristics
of Slums
Housing
Conditions
Andhra Pradesh 13,24,762 11,29,374 12,06,112 14,98,298 9,24,898
Bihar 1,31,099 69,363 61,559 25,367 47,424
Chhattisgarh 2,15,685 1,09,902 79,459 59,059 94,005
Gujarat 3,86,318 1,57,863 1,57,485 3,00,168 3,00,553
Haryana 3,23,020 .. 25,169 10,710 20,595
Karnataka 4,52,114 4,83,828 2,12,962 4,09,377 3,06,629
Madhya Pradesh 6,74,143 3,08,138 3,80,464 2,62,646 2,95,745
Maharashtra 23,75,963 31,82,576 22,30,211 29,11,170 23,19,531
Orissa 2,26,408 18,208 22,849 1,69,349 1,78,222
Punjab 2,74,570 8,962 7,826 4,351 7,633
Rajasthan 2,74,427 56,860 60,837 36,654 49,605
Tamil Nadu 9,66,162 6,19,618 3,31,700 7,24,613 4,14,848
Uttar Pradesh 8,88,267 2,27,799 2,18,660 2,16,279 3,28,692
West Bengal 9,15,380 15,30,920 4,43,658 4,42,626 4,37,210
Delhi 4,15,637 2,12,299 2,12,741 24,49,998 4,93,994
Chandigarh 29,086 12,848 5,34,803 16,203
Others 2,77,678 1,14,034 1,45,493 1,04,358 1,12,012
Total 1,01,50,719 82,29,744 58,10,033 1,01,59,825 63,47,799

38. Data Used in Analysis
• Different sources can provide wide variation
– Some estimates are patently absurd
• Delhi, Chandigarh
• Analysis uses
– Characteristics of Slum data to investigate issues of
tenability and relationship to service provision
– Housing condition data for household level analysis and
comparison of slum with rest of city
– Three broad categories
• Million plus cities
• Other cities
• Specific cities
38

39. Tenability
Where are the Slums
and
What is their status?

40. Which Cities?

41. Bigger Cities have a higher proportion living in
Slums, but…
41
Notified
Slums
Non-
Notified
Slums
Total Slums Squatter Other Areas
All India 5% 4% 10% 1% 89%
Non Million 3% 4% 7% 1% 92%
Million Plus 10% 7% 17% 1% 83%
Mumbai 24% 19% 43% 0% 57%
Delhi 8% 11% 20% 1% 80%
Kolkata 15% 6% 21% 0% 79%
Pune 11% 2% 13% 0% 87%
Hyderabad 6% 6% 12% 0% 92%
Bangalore 2% 5% 7% 0% 93%
Chennai 7% 0% 7% 0% 93%
Ahmedabad 0% 1% 1% 0% 99%
Data Source: NSS 65th Round Housing Conditions and Amenities in India 2008-09

42. Smaller Towns account for a higher share of Slum
Dwellers
42
Notified
Slums
Non-
Notified
Slums
Total Slums Squatter Other Areas
All India 100% 100% 100% 100% 100%
Non Million 50% 61% 55% 83% 76%
Million Plus 50% 39% 45% 17% 24%
Mumbai 20% 18% 19% 0% 3%
Delhi 6% 10% 8% 2% 3%
Kolkata 5% 2% 4% 0% 1%
Pune 4% 1% 3% 0% 2%
Hyderabad 2% 2% 2% 0% 2%
Bangalore 1% 3% 2% 0% 3%
Chennai 2% 0% 1% 0% 2%
Ahmedabad 0% 0% 0% 0% 1%
Data Source: NSS 65th Round Housing Conditions and Amenities in India 2008-09

43. Where in the Cities?

44. ‘Whose’ lands do what slums occupy?
44
2008-09 2002
Tenable Non-Tenable Tenable Non-Tenable
Notified
Non
Notified Notified
Non
Notified Notified
Non
Notified Notified
Non
Notified
Private 43% 51% 29% 31% 41% 40% 25% 27%
Public
(local)
44% 31% 50% 39% 40% 37% 51% 40%
Public
(non-local)
0% 0% 7% 12% 1% 4% 8% 19%
Others 13% 18% 13% 18% 17% 19% 16% 14%
Total 100% 100% 100% 100% 100% 100% 100% 100%
Data Source: NSS 65th Round Characteristics of Slums 2008-09 and NSS 58h Round Characteristics of Slums 2002

45. Location: Dharavi
45
• The location of Dharavi is integral to the intensity of efforts to ‘redevelop’ the
area.
BKC

46. Non-Tenability ≠ Non-Notification
46
8%
16%
9%
8%
13%
14% 14%
18%
0%
5%
10%
15%
20%
Non
Tenable
Tenable Non
Tenable
Tenable Non
Tenable
Tenable Non
Tenable
Tenable
Notified Non Notified Notified Non Notified
Million Non million
ShareofSlumsinIndia
Data Source: NSS 65th Round Characteristics of Slums 2008-09

47. Non-Tenability ≠ Lack of Services
47
0%
10%
20%
30%
40%
50%
60%
70%
Public None Public None Public None Public None
Non Tenable Tenable Non Tenable Tenable
Million Non million
Latrines 2002
2009
0%
4%
8%
12%
16%
20%
Non Tenable Tenable Non Tenable Tenable
Million Non Million
Street Lights
2002
2009
0%
20%
40%
60%
80%
Non Tenable Tenable Non Tenable Tenable
Million Non Million
Covered Drainage
2002
2009
0%
20%
40%
60%
80%
100%
Non Tenable Tenable Non Tenable Tenable
Million Non Million
Garbage Collection by ULBs
2002
2009
Data Source: NSS 65th Round Characteristics of Slums 2008-09 and NSS 58h Round Characteristics of Slums 2002
47

48. & Non-Notification ≠ Lack of Services
48
0%
4%
8%
12%
16%
20%
Notified Non Notified Notified Non Notified
Million Non Million
Street Light
2002
2009
0%
10%
20%
30%
40%
50%
60%
70%
80%
Public None Public None Public None Public None
Notified Non Notified Notified Non Notified
Million Non million
Latrines
2002
2009
0%
20%
40%
60%
80%
Notified Non Notified Notified Non Notified
Million Non Million
Covered Drainage
2002
2009
0%
20%
40%
60%
80%
100%
Notified Non Notified Notified Non Notified
Million Non Million
Garbage Collection by ULBs
2002
2009
Data Source: NSS 65th Round Characteristics of Slums 2008-09 and NSS 58h Round Characteristics of Slums 2002

49. Non-Notification ≠ Lack of Services
49
Million Plus cities Non Million Cities Mumbai
2001-02
Notified
Slums
Non-
Notified
Slums
Other
Areas
Notified
Slums
Non-
Notified
Slums
Other
Areas
Notified
Slums
Non-
Notified
Slums
Other
Areas
Latrine
Exclusive use 16% 9% 64% 27% 19% 55% 2% 2% 60%
Shared 15% 13% 25% 14% 6% 19% 7% 9% 26%
Community latrine 55% 53% 5% 18% 12% 5% 91% 83% 13%
No latrine 13% 24% 5% 41% 62% 20% 0% 6% 2%
Drinking Water
Exclusive use 24% 18% 58% 14% 8% 43% 33% 34% 86%
Building common use 26% 11% 24% 17% 8% 27% 38% 20% 11%
Community 51% 71% 17% 69% 84% 30% 29% 46% 3%
Drainage
Underground 26% 13% 65% 5% 1% 20% 6% 11% 74%
Covered pucca 20% 7% 10% 5% 3% 14% 37% 14% 13%
Open pucca 35% 34% 16% 45% 24% 36% 49% 43% 11%
Open kutcha 5% 22% 3% 16% 11% 10% 6% 24% 0%
No drainage 14% 24% 6% 29% 60% 21% 2% 8% 2%
Garbage
Local body 84% 67% 71% 63% 26% 54% 99% 97% 98%
Residents 4% 13% 19% 9% 19% 18% 0% 0% 0%
No arrangement 11% 20% 8% 27% 53% 23% 1% 3% 0%
Others 0% 0% 2% 1% 2% 5% 0% 0% 1%
Data Source: NSS 58th Round Housing Conditions and Amenities in India 2002

50. Non-Notification ≠ Lack of Services
50
Million Plus cities Non Million Cities Mumbai
2008-09
Notified
Slums
Non-
Notified
Slums
Other
Areas
Notified
Slums
Non-
Notified
Slums
Other
Areas
Notified
Slums
Non-
Notified
Slums
Other
Areas
Latrine
Exclusive use 24% 14% 66% 37% 28% 60% 1% 11% 58%
Shared 23% 14% 28% 23% 16% 24% 9% 5% 28%
Community latrine 50% 63% 4% 12% 23% 3% 89% 81% 14%
No latrine 4% 9% 2% 29% 33% 13% 0% 3% 0%
Drinking Water
Exclusive use 37% 24% 59% 26% 17% 46% 41% 29% 80%
Building common use 24% 18% 27% 18% 15% 25% 21% 28% 13%
Community 33% 55% 10% 52% 63% 23% 30% 41% 5%
Others 6% 3% 4% 5% 5% 6% 8% 3% 2%
Drainage
Underground 46% 17% 73% 11% 9% 26% 14% 19% 84%
Covered pucca 26% 26% 12% 13% 8% 15% 52% 40% 12%
Open pucca 20% 29% 13% 44% 32% 34% 29% 36% 3%
Open kutcha 3% 14% 1% 8% 10% 7% 0% 3% 0%
No drainage 5% 14% 2% 24% 41% 18% 5% 3% 0%
Garbage
Local body 84% 76% 77% 61% 43% 57% 92% 86% 98%
Residents 3% 6% 14% 15% 18% 13% 0% 1% 1%
No arrangement 9% 16% 7% 24% 38% 26% 8% 13% 0%
Others 4% 2% 3% 0% 1% 4% 0% 0% 0%
Data Source: NSS 65th Round Housing Conditions and Amenities in India 2008-09

51. Productivity

52. Consumption

53. Who lives in slums?
Many poor, but also quite a few rich
53
National
Urban
Decile
Million Plus cities Non Million Cities Mumbai
Notified
Slums
Non-
Notified
Slums
Other
Areas
Notified
Slums
Non-
Notified
Slums
Other
Areas
Notified
Slums
Non-
Notified
Slums
Other
Areas
1 15% 16% 69% 6% 7% 87% 33% 63% 4%
2 18% 17% 66% 5% 8% 87% 68% 14% 18%
3 18% 13% 69% 5% 5% 89% 55% 25% 21%
4 16% 9% 74% 5% 5% 90% 28% 24% 48%
5 14% 7% 79% 4% 4% 93% 47% 24% 29%
6 13% 8% 79% 3% 3% 93% 29% 41% 31%
7 13% 7% 80% 3% 3% 95% 41% 29% 30%
8 11% 8% 81% 2% 2% 95% 33% 24% 43%
9 8% 5% 87% 1% 1% 97% 21% 20% 59%
10 2% 2% 96% 1% 0% 99% 6% 4% 89%
Total 10% 7% 83% 4% 4% 93% 24% 19% 57%
Data Source: NSS 65th Round Housing Conditions and Amenities in India 2008-09

54. Big Cities are different but
Mumbai is truly Maximum
54
96
82 80
53
71 69 70
57
41
11
60
32
16 15 12 12 9 8 6 5 3 2
0
10
20
30
40
50
60
70
80
90
100
1 2 3 4 5 6 7 8 9 10
Percentage
National Urban Decile
Bombay Delhi
Kolkata Million
Non million
Data Source: NSS 65th Round Housing Conditions and Amenities in India 2008-09
Share of Slum-Dwellers by Consumption Class

55. Employment

56. Where does their income come from?
56
All Deciles BottomThree Deciles TopThree Deciles
Million Plus Non Million Million Plus Non Million Million Plus Non Million
Slums
Other
Areas
Slums
Other
Areas
Slums
Other
Areas
Slums
Other
Areas
Slums
Other
Areas
Slums
Other
Areas
Primary 1% 1% 11% 9% 0% 2% 12% 15% 0% 1% 8% 4%
Food manufacture 1% 2% 3% 3% 1% 1% 4% 4% 2% 1% 1% 2%
Clothing & footwear 12% 8% 11% 6% 6% 11% 9% 6% 21% 6% 14% 5%
Machinery
manufacture
3% 5% 1% 3% 1% 2% 1% 1% 3% 5% 3% 4%
Other manufacture 11% 10% 8% 8% 5% 9% 10% 8% 12% 10% 7% 8%
Public Utilities 0% 1% 1% 1% 1% 1% 1% 0% 1% 1% 1% 2%
Construction 13% 7% 19% 11% 22% 11% 23% 17% 6% 4% 9% 5%
Govt. Services 5% 8% 5% 8% 8% 3% 2% 3% 4% 11% 14% 15%
Traditional Services 41% 37% 34% 35% 49% 50% 35% 39% 34% 31% 27% 29%
Modern Services 6% 15% 4% 7% 3% 3% 2% 3% 9% 22% 8% 13%
Social Services 3% 5% 3% 7% 1% 5% 2% 3% 5% 6% 7% 13%
Household Services 3% 1% 1% 1% 5% 3% 1% 1% 3% 1% 2% 0%
Data Source: NSS 65th Round Housing Conditions and Amenities in India 2008-09

57. What kind of jobs do they do?
57
All Deciles BottomThree Deciles TopThree Deciles
Million Plus Non Million Million Plus Non Million Million Plus Non Million
Slums
Other
Areas
Slums
Other
Areas
Slums
Other
Areas
Slums
Other
Areas
Slums
Other
Areas
Slums
Other
Areas
Managers 4% 18% 6% 13% 4% 12% 6% 7% 3% 23% 9% 18%
Professionals 9% 13% 4% 11% 6% 5% 2% 4% 14% 19% 9% 21%
Technicians 2% 8% 3% 6% 0% 2% 1% 2% 5% 11% 10% 11%
Clerks 5% 7% 2% 6% 1% 1% 1% 2% 6% 10% 5% 10%
Service and sales 17% 13% 12% 15% 14% 15% 10% 15% 17% 12% 13% 14%
Craft and trades 22% 17% 27% 18% 13% 23% 28% 23% 30% 12% 23% 11%
Machine operators 13% 10% 10% 8% 10% 13% 6% 8% 10% 7% 14% 6%
Elementary
Occupations
27% 12% 32% 18% 52% 28% 41% 32% 14% 5% 15% 6%
Others 1% 1% 4% 5% 0% 1% 5% 7% 0% 1% 2% 3%
Data Source: NSS 65th Round Housing Conditions and Amenities in India 2008-09

58. Housing Investment

59. Slum houses are small
(even for rich slum residents in big cities)
59
0
100
200
300
400
500
600
1 2 3 4 5 6 7 8 9 10
Notified
Non-notified
Squatter
Other
0
100
200
300
400
500
600
1 2 3 4 5 6 7 8 9 10
Notified Slums
Million
Other
0
100
200
300
400
500
600
1 2 3 4 5 6 7 8 9 10
Non notified Slums
Million
Other
0
100
200
300
400
500
600
1 2 3 4 5 6 7 8 9 10
Other areas
Million
Other
Data Source: NSS 65th Round Housing Conditions and Amenities in India 2008-09

60. Proportionately more Slum Residents undertake new
construction
60
Million Plus cities Non Million Cities
Notified
Slums
Non-
Notified
Slums
Other
Areas
Total
Notified
Slums
Non-
Notified
Slums
Other
Areas
Total
1 19% 4% 3% 6% 5% 6% 6% 6%
2 7% 10% 2% 5% 4% 6% 4% 5%
3 6% 4% 4% 5% 13% 5% 5% 5%
4 6% 15% 4% 5% 5% 1% 7% 7%
5 3% 5% 2% 3% 4% 7% 4% 4%
6 2% 6% 3% 3% 4% 4% 5% 5%
7 6% 11% 4% 5% 7% 2% 4% 4%
8 5% 16% 3% 4% 3% 4% 4% 4%
9 8% 4% 2% 3% 8% 1% 4% 4%
10 6% 3% 2% 2% 8% 4% 3% 3%
6% 8% 5% 3% 6% 4% 5% 5%
Data Source: NSS 65th Round Housing Conditions and Amenities in India 2008-09
Percent of Households undertaking new construction by consumption decile

61. …and they spend a fair bit too
61
05.000e-06.00001.000015
Density
0 500000 1000000 1500000 2000000 2500000
Total Cost of 1st constr. in last 1 yr.(Rs.)
kernel = epanechnikov, bandwidth = 1598.82
Kernel density estimate
0.00002.00004.00006.00008
Density
0 50000 100000 150000 200000 250000
Total Cost of 1st constr. in last 1 yr.(Rs.)
kernel = epanechnikov, bandwidth = 840.67
Kernel density estimate0.00001.00002.00003.00004
Density
0 200000 400000 600000 800000
Total Cost of 1st constr. in last 1 yr.(Rs.)
kernel = epanechnikov, bandwidth = 1370.34
Kernel density estimate
0.00001.00002.00003.00004
Density
0 100000 200000 300000 400000 500000
Total Cost of 1st constr. in last 1 yr.(Rs.)
kernel = epanechnikov, bandwidth = 1243.57
Kernel density estimateNotified Slums
Non-notified Slums
Squatter Settlements
Other Areas
Data Source: NSS 65th Round Housing Conditions and Amenities in India 2008-09

62. How can 5% of slum
households be ‘managers’?
in million
Share of
Owners
Managers 12.3 7.9 64%
Professionals 9.3 3.5 38%
Technicians 6.5 1.0 16%
Clerks 5.3 0.1 2%
Service and sales 14.0 4.6 33%
Craft and trades 4.0 0.6 15%
Machine operators 17.9 4.5 25%
Elementary Occupations 7.4 1.7 23%
Managers 17.7 2.8 16%
X 0.1 0.0 21%
Total 94.4 26.7 28%
From the NSS 66th Round
‘Employment & Unemployment
Survey’ (EUS) in 2009-10, we find a
large majority of senior officials/
managers are ‘Owners’ Their share
is 64%
Owners are defined as those
working in partnerships or
proprietorship and self-employed.
Note: EUS is individual level data
and cannot be separated by those
living in slums and non slums.
62

63. Where is the Indian City?
Working Group I: SessionII
Integrated Planning, Management and Governance Structure Imperatives

64. Where?
Urban India is more about morphing places, than about moving people
64
24.3% 25.3%
8.2%
25.6%
6.7% 2.6%
6.4%
0.9%
25.6%
34.1%
7.4%
32.9%
0%
5%
10%
15%
20%
25%
30%
35%
40%
Million Plus
Towns
1L - 10L
Towns
Census
Towns
Other
Urban Areas
ShareofUrbanPopulationby TypeofUrban Area
2001 2011_New 2011_Old
Census towns are functionally urban (share of non-farm work more than 75%) and large
(more than 5000 people) villages, that continue to be administered by rural authorities.
The new scheme, SP Mukherji RURBAN Mission, in the Ministry of Rural Development
Source: Census of India 2011, 2001

65. The spread of majority Non-farm
(50%+) Villages over time
Villages with ‘better sanitation’
than smaller towns in the state

66. What drives urban
population growth?
The growth of urban population can
be decomposed into natural
population growth in existing urban
areas, boundary expansion,
changes in classification from rural
to urban (for both statutory and
‘censustowns’ ) and net migration.
The chart shows that the share of
change in classification (35%) – see
census towns in previous slide – is
more than net migration (23%),
though gross rural urban flows
(36%) are comparable.
Over 1999-2001, natural population
growth in existing urban areas
accounted for 69%, compared to
42% over 2001-11
20.6
38.5
31.8
-11.5
-15 0 15 30 45 60 75 90
Components of Urban Population Growth (mn.)
Net Rural Urban Migration Natural Growth and expansion
Change in Classification Urban Rural Migration
32.1 TotalRuralUrbanMigration

67. Is this growth serviced?
Piped Sewerage
46%
43%
93%
79%
82%
40%
8%
25%
22%
27%
5%
2% 5%
9%
3%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Core District MR Urban (Non-Core) MR Rural
Treated Tap Water
78%
67%
64% 65%
88%
77%
30%
26%
18%
47%
22%
2%
15%
12%
15%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Core District MR Urban (Non-Core) MR Rural

68. Thank You
partha@cprindia.org
Pillars do not make cities, people do
A construction site is never a tidy place