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Hippocrates and the Beatles Lessons for Informal Settlements

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Working Group II: Session III: Hippocrates and the Beatles Lessons for Informal Settlements (Partha Mukhopadhyay, Center for Policy Research), 14-16 December 2016, India, 6th Asian Pacific Ministerial Conference on Housing and Urban Development

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Hippocrates and the Beatles Lessons for Informal Settlements

  1. 1. Working Group II: Session III Hippocrates and the Beatles Lessons for Informal Settlements Partha Mukhopadhyay Centre for Policy Research
  2. 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. 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. 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. 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. 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. 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. 8. Imagining the Indian City: The Chinese Model?
  9. 9. If China can do it…
  10. 10. Conclusion and Implications
  11. 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. 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. 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. 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. 15. Thank You partha@cprindia.org Pillars do not make cities, people do A construction site is never a tidy place
  16. 16. Comparing form in India and China © theswankytraveler.com
  17. 17. Comparing form-1 © Rafiq Maqbool/AP Photo
  18. 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. 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. 20. The Indian Model…
  21. 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. 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. 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. 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. 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. 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. 27. Putty or Protest…
  28. 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. 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. 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. 31. partha@cprindia.org A construction site is never a tidy place
  32. 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. 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. 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. 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. 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. 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. 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. 39. Tenability Where are the Slums and What is their status?
  40. 40. Which Cities?
  41. 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. 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. 43. Where in the Cities?
  44. 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. 45. Location: Dharavi 45 • The location of Dharavi is integral to the intensity of efforts to ‘redevelop’ the area. BKC
  46. 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. 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. 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. 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. 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. 51. Productivity
  52. 52. Consumption
  53. 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. 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. 55. Employment
  56. 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. 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. 58. Housing Investment
  59. 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. 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. 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. 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. 63. Where is the Indian City? Working Group I: SessionII Integrated Planning, Management and Governance Structure Imperatives
  64. 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. 65. The spread of majority Non-farm (50%+) Villages over time Villages with ‘better sanitation’ than smaller towns in the state
  66. 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. 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. 68. Thank You partha@cprindia.org Pillars do not make cities, people do A construction site is never a tidy place

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