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foot, then the minimum household income level to afford construction costs alone is about INR 2100 and using the residual cost of land based on the market assessment data for Ahmedabad (see figure 10) this figure increases to 2500 per month<sup>13</sup> . This figure is roughly 90% of the All India urban poverty line (Himanshu:2009). For Ahmedabad, our income distribution data suggest this target population would amount to about 10% of the total. Performing a similar calculation for Mumbai, based on derived cost of land for Dharavi<sup>14</sup> , the required income per month is roughly 10 times the figure for Ahmedabad, or about INR 26,000. Although incomes in Mumbai are higher than in Ahmedabad, nonetheless 80% of the population is below this required income level. This simple exercise shows the dramatic difference that real estate market conditions can make for the size of even a minimalist slum program<sup>15</sup> . They also show that without supply side and regulatory measures in many cities, addressing basic needs can rapidly become an unmanageable problem.

Now we turn to a rough characterization of the housing market equilibrium using the income distribution and housing price indications developed above. Figure 12 illustrates the housing market equilibrium in Mumbai. Using house price indications, affordability estimates based on the income distribution data, and estimates of the stock of various types of housing in our typology, this figure shows how different income classes are distributed into various types of accommodation in Mumbai. Much of the middle class and all of the poor are forced into substandard housing because of the high price of land and the highly inadequate supply of housing. Most households are living in slums and chawls<sup>16</sup> . The number of such dwelling units can only grow through subdivision of the existing floor space or densification by adding additional floors. This illustrates the difficulties created by freezing so much of the housing stock for redevelopment through reservations or rent controls. (See box 1 above) Most of the scope for

> 13 Residual land value is calculated by taking market price per square foot of housing space, subtracting cost of construction, then calculating land value using the assumption that land area would 16% more than the surface area. These calculations are illustrative only and would have to be redone based on field surveys in the city. We also assume that a household could afford a home 2.4 times its income. Again, such figures should be validated with field measurements when actually used for establishing the program in a city.

> 14 Dharavi is well located , but is still one of the cheapest housing solutions per sq foot. Figures 8-9 illustrate that it is necessary to move more than 50km from the city centre to achieve such a low price. It is quite unrealistic to expect that many poor households will accept to stay at these long distances from their work—even if they are provided with a home there.

> 15 These calculations should not be interpreted as a costing of a minimalist program of housing improvement. Such a costing would need to include, among others,  infrastructure upgrading, both tertiary improvements for individual households and secondary and primary network upgrades to ensure the capacity of the system can handle the expansion of new connections.

> 16 Chawls are low standard housing once provided to factory workers by their employers. They do not meet current standards for formal housing.

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