labor force in informal activity. The developing country context also requires that we capture informal sector housing – slums – which we do with the distinction between modern and traditional sectors. They use different building technologies, one expensive and the other cheaper and delivering lower amenity value per unit land area.

The literature on quantitative spatial models has grown substantially in recent years, as summarized in the Redding and Rossi-Hansberg 2017. Most of this work has focused on developed countries, including in Berlin where Ahlfeldt et al. 2015 use the shock of the Berlin wall to examine the impacts of connectivity within a city on urban structure and production. Monte et al. 2015 use a related approach to quantify the benefits from a reduction in commuting costs across cities in the United States. Papers focused on developing countries are more limited however, mainly as a result of data limitations. The model in this paper develops a model set out in Bird and Venables (2019) on Kampala, Uganda, which uses a CGE approach to analyzing the impact of land tenure on the city, and considering the potential welfare impacts of land reform.

Our core results take a benchmark data set of Dhaka in 2035. This data set is based on detailed spatial data for the period 2010-2011 (Li et al. 2016), combined with projections (supplied by the World Bank) of aggregate variables to 2035, knowledge of planned transport improvements, and supplemented by using the model to fill in projections of disaggregate detail. Some economic activity currently exists in East Dhaka, and this is projected to increase over time due to private infilling of land to create low-quality but developable areas. We refer to this as scenario A, or Business as Usual. Given this benchmark we then simulate the effect of increasing the quantity and quality of available land in East Dhaka following the construction of an embankment and related flood protection measures (Bird et al. 2018). The assumed changes are: Scenario B: Reduction in the share of land that floods according to estimates from the Institute of Water Modelling (IWM) (Zaman 2014). This increases the total amount of land developable in East Dhaka by over 50%, from 66km<sup>2</sup> to 102 km<sup>2</sup> . We assume that the quality of developable land in East Dhaka rises, as it is no longer infilled land but instead is land protected from flooding by the presence of the embankment. The quality is then assumed to match the median levels of land productivity for firms and amenity for households of Central Dhaka. Scenario C: We modify the transport network to include proposed investments in road and Mass Rapid Transit (MRT) infrastructure, targeted at East Dhaka (Bird et al. 2018). Scenario D: we reduce the costs of doing business for tradable-services firms in East Dhaka, to encourage the formation of new clusters in this area, while boosting further the amenities provided for residents.

We analyze scenario B, our core policy experiment, under a series of increasingly less restrictive assumptions about what changes in the city. Initially we suppose that the structure and location of productive and residential activity changes, but the overall city population remains constant at its 2035 projected level. In East Dhaka the residential population rises nearly threefold, attracted by the increased land availability and the lower risk of flooding, increasing the population density from 14,560 to 40,070 people per km<sup>2</sup> , closer to levels seen in Central Dhaka where the base population density is 64,960 people per km<sup>2</sup> . There is little 3