Finally, tables 1 and 2 present summary statistics for two estimated elasticities – the elasticity of _overall_ area with respect to population across different types of urban area and the elasticity of _built-up_ area with respect to population across different types of urban area, where a settlement’s built-up area may be less than its overall area due to open spaces. For the overall area elasticities, these are estimated to be less than 1 for most countries for all types of urban area. This implies that a doubling of an urban area’s population is associated with a less than doubling of its overall area, hence a higher density. However, for the built-up area elasticities, these are estimated to be larger than 1 for a large majority of countries for all types of urban area. Indeed, the median (mean) estimated elasticity of built-up area with respect to population is 1.22 (1.23) for all urban areas and 1.21 (1.27) for cities. Hence, for the median country, a doubling of an urban area or city’s population is associated with a 121-122 percent increase in its built-up area. The finding of estimated built-up area elasticities that exceed 1 is in marked contrast with results for developed countries and cities globally. Ahfledt and Pietrostefani (2019) estimate an elasticity of approximately 0.60 for a large global sample of cities, while de Bellefon et al. (2021) estimate an elasticity of 0.84 for all French urban areas, as defined using the dartboard algorithm, with a population greater than 100 and 0.89 for the 500 largest French urban areas.

One possible explanation for the difference in our estimated built-up area elasticities for SSA countries and those from the literature for developed countries is related to possible differences in the costs of vertical construction, and the ability of households and firms to cover those costs, in SSA versus developed countries.<sup>22</sup> It has been argued by, for instance, Lall et al. (2021) and Mukim and Roberts (2023), that dysfunctional land markets and, in some cases, misguided planning restrictions – for example, excessively stringent building height restrictions and floor area ratios – inflate the costs of vertical development in developing country cities. At the same time, because productivity and hence income levels are much lower in developing country cities, households and firms are less able to cover the costs of vertical construction (i.e., the development of mid- and high-rise buildings), which is much more capital intensive than low-rise construction that leads to more horizontal development of an urban area. For these reasons, Lall et al. (2021) describe cities in SSA and many other developing countries as expanding like “pancakes” rather than developing as “pyramids”, in which case horizontal expansion of a city is accompanied by vertical layering.

An alternative, not necessarily mutually exclusive, explanation for the difference in our estimated elasticities for SSA countries (greater than 1) vis-à-vis the estimates (less than 1) for developed countries relates to the potential composition of built-up area. Hence, built-up area includes not only residential builtup area, but also built-up area associated with industrial and commercial uses. If industry is more intensive in its use of land than housing and more populous cities in SSA countries dedicate a relatively larger share of their land to industrial than to residential uses, this could help explain the high estimated elasticities for these countries. This is especially the case if such compositional changes in built-up area across urban areas of different size are less evident in developed countries, as we might expect given both their more serviceoriented economies and the tendency of manufacturing to gravitate towards smaller cities, where land tends to be cheaper, in these countries (World Bank 2009).<sup>23</sup>

# **3.2.** **_Spatial concentration across urban areas_**

Having described aggregate differences in basic urbanization characteristics across countries, we now turn to the description of urban _area_ characteristics and the spatial concentration of population across urban areas. This includes a focus on characteristics of the size-distributions of urban areas, as captured both by estimated Zipf’s coefficients and the share of a country’s population that lives in its largest urban area, which is a measure of urban primacy.

> 22 This includes both the absolute costs of vertical construction and the costs relative to the price of land. In the case of illegal squatter development, the price of land to the household occupying it is zero.

> 23 The fact that estimated elasticities of overall area with respect to population tend to be less than 1 for most SSA countries while estimated elasticities of built-up area tend to be more than 1 suggests that larger SSA cities tend to have more in-fill development.

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