To examine how urban forms evolve across stages of development, we examine built-up area growth across income groups.

As a final robustness check, we run the same regression as in Table 4 using population, income and builtup from the Functional Urban Area (FUA) database developed by the OECD and the European Commission. The spatial entities represent the commuting areas of the urban centres in 2015, which are geographically larger than our urban extents as they often contain multiple urban centers. Annex 2 presents a similar table as in Table 4. The new coefficients are similar to the ones estimated using our urban centers.

Table 5 reports the results of the between and within estimator following equation (1) for cities per country income group as defined by the World Bank. The coefficients of each column can be interpreted as the income and population elasticities of built-up surface for cities in each income group.

Growing population is associated with a larger increase in built-up surface in poorer countries. As population doubles, cities’ built-up increases by 34% in low-income countries, 31% in lower-middle income countries, 25% in upper-middle-income countries and by 28% in high-income countries.<sup>7</sup> Cities in poorer countries grow more horizontally than cities in richer countries. In contrast, rising incomes are associated with slower built-up surface expansion in poorer countries than in richer ones. As urban population doubles, the city’s built-up area increases by 5 percent in low-income countries, 9 percent in lower-middle-income countries, 11 percent in upper-middle-income countries, and 10 percent in highincome countries. The significant jump in the income elasticities between low-income and middle-income countries is indicative that the evolution of urban form follows broader stages and processes of economic development.

Next, we examine the extent to which rising incomes and stages of economic development influence the shares of extensive margin and infill development. We build a panel of two periods of built-up growth: 1990-2000 and 2000-2015. We estimate the share of infill as : 1 2 (2) where denotes the share of infill built in the period between two years of our data (1990-2000 ln IIPPooeep cc,tt = αα+ ββ ln IIPPeecc,tt + ββ ln FFooppcc,tt + λλtt + γγcc + εεcc,tt 1 2 (2) where denotes the share of infill built in the period between two years of our data (1990-2000 and 2000-2015). cc,tt IIPPooeep Consistent with the stylized facts shown in Figure 5, the share of infill has reduced over time. Also consistent with the stylized facts, the share of infill increases with economic development. Within broad income groups, there is no association between income changes and infill in low-income countries. The positive relationship is strong and statistically significant for middle-incomes countries. We see a negative association between incomes and infill in high-income countries, presumably driven by the United States.

**Table 6: Determinants of infill development**

|**Dependent variable:**|**All**||**Lower**|**Upper**||
|---|---|---|---|---|---|
|**share of infill construction in total**|<br>**ti**|**Low income**|**middle**|**middle**|**High income**|
|**built-up area**|**counres**||**income**|**income**||

> 7 There is no contradiction in the fact that the estimated coefficients per income group are all lower than the estimated coefficient when including all cities.

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