This method gives us clues as to which specific elements, such as geological conditions or access to technology, impact the growth of each region’s skyline. We performed a stepwise regression analysis, beginning with two basic controls – population and income – and then adding more supply- and demand-related variables to see how the ‘controlling for’ nature of the regressions alters the residuals. A positive average means that a region tends to build more than the urban model would predict, while a negative average means the region ‘underbuilds’ relative to its economic fundamentals.įigure 2 shows the rankings based on the residuals. To this end, we reviewed the rankings based on average residuals within each region. Our aim is to identify regions that grow taller than expected given their economic and demographic conditions. More precisely, we used the 19 United Nations subregions (UN 2022), each of which we call simply a ‘region.’ To simplify the analysis, we performed regional comparisons, grouping countries by geographic areas with similar income levels and/or cultures. We thus delve deeper into the nature of the regression residuals to better understand the patterns of global tall-building construction. For example, even in our most comprehensive specification, the explanatory power (as measured by R2) is still only about 64%. Our regression results show that though income, population, and supply conditions explain a large fraction of the global variation in heights, considerable differences remain. Urban economic theory holds that a country’s or city’s heights should be positively related to its income and population, but negatively related to geographic and environmental features that increase costs, such as earthquake risk and poor geological conditions for anchoring building foundations. Guided by predictions from the standard land-use model in urban economics (Brueckner 1986), we perform country-level econometric analyses for 163 countries every five years (from 1950 to 2020) and city-level econometric analyses for 12,877 cities every five years (from 1975 to 2020). Notes: Cities that have at least one building above 55 meters and have a population greater than 50,000. Figure 1 shows tall building heights per capita in cities around world.įigure 1 Map of tall builidng stocks per capita For this study, we include all completed, occupiable structures above 55 meters (about 14 floors). We analyse tall building completions using a novel dataset from Emporis – a global provider of tall buildings data – on the location, year of construction, heights, and uses of nearly all tall buildings in the world. Our research adds to our understanding of why there is so much global variation in tall building stocks (Barr and Jedwab 2022). While cities can physically grow via land expansion – by building out – they can also grow by becoming more vertical – by building up (Jedwab et al. Given the durable nature of real estate, policies and preferences regarding different types of structures can have long-run effects on the wellbeing of cities and their residents (Barr et al. This is true even though real estate is one of the largest asset classes in the world. Dramatic skylines in Chicago, Hong Kong, and Dubai, for example, are visible manifestations of each city’s growth (Ahlfeldt and Barr 2020).ĭespite the increasing role of tall buildings for local and national economies (Ahlfeldt and Jedwab 2022), little is known about how tall building stocks vary globally and what drives international differences (Ahlfeldt and Barr 2022). Alongside this urbanisation has been the rise of tall buildings. Today, more than half of the world’s population lives in cities, and this figure will keep rising in the coming decades (World Bank 2022). Over the past century, humanity has experienced dramatic urbanisation.
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