2 on skyscrapers and high-rise buildings only. Since 2003 Emporis has branched out, widening its database by collecting building information on all construction types.” As such, Emporis obtains data from its extensive member network of land developers, architectural firms, builders, city administrations, and banks to maintain the database. Emporis was recently bought by the CoStar group, a global leader in commercial real estate. As such, the data is confidential.

# **B2. First-step selection of the tall buildings**

We only consider “existing” or “demolished” buildings, thus ignoring “unbuilt” and “planned” buildings. We also exclude “under construction” buildings (as of 09-07-2022) since it means they did not exist as of 2019. This leaves us with 781,136 buildings. Next, we exclude buildings without geographical coordinates. This reduces the sample size to 764,343 buildings. Lastly, we exclude buildings for which we do not have any height information, which further reduces sample size to 748,651 tall buildings.

The main types of tall buildings are “high-rise buildings,” “low-rise buildings,” “skyscrapers,” and “building with towers.” Altogether, they account for 96% of buildings and almost 100% of total heights in the data. Other types of buildings include, for example, airport towers, openair structures, reactor buildings, and telecommunications towers. We do not exclude these as the satellite data that we also use cannot distinguish a building’s use. To be consistent with this other data set, we thus keep all buildings, noting that it should not be too consequential for the analysis given how little they contribute to overall heights globally.

**B3. Height variables used**

The main height variable used by Emporis is “architectural height” (meters), which “is the elevation from its base to its highest architectural element.” For some buildings where the information is missing, Emporis reports “architectural height (estimated),” which “is an automatic calculation of a probable approximation” of the architectural height based on other sources of height information and considering the building’s locality. Combining both variables, architectural height (incl. estimated) is only missing for 9,151 out of the 748,651 buildings. In contrast, the variable that we are most interested in is “roof height,” which is “the vertical elevation from the base of a building to the highest exterior portion of the shell enclosing its interior space.” Indeed, this type of height matches the most with what the satellite data captures. As such, it excludes spires and antennas, which do not occupy much volume. Roof height is missing for 724,655 of the 748,651 buildings. However, we can use “architectural height” (i.e., not including the observations for which we have “architectural height estimated” only) to recreate roof height since the two are very correlated with each other (additionally, almost all buildings do not have spires/antennas). More precisely, the coefficient of correlation between the two types of heights is 0.99 (N = 22,396). Next, to impute roof height based on architectural height, we use the following model for buildings b in locality c (N = 23,558): _ROOFHEIGHTbc_ = _α_ + _β ∗ ARCHHEIGHTbc_ + _ωc_ + _μbc._ ( _B_ 1) (1) Note that we include 1,593 locality fixed effects ( _ωc_ ). Hence, the comparison is restricted to buildings within the same locality (the locality fixed effects also control for how measurement