performance for 775 cities, from 2000 to 2015. It includes capital cities and cities with at least 400,000 inhabitants. located in 140 countries across all regions and all income levels.<sup>4</sup> Second, we combine Oxford Economics Dataset with city centroids data from the Global Rural‐Urban Mapping Project data set (GRUMP) to geo‐reference the cities. Since we did not have the associated geographic limits for each of the cities in the original Oxford Economics Dataset, we chose to match each city with the corresponding city centroid to avoid using arbitrary limits. Since there was no common identification for the cities in both data sets, we use the name of the city (and country) for matching purposes. Because of this limitation, not all cities were perfectly matched. After manually fixing more than 200 city names to improve the matching, we end up with 769 geo‐referenced cities, distributed by region as follows: 27.5% in East Asia Pacific, 22.5% in OECD countries, 12.5% in Latin America, 11.5% in South Asia, 9.5% in Sub‐Saharan Africa, 9% in Europe and Central Asia, and 6.5% in Middle East and North Africa. The six cities in the Oxford Dataset that we were unable to match are: Baixada Santista and Norte Catarinense (Brazil), Erdos (China), Male (Maldives), Marseille (France), and Podgorica (Montenegro).

Third, we combine the city‐level data with PM 2.5 surface data estimated by van Donkelaar et al. (2016). They combine Aerosol Optical Depth (AOD) data from MODIS satellite (NASA), MISR, and SeaWIFS Instruments with the GEOS‐Chem Chemical transport model to obtain surface‐level measures of PM 2.5.<sup>5</sup> Their resulting data set is a global raster with a resolution of 0.1 degrees x 0.1 degrees, containing the annual mean estimated surface level of PM 2.5, for the years 1998 to 2015. For each year and geo‐ referenced city, we extract the annual mean level of PM 2.5, using a 10 km buffer around the city centroids.

> 4 As mentioned in the World Bank Report (2016), income levels are defined by the World Bank Group’s per capita GDP cut‐off lines as of 2012: low income (below $1,035), lower‐middle income ($1,036‐$4,085), upper‐middle income ($4,086‐$12,615), and high income (above $12,616).

> 5 As mentioned before, because fine particles can have long lasting effects on human health, we focus our analysis on the smallest of these particles, those with diameter less than 25 microns (PM 2.5). These particles can be measured with two different methods. The first method has been widely used and consists of placing ground‐level monitors, that can measure concentration levels on the earth surface. These monitors are fairly precise but can be costly to install and maintain, involving sophisticated equipment, and requiring technical knowhow. This results in many countries having only one monitor, limiting the possibility to perform a city‐level analysis. The second method involves satellite‐driven technologies that can measure concentration levels in the atmosphere and, with the help of ground‐level measures, reasonably estimate ground‐level pollution. This method provides a global coverage of concentration levels, which makes it particularly useful for our study at the city level.

4