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Over the next 15 years, 600 cities will account for more than 60 percent of global GDP growth. Which of them will contribute the largest number of children or elderly to the world’s population? Which will see the fastest expansion of new entrants to the consuming middle classes? How will regional patterns of growth differ?
McKinsey Global Institute’s database of more than 2,000 metropolitan areas around the world have explored these questions and provided us with an interactive global map. You’ll see why growth strategies focused at the country level may fall short in the future: with new hot spots emerging and household wealth surging in little-known urban centers, companies may have to adopt a much finer-grained approach to tap into the growth that lies ahead.
For further details, see the full report, Urban world: Mapping the economic power of cities, available at the McKinsey & Company Web site.
McKinsey have provided a breakdown on the uncertainties and assumptions which we have grabbed below:
Urban world uncertainties and assumptions
This interactive presents one scenario for the urban world’s evolution. Like any scenario, it is subject to large bands of uncertainty about population trends, migration, business innovation, per capita GDP, the evolution of city structure and management, and the outlook for exchange rates. Like these uncertainties, methodological issues influence urban economic forecasts. Below are details on how we approached two key methodological issues.
Defining cities. Where possible, the cities in our database refer to integrated metropolitan areas rather than specific city jurisdictions; we aggregate neighboring cities into a single urban center. To do so, we have relied on the Functional Urban Area definition from Eurostat’s ESPON project, as well as the metropolitan statistical area definition of the US Bureau of Economic Analysis.
Our approach often results in a relatively broad definition of “city,” because in many instances the city center and the legal city make up only a fraction of a total integrated urban region, in both population and area. Examples of such aggregations include Rhein–Ruhr in Germany; Los Angeles, Long Beach, and Santa Ana in California; and Mumbai and Thane in India. In some cases, functional urban regions cut across national boundaries (for instance, Geneva in Switzerland and France, as well as Copenhagen–Malmo in Denmark and Sweden). However, to be consistent across regions, we also strive to separate urban entities that are located closely together but have relatively little cross-city integration measured by commute flows (for instance, Seoul, Incheon, and Suwon in South Korea, as well as Beijing and Tianjin in China).
Measuring GDP. The MGI Cityscope database encompasses several GDP-measurement approaches because different ones are better suited to some purposes than to others. Per capita GDP figures, for example, are expressed in 2007 purchasing-power-parity (PPP) exchange rates, which are useful for shedding light on differences in living standards. On the other hand, in this interactive we express overall urban GDP data in US dollars measured at the real exchange rate (RER) because it most closely approximates the expected dollar value of revenues or income earned in different currencies. The RER for 2007 is the market exchange rate. We predict the 2025 RER from differences in per capita GDP growth rates, in order to approximate the combined effect of changes in local prices and market exchange rates that affect the dollar value of GDP or income in each country.1