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Everything You Heard About Urbanisation Is Wrong Everything You Heard About Urbanisation Is Wrong

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Everything You Heard About Urbanisation Is Wrong Everything You Heard About Urbanisation Is Wrong Everything you heard about urbanisation is wrong Everything you heard about urbanisation is wrong By Lewis Dijkstra, [email protected] Head of the Economic Analysis Sector DG for Regional and Urban Policy, Regional & Urban Policy The well known narrative… • The world is 50% urban. • Middle income countries are less urbanised. • Low income countries are least urbanised. • Urbanisation will grow rapidly in low-income countries between 2010 and 2050. … is purely based on national definitions But national definitions are fine • “I know it when I see it”, but maybe we see different things? • The difference between national definitions must be quite small. How can we verify this without a benchmark? • A city is a relative concept and differs between cultures and countries. A global definition is not appropriate. What density reproduces the nationally defined urban population share? Urban areas … lost in translation? Big urban areas Small urban areas • High Density • Medium density • Big population • Medium population • Low shares of • Medium share of agricultural jobs agricultural jobs • Specialised services • Some services (higher education, (primary school, hospital, government) doctor) National definitions • 75 countries use • 10 use other population size or indicators than density, but population thresholds and • 100 countries use spatial units vary administrative • 47 use a designations, not a combination of statistical definition population and that can be other indicators replicated in other countries Do national definitions rely on population size and or density? Only half the countries use a minimum population size Minimum population size for urban areas, WUP 35 2014 30 25 20 15 10 5 0 Number of of countries Number Residents 14 countries use density Minimum • For the other Country density countries we don’t Germany 150 know the density Cambodia 200 • Density is highly USA 390 and 195 Canada 400 dependent on the India 400 size of the unit, Bhutan 1,000 census block vs Philippines 1,000 local authority vs China 1,500 region… What indicators can be used globally • Agricultural employment? Varies too much • Infrastructure? No harmonised data • Services? No harmonised data • Poverty? Circular argument Rural cannot be defined by problems, because then no problems = no rural • Remoteness Separate dimension Access to cities - Remoteness SDG City goals, but no city definition City Edge of Centre the city Open Space Low High Air pollution High Low Access to transport High Low Built-up area per head Low High Population change Low (neg) High Built-up change Low High Access to public transport by distance to centre 100 90 80 n o 70 i t a l u p 60 o Praha p f o Berlin % 50 London 40 Madrid 30 Paris 20 0 5 10 15 20 25 30 km from city centre Who committed to develop a global definition? • The European Union together with the OECD and the World Bank launched this commitment during Habitat III in Quito in 2016 • FAO has joined this commitment in 2017 • UN-Habitat follows this work closely • Goal: present a definition to UN Statistical Commission in 2019 • UN SC side event in 2017 and in 2018 This is not a city The population grid reduces modifiable areal unit problem • Mongolian capital: Ulaanbaatar 1.4 million inhabitants, but a density of 272 inhab/km2 • Overcomes key obstacle: the variable size and shape of administrative and statistical units • Allows to capture cities within a single large administrative unit AND a city spread out over multiple administrative units. • Fixed boundaries and high spatial resolution • Next census is going to more geo-coded Exogenous city list reproduce distortions of national definitions UN WUP City definition 2015 Cities over 300,000 9 24 Population 16 million 32 million National population share 17% 34% in cities over 300,000 Population in same cities 16 million 24 million Ho Chi Minh City 8 million 12 million Hanoi 3.6 million 7.5 million Hai Phòng 1.1 milion 1.3 million Can Tho 1.2 million 0.7 million An endogenous city list • This method relies purely on the population grid to identify cities • Other global work on cities relies on an exogenous city list • Global Rural-Urban Mapping Project (GRUMP) • Agglomeration index • Shlomo Angel’s urban extent • Any work that (in part) aims to replicate national shares will suffer from these distortions Grid cells: same shape and size and boundaries do not change Municipalities (LAU2) Population Grid 118,504 in the EU 4,404,011 in the EU Two definitions with a common element: Cities Population Creates a grid based Cities functional economic area Towns & Commuting suburbs zones Rural Non-metro areas areas Three types of grid cells Contiguous cells Urban 2 centres above 1,500 residents per km and at least 50,000 people in the centre Contiguous cells Urban 2 Clusters above 300 residents per km and at least 5,000 people in the cluster Rural Cells below 300 residents per km2 + grid cells other cells outside urban clusters Cork, Ireland: Urban centre, urban clusters and rural grid cells Three types of municipalities Cities > 50% pop. in urban centres Towns and > 50% pop. in urban clusters suburbs and not classified as city Rural area > 50% pop. in rural grid cells Urban areas = Cities + Towns and Suburbs Cork, Ireland: Urban centre, urban clusters and rural grid cells Cork, Ireland: City, towns & suburbs, and rural areas Joint EU-OECD Definition of a Functional Urban Area 28 Population by degree of urbanisation per major global region, 2015 100 90 80 70 60 50 40 30 20 10 Share of population, Share of population, in % 0 Asia Africa World Europe Oceania Cities & Carribean Latin America Towns and suburbs NorthAmerica Rural areas Russia, Ukraine, Source: JRC 2018, GHSL SMOD v9s5, WUP 2014 Urban areas WUP 2014 Belarus and Moldova More urban with the national definition or the degree of urbanisation? Pilot projects to compare definitions • Apply the definitions also to administrative units (census tracts, municipalities…) • Appraise the result: • Too urban or too rural? • Too many or too few cities? • Improve data (better population and/or remote sensing data) • Find out if/how we can improve the definitions Pilot projects by EC, OECD and WB • Australia • Mozambique • Brazil (completed) • Pakistan • Colombia • South Africa • Egypt (completed) • Haiti • Tunisia • Indonesia • Turkey • India • Uganda • Jordan • Ukraine • Malaysia • USA Australian cities 4,500,000 4,000,000 R² = 0.9957 3,500,000 3,000,000 2,500,000 2,000,000 1,500,000 1,000,000 500,000 0 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000 4,000,000 4,500,000 Colombian cities 10,000,000 R² = 0.9985 9,000,000 8,000,000 7,000,000 6,000,000 5,000,000 4,000,000 3,000,000 2,000,000 1,000,000 0 0 1,000,000 2,000,000 3,000,000 4,000,000 5,000,000 6,000,000 7,000,000 8,000,000 9,000,000 10,000,000 Brazil • We believe that this method offers a useful basis for statistical comparisons across national borders... • … useful for generating Sustainable Development Goals’ indicators, producing data for these three types of cluster or for individual municipalities … Survey by UN Statistical Division 1. Algeria 11.Mexico 2. Argentina 12.Mongolia 3. Australia 13.Namibia 4. Bolivia 14.New Zealand 5. China 15.Republic of Korea 6. Cuba 16.Senegal 7. Ecuador 17.Thailand 8. Ethiopia 18.USA 9. Indonesia 19.Venezuela 10.Japan 20.Zambia Responses to the UN survey • 9 out of 12 NSIs: it captured their main cities. • 5 out of 8 NSIs the validity was good or satisfactory (1 poor and 2 unacceptable) • 9 out of 10 NSIs could produce data by degree of urbanisation • 9 out of 13 NSIs useful for international comparisons • 11 out of 12 NSIs useful for measuring the SDGs • 5 NSIs did not reply • Some confusion about density thresholds and the distinction between cities and towns Three key tools • National fact sheets http://ghsl.jrc.ec.europa.eu/CFS.php • Interactive online mapshttp://ghsl.jrc.ec.europa.eu/visualisation.ph p# • City databasehttp://ghsl.jrc.ec.europa.eu/ccdb2016vi sual.php# National factsheets • Covers every country in the world • Shows the share of population, built-up area and land by degree of urbanisation and its changes since 1975 • Lists the biggest cities • Provides access to a list of all cities in a country with their change in population and built-up area over time • Map of the country and the capital city • Methodological info Malaysia Each city over 50,000 1975 Population 1 984 026 Built-up area 888 km2 1990 Population 3 323 272 Built-up area 900 km2 2000 Population 4 539 169 Built-up area 945 km2 2015 Population 6 472 648 Built-up area 1 039 km2 Per city • Evolution in population, built-up area and built-up per capita, 1975-2015 • Nightlights, 1990-2014 • Greenness index 1990-2014 • Particulate matter, 2000-2010 • Share of imperviousness, 2015 • Proximity to protected natural areas • Population at or below sea-level, 1975-2015 • Population on steep slopes, 1975-2015 Next steps • Distinguish towns from suburbs and villages from dispersed rural areas (done) • Validate the updated cities (June 2018) • Estimate commuting zones (summer 2018) • Update factsheets, city database and interactive maps (October 2018) Refined degree of urbanisation Driving time buffers • Commuting data is not widely available • We will create a driving time buffer around each urban centre. Distance will depend on the population size of the city, GDP per head of the country and the road network • Time series in selected countries Next events • May 2018 Urban Economics Association Conference (Dusseldorf) • September 2018 International Association of Official Statistics, (Paris) • October 2018 UN World Data Forum (Dubai) • March 2019 UN Statistical Commission (New York) • August 2019 ISI World Statistical Congress (Kuala Lumpur) Conclusions • A neutral global definition of urban is needed, national definitions are too different.
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