Disclaimer: The views expressed on this website are those of the authors and do not necessarily reflect the views and policies of the Asian Development Bank (ADB) or its Board of Governors or the governments they represent. ADB does not guarantee the accuracy of the data included in this publication and accepts no responsibility for any consequence of their use. By making any designation of or reference to a particular territory or geographic area, or by using the term “country” in this document, ADB does not intend to make any judgments as to the legal or other status of any territory or area. Fostering Growth and Inclusion in Asia’s Cities Asia ian Development Outlook 2019 Update Theme Chapter Rana Hasan Economic Research and Regional Cooperation Department Asian Development Bank
Outline • Examining urbanization through nighttime lights data • Urban agglomeration economies in Asian cities • Managing the city as a labor market • Managing the urban system
Examining urbanization through nighttime lights data V4.1 3
Official statistics on urbanization • UN’s World Urbanization Prospects database • Based on official statistics of over 200 countries/economies. • Official statistics on urbanization are often based on different ways of defining and distinguishing urban settlements from rural ones • Four types of criteria typically used to define urban areas: administrative boundaries, economic parameters, population size and/or density, and urban characteristics. • Due to various combinations, there are 13 known ways to define urban areas among the 233 countries/economies in the world.
Night- time lights based “natural” city data • We use nighttime light satellite imagery to delineate the contours of urban agglomerations, which we call “natural cities” to distinguish them from administratively defined cities, and then fill in each contour with grid population data from LandScan. • With this methodology, the geographic extent and population size of the natural cities are consistently defined and estimated across space and time. • We obtain a geo-coded panel dataset that contains 1,459 natural cities in 42 economies of developing Asia between 1992 and 2016 (population available since 2000).
PHILIPPINES Cities are expanding beyond 1992 PHILIPPINES 2016 Cebu Cebu administrative boundaries • “ Natural cities ” capture actual urban footprint using nighttime INDIA INDIA 1992 2016 Kolkata Kolkata lights satellite imagery. • 1,459 natural cities are identified, hosting 34.7% of the population on 2.3% of land area. 1992 2016 • Natural cities have expanded beyond administrative boundaries. • Some have gotten connected to form city clusters . Source: ADB estimates.
Natural cities versus administrative counterparts
Natural cities by country Source: ADB estimates using nighttime lights images from the National Oceanic and Atmospheric Administration
Evolution of city sizes Distributions of Natural City Size by Land Are Distributions of Natural City Size by Population Source: ADB estimates using nighttime lights images from the National Oceanic and Atmospheric Administration and grid population data from LandScan datasets.
Urban population growth, 2000-2016 Urban population growth by size of Increase in urban population by size natural city of natural city Source: ADB estimates using nighttime lights images from the National Oceanic and Atmospheric Administration and grid population data from LandScan datasets.
Shares of urban pop. by city size: 2000 vs. 2016 Source: ADB estimates using nighttime lights images from the National Oceanic and Atmospheric Administration and grid population data from LandScan datasets.
Urban agglomeration economies in Asian cities V4.1 12
The benefits of agglomeration Concentration of households and firms enables: • Learning through spillovers of ideas and knowledge - Garments in Dhaka, soccer balls in Sialkot, IT startups in Bengaluru • Matching of input-output markets - Workers find more suitable jobs - Firms locate next to suppliers and buyers • Sharing of resources - Infrastructure - Tap into wide-ranging expertise
Why the interest in cities? • Developed world and Asia’s NIEs: • Urbanization and growth intimately connected • A key role for manufacturing historically • Strong evidence of agglomeration economies • Developing world: • Urbanization without industrial development. • Due to low cost of trade and growing role of scale economies? • A rise of “consumption” cities over “production” cities? • “Messy” urbanization? • Are people agglomerating without agglomeration economies kicking in?
Cities with 1m+ population have higher employment shares in manufacturing
Wage data suggest Asian cities do benefit from “agglomeration economies” • Nominal wages used to test the Big cities pay similar workers more presence of agglomeration Urban wage premium relative to rural areas (%) economies. • Nominal wages better capture the productive advantages of cities than real wages. • The former reflect how much more firms are willing to pay in bigger cities to comparable workers. • Using real wages is appropriate when analyzing the welfare implications of * different types of employment and studies of location choice. * Small cities’ wage premium over rural areas is not statistically different from zero. Source: ADB estimates based on labor force surveys .
Human capital and skills seem to be important channels through which agglomeration economies work Larger cities have higher returns to education …and greater diversity of occupations
Other results Larger cities have: Firm innovation and universities • Higher shares of college graduates • Greater presence of college graduates benefits less educated workers as well • Better opportunities for female workers • Presence of universities • High quality universities enable firms to be more dynamic Source: ADB estimates based on World Bank enterprise surveys, QS World University Rankings, and NTL based natural city data.
Managing the city as a labor market V4.1 19
So, is it all good news? Smaller cities need more hard and soft Large cities are likely to be infrastructure to attract modern businesses limiting their potential
Cities thrive when they function well as labor markets Low mobility scenario • Key conditions • Travel within the city is fast and cheap • Firms and households have flexibility to relocate within the High mobility scenario city • Real estate is relatively affordable Source: Adopted from Bertaud (2018)
Congestion and housing affordability are concerns Housing affordability measured by Housing affordability measured by Average congestion index of natural cities Housing price to income ratio (PIR) , 2018 with population greater than 5 million housing price to income ratio (PIR) PIR 2.0 20 17.2 1.8 15 13.6 Average 1.6 1.5 10.9 10 1.4 4.0 Developed 1.2 5 countries 1.0 0 Small (<M) Medium (1-5M) Big (>5M) Small (1<M) City size Note: The price-to-income ratio (PIR) was computed as the average house price (50 m2) divided by the mean annual household income. Source: ADB estimates using Google Maps. Source: ADB estimates using data from Colliers International; Global Property Guide; household income and expenditure surveys, various countries; Knight Frank; Makaan; National Bureau of Note: 1.5 represents the average index of the 24 cities in the chart. Statistics, People’s Republic of China; Numbeo; World Bank’s PovcalNet; Zameen.
Cities need efficient multimodal public transport system Share of trips viable by public transit and • Combine trains, buses, and ride duration of public versus driving sharing, with better regulated Ratio of duration Share of trips by privately provided autorickshaws via public transit public transit (%) to driving and jeepneys. 3.6 3.5 89.8 • Demand-side management may 2.5 be considered as well to reduce 71.1 congestion over the longer term. 63.4
Good land-use planning is on the decline Share of residential area laid out before development Share of built-up area within walking distance (625 meters) of an arterial road Source: ADB estimates using data from Land and Housing Survey of the New York University Urban Expansion Program 2016.
Must ensure that urban expansion is subject to land use planning Dhaka, Bangladesh Mumbai, India
Some land-use regulations need to be more flexible. City center floor area ratios in selected cities Construction permit, processing days Note: Each data point is a regional average across cities. Source: ADB estimates using data from World Bank’s Source: Adapted from Vishwanath et al. (2013) Doing Business database.
Housing policy options
Housing policies: Lessons learnt 1. Improve data collection and analysis (e.g. using big data). 2. Tackle supply side constraints and develop integrated neighborhoods with access to social services and efficient and affordable transportation system. 3. Incentivize the private sector to come in by de-risking their investment and providing financial incentives. 4. Develop coherent housing policies tailored to the need of each income segment. 5. Promote public and private rental market . 6. Improve efficiency in implementation of policies which often requires addressing fundamental problems, e.g. land titles.
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