Brasil Urbanização, Crescimento e Bem-estar Um projeto de pesquisa do IPEA e do Banco Mundial Apresentado no 3 rd Urban Research Symposium Presented by Daniel da Mata (IPEA) and Somik V. Lall (Banco Mundial) April 5, 25 Brasília IPEA: Daniel da Mata, Piedade de Morais, Joao Carlos, Alexandre Ywata Banco Mundial / Brown U.: Kenneth Chomitz, Uwe Deichmann, Vernon Henderson, Somik V. Lall, Hyoung Wang Policy Debates in Brazil Motivation What are the relative roles of secondary cities vs. large agglomerations in boosting and absorbing poor migrants? What are the prospects for in spatially less-favored areas? Linkages between agricultural and urban? Analytic and Empirical Question(s) What is the role of policy interventions to offset (build on) the costs (benefits) of geography and history? How can cities who are lagging catch up with cities having first mover advantage? There are no one size fits all policies for cities Presentation Outline Economic Growth A. Low, Low Typically highly specialized Providing basic amenities and public services Institution and governance bottlenecks C. High, Low Service delivery needs to keep up or catch up with Managing externalities from Infrastructure investments that anticipate future to avoid potential bottlenecks Urban Size/ Density B. Low, High Relatively diverse cities specializing in sunset industries M aintaining infrastructure and providing services Need to stimulate new anchor industries with multiplier effects D. High, High Challenges of maintaining existing infrastructure and expanding new networks Strengthen institutions and local urban management to effectively accommodate Absorb new residents Provide stylized facts on Population Productivity Managing externalities Preliminary results on factors that stimulate population and productivity Implications of these findings Main Findings Descriptive Questions Productivity is higher in cities with better access to markets/ lower transport costs Better human capital and education quality Better local public service provision Higher economic diversity and manufacturing concentration Employment is primarily driven by urban rural wage differentials and rural populations in the city s hinterland Existence of local land use, zoning, and planning laws are not associated with managing the rate of slum formation How have Brazilian cities grown over time and where has population and income been unusually strong? How did the character of urban economy changed? Role of economic specialization across cities over time Role of diversification: Does it help absorb macroeconomic shocks? Does it attract a wider pool of skilled labor? How has poverty and inequality changed across cities over time? What are proximate determinants of urban poverty? How do we identify successful cities? 1
All net population over the next 25 years will be in urban areas Urban dynamics in Brazilstylized facts (Agglomerations are defined as contiguous set of MCAs with more than 75, population and 75% urbanized in 1991) Population (mio 25 2 15 1 5 Total Urban Rural This will add 5 million people to Brazil s cities Rural population will decline further 195 196 197 198 199 2 21 22 23 Source: UN Population Division, World Urbanization Prospects Growth is occurring across the urban size distribution 197 2 > 5 million 2 3 2-5 million 1 7 1-2 million 4 8 5, - 1 million 5 14 25, - 5, 16 3 1, - 25, 44 46 < 1, 51 15 Total number of agglomerations 123 123 Of the 123 major urban agglomerations in Brazil, only 3 were above 2 million in 197 versus 1 today. Another 22 have between 5, and 2 million people Population of urban agglomerations 2 Strongest in Center West and North cities, 197-2 Cities with fastest population 197-2 Annual % rate, 197-2 6 5 4 3 2 1 North Northeast Central- Southeast South Total Growth has been slowest in the South and Southeast, where rapid urban expansion occurred in an earlier period Top 7 Cities Region Population in 197 Population In 2 Annual pop (197-2, %) Campo Grande West -Central 14,233 663,621 5.18 Cuiabá West -Central 226,437 1,51,183 5.12 Brasília West -Central 761,961 2,965,951 4.53 Goiânia West -Central 45,538 1,651,691 4.33 Manaus North 534,6 1,865,91 4.17 Petrolina Northeast 122,9 428,841 4.17 Vitória Southeast 385,998 1,337,187 4.14 West Total Urban Average of the top 7 cities 374,59 1,423,482 4.52 Average of others (65) 571,85 1,231,759 2.54 total (72) 552,631 1,25,398 2.73 * For the cities with population greater than 1, in 197. 72 cities meet this cutoff criterion. 2
What do rapidly growing Center West cities do? Agro processing hubs for servicing rural demand (food and beverage manufacturing) Transportation and logistics services Other Services (public service ; education; health; finance) Examining incomes/ productivity Relative to the national average, wages are higher in larger cities At the same time, trends suggest convergence in wages cities with lower wages in 197 are growing relatively faster Retail and wholesale trade per captia income/national average 1 2 3 relative income vs. ln(pop) in 197, 2 Potential market integration and per capita wages, 2 1 12 14 16 18 ln(pop) per capita income/national average in 197 per capita income/national average in 2 annual income (7-) vs. ln(income in 197) annual income (7-) -.2.2.4.6 3.5 4 4.5 5 5.5 6 ln(per capita income in 197) annual income (7-), North annual income (7-), South Darker areas have higher market potential Change in incomes 1991-2 Specialization index Urban productivity is influenced by economic composition Insights into relative specialization.7.6.5.4.3.2.1 198 2 est st Total Specialization index: Economic diversity enhances productivity through urbanization economies er agglomerations are more specialized than larger ones But specialization has decreased everywhere in the last 2 years 3
25 2 15 1 5 25 2 15 1 5 25 2 15 1 5 Employment shares in agglomerations relative to national average, % 25 198 2 2 15 1 5 25 198 2 15 1 5 Food & Beverages 2 9 15 Electrical / 8 1 electronic machinery 7 5 6 5 4 3 2 25 1 198 2 2 Public services Percent The emergence of services and decentralization of manufacturing to the periphery of large agglomerations Secondary sector Tertiary sector 197 2 Core area's secondary industry share est st Total Percent 9 8 7 6 5 4 3 2 1 Secondary sector Tertiary sector Core area's secondary industry share est st Total Managing externalities Proximate Determinants Labor demand/ productivity Change in percentage of slum households 1991-2 Orange: Percentage of slum households increased Labor supply Blue: Percentage of slum households decreased Note that absolute number of slum households may still have increased What explains variations in productivity? Underlying model Economic performance is driven by : demand for a city s product (market potential) Relative specialization manufacturing/ services ratio Transport and logistics costs Local amenities and innovations that expand the city s production frontier Human capital that boosts productivity Estimate various specifications that account for endogeneity and effect of (positive) unobservable attributes What explains variations in employment? Underlying model city s labor supply curve wages a city offers wages in neighboring rural areas labor availability in the city s hinterland housing rents and other retail prices local taxes local public services and consumer amenities Supply curve gets flatter over time Only significant determinants are (a) wages offered in the city (+); (b) wages in neighboring areas (-); labor available in the hinterland (+) Local innovations and amenities are not significant 4
Main Findings Productivity and employment in secondary cities driven by manufacturing decentralization and rural demand But not all secondary cities will benefit from this process Local innovations such as education quality and public service provision are important However, still need to evaluate the relative impact of local innovations vis-a-vis federal / state interventions Further analytic and empirical work is needed to establish linkages between rapid urban, local regulations, and slum formation Further work The results presented today are preliminary and will be refined over the coming months Data Issues Limited meaningful data on slum formation/ informal settlements as well as effectiveness of local regulations Access to finance and industry credit needs to be examined Areas deserving more attention Supply side adjustments in response to urban management challenges (complement demand side work) Provide a typology of policies and programs that are useful for cities of different types 5