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'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
'Cities and economic development’
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'Cities and economic development’

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Conferencia ‘Cities and economic development’ del economista estadounidense Robert Lucas, Premio Nobel de Ciencias Económicas en 1995. Un acto que entra dentro del programa de conferencias ‘Madrid, …

Conferencia ‘Cities and economic development’ del economista estadounidense Robert Lucas, Premio Nobel de Ciencias Económicas en 1995. Un acto que entra dentro del programa de conferencias ‘Madrid, Comunidad del Conocimiento’ que organiza Madrid Network.

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  • 1. Cities and Economic Development Robert E. Lucas, Jr. Madrid December 14, 2009
  • 2. • Sustained growth in living standards–per capita GDP–a phenom- enon of the last 300 years, of the Industrial Revolution • Began in Britain, NW Europe • Diffused–and is still diffusing–to rest of world • Gave rise to vast wealth, inequality among nations
  • 3. GDP per capita, five regions 18000 15000 12000 1985 Dollars 9000 6000 3000 0 1750 1800 1850 1900 1950 2000 1990 Population in millions UK, USA, Canada, Australia, New Zealand 354 Japan 124 France, Germany, Netherlands, Scandinavia 184 Rest of Western Europe, Eastern Europe, Latin America 986 Asia (except Japan), Africa 3590
  • 4. • Industrial revolution mainly an intellectual event • Matter of creation, diffusion of knowledge, of ideas • Want to look at nature of this process • What is the role of cities ?
  • 5. • No question about statistical relation between urbanization and eco- nomic success • Look at cross-section plot of employment share in agriculture and per capita GDP (in logs) • 112 countries, World Bank, 1980 • 9.5 = log(13500), 6.5 = log(665)
  • 6. AGRICULTURAL EMPLOYMENT SHARES, 112 COUNTRIES, 1980 100 90 80 EMPLOYMENT SHARE OF AGRICULTURE 70 60 50 40 30 20 10 0 5.5 6 6.5 7 7.5 8 8.5 9 9.5 10 10.5 LOG GDP PER CAPITA, 1990 DOLLARS
  • 7. • Look at historical data (Kuznets, 1971, Economist) on four countries
  • 8. EMPLOYMENT SHARES IN AGRICULTURE: FOUR COUNTRIES 90 80 India 70 U.S. 60 50 Japan 40 U.K. 30 20 10 0 1800 1820 1840 1860 1880 1900 1920 1940 1960 1980 2000
  • 9. EMPLOYMENT SHARES IN AGRICULTURE: FOUR COUNTRIES 90 80 70 India EMPLOYMENT SHARE, PERCENT 60 50 U.S. 40 Japan 30 20 U.K. 10 0 6 6.5 7 7.5 8 8.5 9 9.5 10 10.5 LOG PER CAPITA GDP
  • 10. • How interpret these relationships? • Increases in agricultural productivity obviously essential • Are cities just side-effects of this agricultural success? Places for rich landowners and their servants to live? Babylon, Athens, Rome? • Preindustrial cities associated with wealth and, sometimes, high civi- lization, but not economic growth in the sense of growing living stan- dards for ordinary working people • On figure, Ancient Egypt, Roman and Renaissance Italy, colonial North America were pairs (665, 0.85)
  • 11. • All of this changed during the industrial revolution • Cities of modern world are centers of production • Think of iron and steel? Manufacturing? • Better, more basic to think of ideas • Think of modern city as a collection of educated problem-solvers, en- gaged in technical, work-related conversations, taking ideas from oth- ers, contributing new ones
  • 12. • Can see signs of this role of cities in data from the postwar WWII, post-colonial world • Next figure plots 40 year (1960-2000) annual growth rates of 112 countries against their 1960 income levels
  • 13. INCOME LEVELS AND GROWTH RATES, 112 COUNTRIES 0.06 0.04 Annual Growth Rate, 1960-2000 0.02 0 -0.02 -0.04 0 2000 4000 6000 8000 10000 12000 14000 1960 Per Capita Income (1990 $)
  • 14. • Now classify as “open”, “closed” (Sachs-Warner, 1995)
  • 15. INCOME LEVELS AND GROWTH RATES, 112 COUNTRIES 0.06 0.04 Annual Growth Rate, 1960-2000 0.02 0 -0.02 -0.04 0 2000 4000 6000 8000 10000 12000 14000 1960 Per Capita Income (1990 $)
  • 16. • Can connect some of these dots with a simple model of catch-up growth • Take country’s per capita GDP to be proportional to knowledge level • Consider country with knowledge level h; leader (US) has level H > h • Assume 1 dH = μ (a constant) H dt µ ¶θ 1 dh H =μ h dt h • Call θ ∈ [0, 1] a spillover parameter: measure of rate of idea flows
  • 17. • Example: U.S. growth about μ = .02 • US GDP in 1951 about 4.4×Spain’s GDP (per capita, Maddison) • Then Spains growth rate should have been about 1 dh = (.02)(4.4)θ h dt • If θ = 0, growth is 0 : Spain should never catch up! • If θ = 1, growth is .09: Spanish income converges to US level fast
  • 18. • How good is this model? What is value of θ? Is it really constant? • Apply model to open economies only • Work out predictions for Sachs-Warner plots (solve DE) • Plot curve against data. • Which θ gives best fit?
  • 19. INCOME LEVELS AND GROWTH RATES, 39 OPEN ECONOMIES 0.07 0.06 Parameter Values 0.05 θ = .67 Annual Growth Rate, 1960-2000 µ = .02 0.04 0.03 0.02 0.01 0 0 2000 4000 6000 8000 10000 12000 14000 1960 Per Capita Income (1990 $)
  • 20. INCOME LEVELS AND GROWTH RATES, 39 OPEN ECONOMIES 0.07 0.06 Parameter Values 0.05 θ = .5, .67, .83 Annual Growth Rate, 1960-2000 µ = .02 0.04 0.03 0.02 0.01 0 0 2000 4000 6000 8000 10000 12000 14000 1960 Per Capita Income (1990 $)
  • 21. RELATIVE PER CAPITA GDP: US AND SPAIN 5 4.5 4 3.5 3 2.5 2 1.5 1 1950 1960 1970 1980 1990 2000
  • 22. LOG INCOME, EIGHT COUNTRIES 10.5 COUNTRIES, ORDERED BY 1870 INCOME LEVELS United Kingdom 10 United States France 9.5 Germany Canada LOG PER CAPITA REAL GDP Italy 9 Spain Japan 8.5 8 7.5 7 6.5 1880 1900 1920 1940 1960 1980 2000
  • 23. • But there are other open economies that do not fit this model at all • Who are they?
  • 24. 16 ASIAN COUNTRIES 0.07 South Korea Taiwan 0.06 Singapore -- open -- closed 0.05 Annual Growth Rate, 1960-2000 Hong Kong Thailand Japan 0.04 Malaysia 0.03 Indonesia Sri Lanka 0.02 0.01 0 0 2000 4000 6000 8000 10000 12000 14000 1960 Per Capita Income (1990 $)
  • 25. • Countries that still have large traditional agriculture share: Why is this? • Technology diffusion is an outcome of thousands of work-related con- versations, involving suitably trained people • All of us in this room are involved in these conversations–this is what we do all day, every day • Workers in traditional agriculture are not part of these conversations: They are spectators, possibly beneficaries, but not contributors, in development process
  • 26. • Try to summarize the process of development that these observations suggest • Need to think of any economy as two parts: a modern, educated, urbanized sector, and a traditional agricultural sector • “Dual economy” • Prior to the IR, traditional sector was entire economy • In successful (i.e. OECD) economies today, modern sector is entire economy
  • 27. • Traditional economy supports a few wealthy people (owners of land, oil, etc.) but cannot generate sustained growth in living standards of working people • This model continues to describe traditional sectors in world today • Urbanized sector now comprises almost all of successful economies (Even agricultural sectors well-educated, high tech) • Characterized by continuous economic growth, built on idea-generating urban middle class
  • 28. • How do these forces balance out, in economies with reasonable gov- ernments? • The rate of growth of an economy’s urban sector depends on two factors: — Your own technology relative to the technology in the leading economies (the higher this ratio the more you learn and the faster you grow) — Your ability to process and make productive use of new ideas (the larger is your educated urban sector, the faster you grow)
  • 29. • The slow growth economies are — the very wealthy: they don’t have anyone ahead of them to learn from — the very poor: they don’t have the educated class that can make use of new technology • The fast growth economies are the middle income economies, which have — a world environment with much better technology than theirs, and — a labor force that can make good use of this technology
  • 30. • These are ways that a large traditional sector works as a drag on economic growth • But there is a feedback affect from growth on the size of the traditional sector • As the urban sector gets richer, this acts as a magnet for young, talented people • Ambitious 18 years olds in Asia, Africa, Latin America are flocking to cities that are already large, crowded • To us in the wealthy world, they may seem to be leaving idyllic sur- roundings for marginal city jobs or maybe no jobs at all
  • 31. • But they know what they are doing and if they don’t find a better life for themselves they are at least increasing the chances that their children will • They are seeking places in what V.S. Naipaul calls “the universal civ- ilization” • Their decisions are the main driving force in economic development
  • 32. LOG INCOME, EIGHT COUNTRIES 10.5 COUNTRIES, ORDERED BY 1870 INCOME LEVELS United Kingdom 10 United States France 9.5 Germany Canada LOG PER CAPITA REAL GDP Italy 9 Spain Japan 8.5 8 7.5 7 6.5 1880 1900 1920 1940 1960 1980 2000
  • 33. MEAN AND STD. DEV., LOG INCOME, EIGHT COUNTRIES 2.5 2 LOG STANDARD DEVIATION 1.5 1 0.5 MEAN LOG GDP, RESCALED 0 1880 1900 1920 1940 1960 1980 2000

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