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.

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

4. 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

6. • 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 ?

7. • 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)

8. 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

9. • Look at historical data (Kuznets, 1971, Economist) on four countries

10. 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

11. 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

12. • 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)

13. • 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

14. • 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

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. • Now classify as “open”, “closed” (Sachs-Warner, 1995)

17. 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 $)

18. • 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

19. • 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

20. • 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?

21. 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 $)

22. 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 $)

23. 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

24. 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

25. • But there are other open economies that do not fit this model at all
• Who are they?

26. 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 $)

27. • 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

28. • 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

29. • 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

30. • 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)

31. • 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

32. • 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

33. • 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

34. 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

35. 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