cities and economic development’
DESCRIPTION
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.TRANSCRIPT
Cities and Economic Development
Robert E. Lucas, Jr.
Madrid
December 14, 2009
• 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
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2003 Annual Report
World Populationand Production
Figure 1: Income DistributionFigure 3: GDP Per Capita, Five Regions Figure 4: Demographic Transitions
Return to: The Industrial Revolution: Past and Future
GDP per capita, five regions
1750 1800 1850 1900 1950 20000
3000
6000
9000
12000
15000
18000
1985
Dol
lars
1990 Population in millionsUK, USA, Canada, Australia, New Zealand 354Japan 124France, Germany, Netherlands, Scandinavia 184Rest of Western Europe, Eastern Europe, Latin America 986 Asia (except Japan), Africa 3590
• 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 ?
• No question about statistical relation between urbanization and eco-nomic success
• Look at cross-section plot of employment share in agriculture and percapita GDP (in logs)
• 112 countries, World Bank, 1980
• 9.5 = log(13500), 6.5 = log(665)
5.5 6 6.5 7 7.5 8 8.5 9 9.5 10 10.50
10
20
30
40
50
60
70
80
90
100AGRICULTURAL EMPLOYMENT SHARES, 112 COUNTRIES, 1980
LOG GDP PER CAPITA, 1990 DOLLARS
EM
PLO
YM
EN
T S
HA
RE
OF
AG
RIC
ULT
UR
E
• Look at historical data (Kuznets, 1971, Economist) on four countries
1800 1820 1840 1860 1880 1900 1920 1940 1960 1980 20000
10
20
30
40
50
60
70
80
90EMPLOYMENT SHARES IN AGRICULTURE: FOUR COUNTRIES
U.K.
U.S.
Japan
India
6 6.5 7 7.5 8 8.5 9 9.5 10 10.50
10
20
30
40
50
60
70
80
90EMPLOYMENT SHARES IN AGRICULTURE: FOUR COUNTRIES
LOG PER CAPITA GDP
EM
PLO
YM
EN
T S
HA
RE
, PE
RC
EN
T
U.K.
U.S.
Japan
India
• How interpret these relationships?
• Increases in agricultural productivity obviously essential
• Are cities just side-effects of this agricultural success? Places for richlandowners 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 NorthAmerica were pairs (665, 0.85)
• 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
• 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 112countries against their 1960 income levels
0 2000 4000 6000 8000 10000 12000 14000-0.04
-0.02
0
0.02
0.04
0.06
INCOME LEVELS AND GROWTH RATES, 112 COUNTRIES
1960 Per Capita Income (1990 $)
Ann
ual G
row
th R
ate,
196
0-20
00
• Now classify as “open”, “closed” (Sachs-Warner, 1995)
0 2000 4000 6000 8000 10000 12000 14000-0.04
-0.02
0
0.02
0.04
0.06
INCOME LEVELS AND GROWTH RATES, 112 COUNTRIES
1960 Per Capita Income (1990 $)
Ann
ual G
row
th R
ate,
196
0-20
00
• Can connect some of these dots with a simple model of catch-upgrowth
• Take country’s per capita GDP to be proportional to knowledge level
• Consider country with knowledge level h; leader (US) has level H > h
• Assume1
H
dH
dt= μ (a constant)
1
h
dh
dt= μ
µH
h
¶θ
• Call θ ∈ [0, 1] a spillover parameter: measure of rate of idea flows
• 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 about1
h
dh
dt= (.02)(4.4)θ
• If θ = 0, growth is 0 : Spain should never catch up!
• If θ = 1, growth is .09: Spanish income converges to US level fast
• 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?
0 2000 4000 6000 8000 10000 12000 140000
0.01
0.02
0.03
0.04
0.05
0.06
0.07INCOME LEVELS AND GROWTH RATES, 39 OPEN ECONOMIES
1960 Per Capita Income (1990 $)
Ann
ual G
row
th R
ate,
196
0-20
00
Parameter Values
θ = .67
µ = .02
0 2000 4000 6000 8000 10000 12000 140000
0.01
0.02
0.03
0.04
0.05
0.06
0.07INCOME LEVELS AND GROWTH RATES, 39 OPEN ECONOMIES
1960 Per Capita Income (1990 $)
Ann
ual G
row
th R
ate,
196
0-20
00
Parameter Values
θ = .5, .67, .83
µ = .02
1950 1960 1970 1980 1990 20001
1.5
2
2.5
3
3.5
4
4.5
5RELATIVE PER CAPITA GDP: US AND SPAIN
1880 1900 1920 1940 1960 1980 20006.5
7
7.5
8
8.5
9
9.5
10
10.5LOG INCOME, EIGHT COUNTRIES
LOG
PE
R C
AP
ITA
RE
AL
GD
PCOUNTRIES, ORDERED BY 1870 INCOME LEVELS
United Kingdom
United States
France
Germany
Canada
Italy
Spain
Japan
• But there are other open economies that do not fit this model at all
• Who are they?
0 2000 4000 6000 8000 10000 12000 140000
0.01
0.02
0.03
0.04
0.05
0.06
0.0716 ASIAN COUNTRIES
1960 Per Capita Income (1990 $)
Ann
ual G
row
th R
ate,
196
0-20
00
Indonesia
Sri Lanka
Malaysia
Thailand
-- open
-- closed
South Korea
Taiwan
Singapore
Hong Kong
Japan
• Countries that still have large traditional agriculture share: Why isthis?
• 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
• Try to summarize the process of development that these observationssuggest
• 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 entireeconomy
• 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-generatingurban middle class
• How do these forces balance out, in economies with reasonable gov-ernments?
• The rate of growth of an economy’s urban sector depends on twofactors:
— 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)
• 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, whichhave
— a world environment with much better technology than theirs, and
— a labor force that can make good use of this technology
• These are ways that a large traditional sector works as a drag oneconomic growth
• But there is a feedback affect from growth on the size of the traditionalsector
• 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 tocities 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
• 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
1880 1900 1920 1940 1960 1980 20006.5
7
7.5
8
8.5
9
9.5
10
10.5LOG INCOME, EIGHT COUNTRIES
LOG
PE
R C
AP
ITA
RE
AL
GD
PCOUNTRIES, ORDERED BY 1870 INCOME LEVELS
United Kingdom
United States
France
Germany
Canada
Italy
Spain
Japan
1880 1900 1920 1940 1960 1980 20000
0.5
1
1.5
2
2.5MEAN AND STD. DEV., LOG INCOME, EIGHT COUNTRIES
LOG
STA
ND
AR
D D
EV
IATI
ON
MEAN LOG GDP, RESCALED