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Economics 216:The Macroeconomics of Development
Lawrence J. Lau, Ph. D., D. Soc. Sc. (hon.)Kwoh-Ting Li Professor of Economic Development
Department of EconomicsStanford University
Stanford, CA 94305-6072, U.S.A.
Spring 2002-2003
Email: [email protected]; WebPages: http://WWW.STANFORD.EDU/~LJLAU
Lecture 1The Historical Experience of
Economic Development
Lawrence J. Lau, Ph. D., D. Soc. Sc. (hon.)Kwoh-Ting Li Professor of Economic Development
Department of EconomicsStanford University
Stanford, CA 94305-6072, U.S.A.
Spring 2002-2003
Email: [email protected]; WebPages: http://WWW.STANFORD.EDU/~LJLAU
Lawrence J. Lau, Stanford University 3
Defining and Measuring DevelopmentWhat distinguishes a developed from a developing (underdeveloped) economy?Economic development is multi-dimensional.Level of well-being (aggregate and per capita).
Current consumption of goods and servicesPotential consumption of goods and services (gross national product (GNP))Net change in tangible wealth (increase in physical capital stock, discovery and depletion of natural resources) Current and future potential consumption of goods and services (national wealth, including natural resources and intangible wealth such as human, R&D and other forms of intellectual capital, goodwill)Quality of life (leisure, life expectancy, literacy, health (infant mortality, morbidity), environment, choice (freedom), security, rule of law)
Distribution of consumption, income, wealth and other benefits of economic development; satisfaction of basic needs; extent and incidence of poverty (both in itself and along ethnic, class and geographical lines); equality of opportunities (consumption externalities).An economically developed country may be underdeveloped in other non-economic, e.g., social and political, dimensions.The rate of growth is just as important as the level--Is there improvement over time? Is life getting better? Is there hope for the future?
Lawrence J. Lau, Stanford University 4
GNPs of Selected Economies, 2000GNP of Selected Countries/Regions, 2000
(Data source: World Bank)
$0
$2
$4
$6
$8
$10
$12
Uni
ted
Stat
es
Uni
ted
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gdom
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y
Japa
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Port
ugal
Spai
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Zea
land
Bra
zil
Mex
ico
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Hon
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Chi
na
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nesi
a
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ea, R
ep.
Mal
aysi
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ppin
es
Sing
apor
e
Tai
wan
Tha
iland
Rus
sian
Fed
erat
ion
Slov
enia
Nig
eria
Country/Region
trillion US$
Lawrence J. Lau, Stanford University 5
Distribution of GNP Per CapitaTotal World GNP in 2001 was US$31.5 trillion (compared to an U.S. GNP of approximately US$10 trillion)World GNP per capita in 2001 was US$ 5,140
Type of economy Average Per Capita GNPLow-Income US$430Lower & Middle-Income US$1,160High-Income US$26,710
GNP per capita in 2000 ranges from a low of US$100 (Ethiopia) to a high of US$42,060 (Luxembourg), a multiple of more than 400. U.S. GNP per capita in 2000 is US$34,100.The mode of the distribution of GNP per capita by countries is between US$200 and US$400, with a relative frequency of 0.168; the median is between US$1,660 and US$1,670 (Russia, Tonga, West Bank & Gaza, and Romania).GDP per capita in 2002
United States US$37,000China US$980
Lawrence J. Lau, Stanford University 6
Real GNPs per Capita of Countries and Regions of the World, US$, 2000
1 Ethiopia 100 44 Zimbabwe 460 87 Romania 1670 130 Mexico 50702 Burundi 110 45 Senegal 490 88 Guatemala 1680 131 Czech Rep 52503 Sierra Leone 130 46 Haiti 510 89 Iran, Islam 1680 132 Uruguay 60004 Eritrea 170 47 Armenia 520 90 Jordan 1710 133 St. Kitts an 65705 Malawi 170 48 Congo, Rep 570 91 Fiji 1820 134 Seychelles 70506 Guinea-Bissau 180 49 Indonesia 570 92 Macedonia 1820 135 Saudi Arab 72307 Niger 180 50 Cameroon 580 93 Suriname 1890 136 Argentina 74608 Tajikistan 180 51 Lesotho 580 94 Maldives 1960 137 Korea, Rep 89109 Chad 200 52 Bhutan 590 95 Marshall I 1970 138 Malta 912010 Burkina Faso 210 53 Azerbaijan 600 96 El Salvado 2000 139 Barbados 925011 Mozambique 210 54 Cote d'Ivo 600 97 Thailand 2000 140 Antigua an 944012 Rwanda 230 55 Solomon Is 620 98 Colombia 2020 141 Slovenia 1005013 Mali 240 56 Georgia 630 99 Namibia 2030 142 Portugal 1112014 Nepal 240 57 Papua New 700 100 Peru 2080 143 Greece 1196015 Madagascar 250 58 Ukraine 700 101 Tunisia 2100 144 Cyprus 1237016 Cambodia 260 59 Turkmenis 750 102 Micronesia 2110 145 New Zeala 1299017 Nigeria 260 60 Equatorial 800 103 Dominican 2130 146 Macao, Ch 1458018 Kyrgyz Republ 270 61 China 840 104 Jamaica 2610 147 Bahamas, 1496019 Tanzania 270 62 Sri Lanka 850 105 St. Vincent 2720 148 New Caled 1506020 Central African 280 63 Guyana 860 106 Belarus 2870 149 Spain 1508021 Angola 290 64 Honduras 860 107 Latvia 2920 150 Israel 1671022 Lao PDR 290 65 Djibouti 880 108 Lithuania 2930 151 French Pol 1729023 Sao Tome and 290 66 Syrian Ara 940 109 South Afri 3020 152 Kuwait 1803024 Togo 290 67 Yugoslavia 940 110 Turkey 3100 153 Italy 2016025 Uganda 300 68 Kiribati 950 111 Belize 3110 154 Australia 2024026 Zambia 300 69 Bolivia 990 112 Gabon 3190 155 Canada 2113027 Sudan 310 70 Philippines 1040 113 Panama 3260 156 Ireland 2266028 Gambia, The 340 71 Albania 1120 114 Botswana 3300 157 France 2409029 Ghana 340 72 Vanuatu 1150 115 Malaysia 3380 158 United Kin 2443030 Kenya 350 73 Morocco 1180 116 Brazil 3580 159 Belgium 2454031 Uzbekistan 360 74 Ecuador 1210 117 Estonia 3580 160 Singapore 2474032 Bangladesh 370 75 Bosnia and 1230 118 Slovak Rep 3700 161 Netherland 2497033 Benin 370 76 Kazakhstan 1260 119 Mauritius 3750 162 Germany 2512034 Mauritania 370 77 Cape Verd 1330 120 Grenada 3770 163 Finland 2513035 Yemen, Rep. 370 78 Swaziland 1390 121 Costa Rica 3810 164 Austria 2522036 Comoros 380 79 Paraguay 1440 122 Lebanon 4010 165 Hong Kon 2592037 Mongolia 390 80 Samoa 1450 123 St. Lucia 4120 166 Sweden 2714038 Vietnam 390 81 Egypt, Ara 1490 124 Poland 4190 167 Iceland 3039039 Moldova 400 82 Bulgaria 1520 125 Venezuela, 4310 168 Denmark 3228040 Nicaragua 400 83 Algeria 1580 126 Chile 4590 169 United Sta 3410041 Pakistan 440 84 Russian Fe 1660 127 Croatia 4620 170 Norway 3453042 Guinea 450 85 Tonga 1660 128 Hungary 4710 171 Japan 3562043 India 450 86 West Bank 1660 129 Trinidad a 4930 172 Switzerlan 38140
173 Luxembou 42060
GNP per Capita, US$,2000
Lawrence J. Lau, Stanford University 7
Relative Frequency Distribution of Real GNP per Capita of Countries & Regions of the World
Relative Frequency Distribution of Real GNP per Capita of Countries & Regions of the World
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0.18
0
1400
2800
4200
5600
7000
8400
9800
1120
0
1260
0
1400
0
1540
0
1680
0
1820
0
1960
0
2100
0
2240
0
2380
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0
2660
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3080
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0
3360
0
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0
3780
0
3920
0
4060
0
4200
0
Real GNP per Capita, 2000 US$
Rel
ativ
e Fr
eque
ncy
<2000 2000-6000 6000-10000 >10000
Lawrence J. Lau, Stanford University 8
Is Economic Development an Absolute or Relative Concept?
In 1963, Japan was considered to have achieved developed countrystatus by attaining the then GNP per capita of Italy, which had the lowest level of GNP per capita among the developed countries at the time (US$6,000 in 1963 prices, equivalent to US$28,100 in 2000 prices).A year later, Japan was admitted as a member of the Organization for Economic Cooperation and Development (OECD)South Korea (GNP per capita = US$8,910 in 2000) was admitted as a member of OECD in 1997 (however, South Korean GNP per capita declined precipitously in US$ terms as a result of the East Asian currency crisis of 1997-1998).Should we use the real GNP per capita of Italy in 1963 or the current real GNP per capita of Italy (US$20,160 in 2000) as a criterion?
Lawrence J. Lau, Stanford University 9
GNP per Capita of Selected Economies, 20002000 GNP per Capita of Selected Countries and Regions
(Data Source: The World Bank)
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
Uni
ted
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es
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gdom
Fran
ce
Ger
man
y
Ital
y
Japa
n
Gre
ece
Port
ugal
Spai
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New
Zea
land
Bra
zil
Mex
ico
Chi
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Hon
g K
ong,
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Indo
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Kor
ea, R
ep.
Mal
aysi
a
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ppin
es
Sing
apor
e
Tai
wan
Tha
iland
Rus
sian
Fed
erat
ion
Slov
enia
Nig
eria
Sout
h A
fric
a
Country/Region
US$
Lawrence J. Lau, Stanford University 10
A Working Definition of a Developed Economy
Economies on the borderline of “developed” statusEconomy Per Capita GNP in 2000Argentina US$7,460Greece US$11,960Italy US$20,160South Korea US$8,910Mexico US$5,070New Zealand US$12,990Portugal US$11,120Slovenia US$10,050Spain US$15,080Taiwan US$14,188
An economy is said to be developed if its GNP per capita exceedsUS$10,000 in 2000 US$.There are very few economies that will be wrongly classified.
Lawrence J. Lau, Stanford University 11
Measurement and Comparability IssuesGNP--Gross National Product--the value of goods and services produced by the nationals of a country (regardless of location) in a given period.GDP--Gross Domestic Product--the value of goods and services produced within the geographical boundaries of a country or region in a given period.The differences between GNP and GDP—net factor incomes from abroad--incomes of foreign direct investment and expatriate workers, profits earned by foreign investors (both portfolio and direct) and lenders—are for most economies quite minor.As an indicator of the well-being or the standard of living of the nationals of a country, GNP is more reliable than GDP.
Lawrence J. Lau, Stanford University 12
GNP/GDP RatiosGNP/GDP Ratio
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
0 5000 10000 15000 20000 25000 30000 35000 40000 45000
GNP per Capita (2000 US$)
GN
P/G
DP
Rat
io
1960 1970 1980 1990 2000
Lawrence J. Lau, Stanford University 13
Measurement and Comparability IssuesAggregate or per capitaLevel or rate of growthMarket or “Purchasing-Power-Parity” (PPP) exchange rate
Relative prices of goods and services differ across countriesOne would want to make international comparison of aggregate real output or GNP that abstracts from differences in relative prices--use of a single common set of pricesAn index number problem--the outcome depends on the set of prices usedDifferences in prices across countries are the greatest in the non-tradable sector (e.g., real estate, service sector); prices of tradable goods are less variable across countries although there are also differences in transportation costs, tariffs, distribution margins and tastes.Differences in prices may in turn induce differences in the composition of the outputs of different countries, further affecting the results of the comparison—it is in principle possible for two economies to have alternately a higher “PPP” GDP than the other depending on the set of prices used. PPP adjustments typically raise the GNP of low-income countries and lower the GNP of high-income countries
Differences in basic needs (e.g., climatic and physiological differences) may also cause differences in prices in addition to differences in tastes.
Lawrence J. Lau, Stanford University 14
GNP (PPP) per Capita and GNP per Capita,1995
GNP (PPP) per Capita and GNP per Capita, 1995, US Dollars
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
45,000
0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 45,000
GNP per Capita, 1995 US$
GN
P (P
PP) p
er c
apita
Lawrence J. Lau, Stanford University 15
GNP (PPP) per Capita and GNP per Capita, 2000
GNP (PPP) per Capita and GNP per Capita, 2000, US Dollars
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
45,000
0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 45,000
GNP per Capita, 2000 US$
GN
P (P
PP) p
er C
apita
Lawrence J. Lau, Stanford University 16
GNP (PPP) per Capita and GNP per Capita, 1995 (Logarithmic Scale)
GNP (PPP) per capita and GNP per capita, 1995, US Dollars
10
100
1,000
10,000
100,000
10 100 1,000 10,000 100,000
GNP per capita
GNP
(PPP
) per
cap
ita
Lawrence J. Lau, Stanford University 17
GNP (PPP) per Capita and GNP per Capita, 2000(Logarithmic Scale)
GNP (PPP) per Capita and GNP per Capita, 2000, US Dollars
10
100
1,000
10,000
100,000
10 100 1,000 10,000 100,000
GNP per Capita, 2000 US$
GN
P (P
PP) p
er C
apita
Lawrence J. Lau, Stanford University 18
Measurement and Comparability IssuesTangible and intangible investment and wealth (the effect of treatment of expenditures on education, R&D, software, goodwill, re-organization and restructuring that are routinely expensed (for accounting and tax reasons) in under-estimating true value-add (GNP) and savings and investment)Depletion of exhaustible resources--oil, forests, other minerals, guano, etc--and degradation of air and water and other natural and environmental resources should be subtracted from GNP (it is similar to a reduction of the stock of inventory)
Kuwait and Saudi Arabia have high measured GNP per capita but are not considered developed economies
Unrealized capital gains and lossesThe value of time (leisure) and other non-market activities
e.g., imputation of income from owner-occupied residential housing and consumer durableMarketization or monetization boosts measured GDP and GNP without necessarily increasing welfare to the same extent. Is there real value added?
Is an expenditure on a good or service a benefit or a cost? A question of the origin or initial conditions (e.g., should elective surgery be treated differently from non-elective surgery?)
Lawrence J. Lau, Stanford University 19
Indicators of Economic Development Other Than Real GNP per Capita
Real consumption per capita; energy consumption per capitaThe rate of growth of population; the rate of fertility
Economic development is almost always preceded by a decline in the rate of growth of population (the outliers in 2000 are Jordan and Singapore) and the rate of fertilityThe rate of fertility has been shown empirically to depend on female education and female educational and employment opportunities and on the degree of urbanization
The shares of value added originating from and the share of labor force employed by agriculture (primary), industry (secondary) and service (tertiary) sectors
The shares of agriculture in GDP and employment always decline with the level of economic development, with the former declining faster than the latter. However, two kinds of services may be distinguished--high value-added and low-value added services (internet, financial, professional services versus fast-food and hawking in the streets). Thus, the shares of the service sector are frequently higher than the shares of the industrial sector throughout the process of economic development. Ultimately, for developed economies, the service sector dominates.
Real wealth per capita (physical, human, and other intangible wealth (e.g., R&D capital), and natural resources); capital intensityConstruction of the “National Balance Sheet”--adding up wealth creation, depletion of natural resources and degradation of the environment as well as the net stock of portfolio and direct investments abroad and subtracting net debt owed to foreign nationals.US$10,000 in 2000 prices as a marker separating developed and developing economies
Lawrence J. Lau, Stanford University 20
Demographic Transition:The Rate of Growth of Population, 1995 (1)
Rate of Growth of Population and GNP per capita
-2.0
0.0
2.0
4.0
6.0
8.0
10 100 1,000 10,000 100,000
GNP per capita
Rate
of G
row
th o
f Po
pula
tion
(198
0)
Lawrence J. Lau, Stanford University 21
Demographic Transition:The Rate of Growth of Population, 1995 (2)
Rate of Growth of Population and GNP per capita (without oil producers)
-2.0
-1.0
0.0
1.0
2.0
3.0
4.0
5.0
10 100 1,000 10,000 100,000
GNP per capita
Rate
of G
row
th o
f Pop
ulat
ion
(198
0)
Lawrence J. Lau, Stanford University 22
Demographic Transition:The Rate of Growth of Population, 2000 (1)
Rate of Growth of Population and GNP per capita
-1
0
1
2
3
4
5
10 100 1,000 10,000 100,000
GNP per Capita, 2000, US$
Rat
e of
Gro
wth
of P
opul
atio
n (1
980-
2000
), Pe
rcen
t p.a
.
Lawrence J. Lau, Stanford University 23
Demographic Transition:The Rate of Growth of Population, 2000 (2)
Rate of Growth of Population and GNP per Capita (without oil producers)
-1
0
1
2
3
4
5
10 100 1000 10000 100000
GNP per Capita, 2000 US$
Rat
e of
Gro
wth
of P
opul
atio
n (1
980-
2000
)
Lawrence J. Lau, Stanford University 24
Demographic Transition:Total Fertility Rate and GNP per Capita
Total Fertility Rate and GNP per Capita, 1995 and 2000
0
1
2
3
4
5
6
7
8
10 100 1,000 10,000 100,000
Real GNP per Capita, US$
Tot
al F
ertil
ity R
ate
1995
2000
Lawrence J. Lau, Stanford University 25
Why Do the Shares of the Agricultural Sector in Both GDP and Employment Decline?
The demand sideEngel’s Law—the household demand for food (primary commodities) rises less than proportionately as income, I.e., its share of the budget declines or equivalently the income elasticity of demand is less than one; increased aggregate demand must come from other sectorsThe price elasticity of demand for food (agricultural commodities) is low—increases in the quantity of agricultural output result in less than proportionate increase in the value of agricultural output
The supply sideThe supply of arable land is fixed, limiting expansion of supplyIncreased productivity in agriculture releases labor force to the other sectorsThere is much more scope for product and process innovation in the industrial and service sectors compared to that of agriculture
Lawrence J. Lau, Stanford University 26
Sectoral Composition of Outputand GNP per Capita, 1995
Sectoral Composition of Output and GNP per capita, 1995
0
10
20
30
40
50
60
70
80
90
10 100 1,000 10,000 100,000
GNP per capita
Perc
ent
% Agriculture value added 1995% Industry value added 1995% Services value added 1995
Lawrence J. Lau, Stanford University 27
Sectoral Composition of Output and GNP per Capita, 1995 (without Oil Producers)
Sectoral Composition of Output and GNP per Capita, 1995 (without Oil Producers)
0
10
20
30
40
50
60
70
80
90
10 100 1,000 10,000 100,000
GNP per capita
Perc
ent
% Agriculture value added 1995% Industry value added 1995% Services value added 1995
Lawrence J. Lau, Stanford University 28
Sectoral Composition of Output and GNP per Capita, Cross-Section of All Economies, 2000
Sectoral Composition of Output and GNP per capita, 2000
0
10
20
30
40
50
60
70
80
90
10 100 1,000 10,000 100,000
GNP per capita, 2000 US$
Perc
ent
% Agriculture value added 2000% Industry value added 2000% Service value added 2000% Manufacturing value added 2000
Lawrence J. Lau, Stanford University 29
Sectoral Composition of Output and GNP per Capita, 2000 (without Oil Producers)
Sectoral Composition of Output and GNP per Capita, 2000, without Oil Producers
0
10
20
30
40
50
60
70
80
90
10 100 1,000 10,000 100,000
GNP per Capita, 2000 US$
Perc
ent
% Agriculture value added 2000% Industry value added 2000% Service value added 2000% Manufacturing value added 2000
Lawrence J. Lau, Stanford University 30
Sectoral Composition of Labor Forceand GNP per Capita, 1995
Sectoral Composition of Labor Force, 1990, and GNP per Capita, 1995
0
10
20
30
40
50
60
70
80
90
100
10 100 1,000 10,000 100,000GNP per capita
Perc
ent
Agriculture 1990Industry 1990
Lawrence J. Lau, Stanford University 31
Sectoral Composition of Labor Force and GNP per Capita, Cross-Section of All Economies, 2000
Sectoral Composition of Labor Force and GNP per Capita, 2000
0
10
20
30
40
50
60
70
80
90
100 1,000 10,000 100,000
GNP per capita
Perc
ent
Agriculture Industry Services
Lawrence J. Lau, Stanford University 32
Tangible Capital Stock per Labor Hour (1980 US$): Selected Economies
Tangible Capital Stock per Labor Hour (1980 U.S.$)
0
10
20
30
40
50
60
1953
1955
1957
1959
1961
1963
1965
1967
1969
1971
1973
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1980
US$
per
Lab
or H
our
China Hong KongIndonesia S. KoreaMalaysia PhilippinesSingapore TaiwanThailand JapanNon-Asian G5
Lawrence J. Lau, Stanford University 33
Non-Economic Indicators of DevelopmentPolitical and social dimensions of economic development
Life expectancy; infant mortality; morbidity; nutritional status; and other health status and service accessibility indicators
Life expectancy and other health status indicators generally rises with GNP per capita; however, there are countries high GNP per capita but low life expectancy (Swaziland, Namibia, South Africa, Botswana, Gabon) with low GNP per capita but high life expectancy (Tajikistan and Kyrgyz Republic) and low infant mortality
Literacy (The outliers in 2000 are Saudi Arabia and Kuwait)Educational enrollment and attainment ratesDue process or the rule of law; equality of opportunity in education and employment; social mobility; choice (freedom)The level of community satisfaction--community preferencesDegree of democratization
Lawrence J. Lau, Stanford University 34
Life Expectancy at Birth and GNP per Capita, 1995
Life Expectancy and GNP per capita
30
35
40
45
50
55
60
65
70
75
80
10 100 1,000 10,000 100,000
GNP per capita
Life
Exp
ecta
ncy
at B
irth
(199
5)
Lawrence J. Lau, Stanford University 35
Life Expectancy at Birth and GNP per Capita, 2000
Life Expectancy and GNP per Capita
30
40
50
60
70
80
90
10 100 1,000 10,000 100,000
GNP per Capita, 2000 US$
Life
Exp
ecta
ncy
at B
irth
, 200
0
Lawrence J. Lau, Stanford University 36
Literacy and GNP per Capita, 1995Adult Literacy and GNP per capita
0
10
20
30
40
50
60
70
80
90
100
10 100 1,000 10,000 100,000
GNP per capita
Adul
t Lite
racy
(199
5), p
erce
nt
Lawrence J. Lau, Stanford University 37
Male and Female Literacy and GNP per Capita, 2000
Adult Literacy and GNP per Capita
0
10
20
30
40
50
60
70
80
90
100
10 100 1,000 10,000 100,000
GNP per Capita, 2000 US$
Adu
lt L
itera
cy (2
000)
, per
cent
Male Female
Lawrence J. Lau, Stanford University 38
Average Human Capital (Years/Working-Age Person: Selected Economies)
Average Human Capital (Years of Schooling per Working-Age Person)
0
2
4
6
8
10
12
14
1953
1955
1957
1959
1961
1963
1965
1967
1969
1971
1973
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
Yea
rs p
er W
orki
ng-A
ge P
erso
n
China Hong KongIndonesia S. KoreaMalaysia PhilippinesSingapore TaiwanThailand JapanNon-Asian G5
Lawrence J. Lau, Stanford University 39
Indicators of Economic Development Other Than Real GNP per Capita
Accessibility, availability and affordability of services (communication, education, transportation, health care)The degree of equity of the income distribution; the incidence of poverty; the fulfillment of basic needsThe degree of urbanization (the rise of cities as centers of markets and manufacturing; economies of agglomeration but infrastructural and social costs). Industrialization and urbanization are complementary—industrialization (or more broadly the growth of the non-agricultural sector) requires urbanization and urbanization facilitates industrialization.The degree of socio-economic mobility
e.g., inter-generational inter-income class transition probabilitiesThe lack of a one-to-one correspondence between GNP per capita and the level of well-being (e.g., income distribution, freedom of choice (occupation, place of residence), rule of law)
Lawrence J. Lau, Stanford University 40
The Distribution of Income andEconomic Development
Simon Kuznets’s U-Shaped HypothesisThe distribution of income worsens before it improves as economic development proceeds (Taiwan was a counter-example)
Competing hypotheses on the distribution of incomeAn initially unequal distribution facilitates economic development and growth through its effect on domestic savings and investment (capitalists save and workers consume)A more equal distribution of income provides the consumer demand base for economic development and growth
The share of income held by the lowest 20% of households by income has a higher lower bound (4%) in developed economies thanin other economiesThe share of income held by the highest 10% of households by income has a lower upper bound (30%) in developed economies thanin other economiesDeveloped economies do not have extremes of income distributions—they are neither too concentrated nor too egalitarian
Lawrence J. Lau, Stanford University 41
The Distribution of Income andEconomic Development
Cause and/or effect?A perfectly egalitarian distribution of income is not efficient or Pareto-optimal given differences in endowment (everyone can be made better off)Incentive is necessary to induce and encourage labor efforts, investment and innovationA compromise between efficiency and equity (a positive-sum game)One important issue is the degree of socio-economic mobility—can someone who starts with little or no wealth become successful?
Lawrence J. Lau, Stanford University 42
The Distribution of Income and GNP per Capita (1)--Share of the Lowest 20%
The Distribution of Income and GNP per capita, 1995
0.0
2.0
4.0
6.0
8.0
10.0
12.0
10 100 1000 10000 100000
GNP per capita
Shar
e of
the
Low
est 2
0%
Lawrence J. Lau, Stanford University 43
The Distribution of Income and GNP per Capita, 2000 (1)--Share of the Lowest 20%
The Distribution of Income and GNP per Capita, 2000
0
2
4
6
8
10
12
14
10 100 1,000 10,000 100,000
GNP per Capita, 2000, US$
Shar
e of
the
Low
est 2
0%
Lawrence J. Lau, Stanford University 44
The Distribution of Income and GNP per Capita (2)—Share of the Highest 10%
The Distribution of Income and GNP per capita, 1995
0.0
10.0
20.0
30.0
40.0
50.0
60.0
10 100 1000 10000 100000GNP per capita
Shar
e of
the
High
est 1
0%
Lawrence J. Lau, Stanford University 45
The Distribution of Income and GNP per Capita, 2000 (2)—Share of the Highest 10%
The Distribution of Income and GNP per Capita, 2000
0
10
20
30
40
50
60
10 100 1,000 10,000 100,000
GNP per Capita, 2000, US$
Shar
e of
the
Hig
hest
10%
Lawrence J. Lau, Stanford University 46
Relationship between Measures of Income Inequality
Relationship between Measures of Income Inequality
0
10
20
30
40
50
60
0 2 4 6 8 10 12 14
Share of Output of Lowest 20 Percent
Shar
e of
Out
put o
f the
Hig
hest
10
Perc
ent
Lawrence J. Lau, Stanford University 47
Relationship between Measures of Income Inequality, 2000
Relationship between Measures of Income Inequality, 2000
0.0
10.0
20.0
30.0
40.0
50.0
60.0
0 2 4 6 8 10 12 14
Share of Output of Lowest 20 Percent
Shar
e of
Out
put o
f the
Hig
hest
10
Perc
ent
Lawrence J. Lau, Stanford University 48
Poverty and Economic DevelopmentPoverty, defined as an income less than US$1 in PPP prices per day per capita, has virtually disappeared in developed economiesUS$1 in PPP terms for low-income economies translates into perhaps US$0.40 in market exchange rate terms on average, or less than US$150 per capitaNote that the lowest-income countries do not necessarily have the highest incidence of poverty
Lawrence J. Lau, Stanford University 49
Poverty and GNP per capitaPercent Population under Poverty and GNP per capita
0.0
20.0
40.0
60.0
80.0
100.0
10 100 1,000 10,000 100,000
GNP per capita
Popu
latio
n un
der
Pove
rty, p
erce
nt
Lawrence J. Lau, Stanford University 50
Poverty and GNP per Capita, 2000Percent Population under Poverty and GNP per capita, 2000
0
10
20
30
40
50
60
70
80
10 100 1,000 10,000 100,000
GNP per capita, 2000 US$
Popu
latio
n un
der
Pove
rty,
per
cent
Lawrence J. Lau, Stanford University 51
Instruments for Changing the Income Distribution and Alleviating Poverty
Taxes and transfersRequires an administrative apparatus that can be costly and ineffectiveThe inflation tax is possible but is generally considered regressive (inflation benefits borrowers and harms lenders (depositors) andthere are more wealthy than poor individuals among borrowers)
Provision of public goods and services (education, health care, transportation, infrastructure)Universalization of (basic) education rather than redistribution is the key to improving the distribution of income over time
Lawrence J. Lau, Stanford University 52
The Degree of UrbanizationUrbanization and GNP per capita
0
10
20
30
40
50
60
70
80
90
100
10.0 100.0 1,000.0 10,000.0 100,000.0GNP per capita
Urba
n Po
pula
tion
as P
erce
nt o
f To
tal (
1995
)
Non-Oil Producers 1995Oil Producers 1995
Lawrence J. Lau, Stanford University 53
The Degree of Urbanization, 2000Urbanization and GNP per Capita, 2000
0
10
20
30
40
50
60
70
80
90
100
10 100 1,000 10,000 100,000
GNP per Capita, 2000, US$
Urb
an P
opul
atio
n as
Per
cent
of T
otal
(199
5)
Non-Oil Producers 2000Oil Producers 2000
Lawrence J. Lau, Stanford University 54
The Degree of Urbanization and the Share of Industry in GDP, 2000
Urbanization versus Industrialization
0
10
20
30
40
50
60
70
80
90
100
0 10 20 30 40 50 60 70 80 90 100
Industrial Value-Added as Percent of GDP
Perc
ent U
rban
izat
ion
Lawrence J. Lau, Stanford University 55
The Degree of Urbanization and the Share of Non-Agriculture in GDP, 2000
Percent Urbanization versus Percent Non-Agriculture, 2002Countries and Regions of the World
0
10
20
30
40
50
60
70
80
90
100
0 10 20 30 40 50 60 70 80 90 100
Non-Agricultural Value-Added as Percent of GDP
Perc
ent U
rban
izat
ion
Lawrence J. Lau, Stanford University 56
Characteristics of the Process of Early Economic Development
Modern economic growth dates from early 19th Century—Empirical regularities sometimes referred to as “stylized facts”A rise in the productivity of labor in the agricultural sector enabling a release of surplus output and labor to the industrial sectorA rise in industrialization supported by capital accumulation and the introduction of new technologies and organizations for production
e.g., the transition from cottage industry to factory production; the introduction of mass production and the assembly line
A decline in the share of the agricultural sector and a rise in the share of the industrial sector (including mining) in total output and employmentNatural endowments, and initial conditions, can make a difference.
Lawrence J. Lau, Stanford University 57
The Importance of Initial Endowment:Cropland per Capita
GNP per capita, Dollars and Cropland per capita, sq. m., 1995
10
100
1,000
10,000
100,000
0.0 1,000.0 2,000.0 3,000.0 4,000.0 5,000.0 6,000.0 7,000.0 8,000.0Cropland per capita, sq. m.
GNP
per
cap
ita, U
.S. D
olla
rs
Lawrence J. Lau, Stanford University 58
The Importance of Initial Endowment:Cropland per Capita, 2000
GNP per Capita, US$ and Cropland per Capita, sq. m., 2000
10
100
1,000
10,000
100,000
0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 5,000
Permanent Cropland per Capita, sq. m., 1999
GN
P pe
r C
apita
, U.S
. Dol
lars
, 200
0
Cropland per Capita
Lawrence J. Lau, Stanford University 59
Characteristics of the Process of Early Economic Development
A rise in the savings and investment ratesThere remain significant differences in savings rates across countries that cannot be fully explained—cultural reasons?
A rise in capital intensity, I.e., physical capital stock per unit laborA continuing rise in energy consumption (use) per capitaA rise in the degree of urbanization
Lawrence J. Lau, Stanford University 60
Gross Domestic Savings as a Percent of GDP and Real GDP per Capita
Gross Domestic Savings as a Percent of GDP
-40
-20
0
20
40
60
80
0 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000
GDP per capita (1995US$)
Perc
ent
1960 1997
Lawrence J. Lau, Stanford University 61
Savings Rates and Real GNP per Capita over Time
Gross Domestic Savings Rates and GNP per Capita, 1980, 1995 and 2000
-60
-40
-20
0
20
40
60
80
10 100 1,000 10,000 100,000
GNP per Capita, US$
Perc
ent
Gross domestic savings rate 1980Gross domestic savings rate 1995Gross domestic savings rate 2000
Lawrence J. Lau, Stanford University 62
The Savings Rate and Real Output per Capita: East Asian Economies
National Savings Rate and Real GNP per Capita
10
15
20
25
30
35
40
45
50
55
100 1000 10000 100000
Real GDP per Capita, 1995 US$
Perc
ent
China Hong KongIndonesia JapanKorea, Republic of MalaysiaPhilippines SingaporeThailand
Lawrence J. Lau, Stanford University 63
Savings and Investment Ratesand GNP per Capita, 1995
Savings and Investment Rates and GNP per capita
-30
-20
-10
0
10
20
30
40
50
10 100 1,000 10,000 100,000
GNP per capita
Perc
ent
Gross domestic investment rate 1995Gross domestic savings rate 1995
Lawrence J. Lau, Stanford University 64
Savings and Investment Ratesand GNP per Capita, 2000
Savings and Investment Rates and GNP per Capita, 2000
-40
-20
0
20
40
60
80
1 10 100 1,000 10,000 100,000
GNP per Capita, US$, 2000
Perc
ent
Gross domestic investment rate 2000Gross domestic savings rate 2000
Lawrence J. Lau, Stanford University 65
The Relationship between Investment Rate and Savings Rate, 1995
The Relationship between Investment Rate and Savings Rate, 1995
0
5
10
15
20
25
30
35
40
45
-30 -20 -10 0 10 20 30 40 50
Savings Rate, Percent of GNP
Inve
stm
ent R
ate,
Per
cent
of G
NP
Lawrence J. Lau, Stanford University 66
The Relationship between Investment Rate and Savings Rate, 2000
The Relationship between Investment Rate and Savings Rate, 2000
0
5
10
15
20
25
30
35
40
45
-40 -20 0 20 40 60 80
Savings Rate, Percent of GNP, 2000
Inve
stm
ent R
ate,
Per
cent
of G
NP,
200
0
Lawrence J. Lau, Stanford University 67
Savings Gap as a Percent of GNPand GNP per Capita, 1995
Savings Gap as Percent of GNP and GNP per capita, 1995
-60.0
-50.0
-40.0
-30.0
-20.0
-10.0
0.0
10.0
20.0
30.0
1 10 100 1,000 10,000 100,000
GNP per capita
Perc
ent o
f GNP
Lawrence J. Lau, Stanford University 68
Savings Gap as a Percent of GNPand GNP per Capita, 2000
Savings Gap as Percent of GDP and GNP per Capita, 2000
-90
-70
-50
-30
-10
10
30
50
10 100 1,000 10,000 100,000
GNP per Capita, 2000 US$
Perc
ent o
f GD
P
Lawrence J. Lau, Stanford University 69
Predictability of Economic DevelopmentPostwar experience--successes of unlikely countries and failures of apparently promising countries--has led to revision of the theory of economic developmentLatin America and even Africa was significantly ahead of East Asia in the 1950sPhilippines and Sri Lanka were considered in the 1950s as the most likely developing economies to succeedEconomic planning, balanced growth, and import substitution werepopular strategies in the 1950s and 1960sExport orientation turned out to be a successful strategyThe “adversity” theoryChallenges to development economists--What policies can bring about economic development in Africa (and in Philippines)?
Lawrence J. Lau, Stanford University 70
Is There a “Late-Comer’s” Advantage?An increased stock of knowledge and technology (but complementary investment is required)A larger group of potential investors, suppliers, and customers (an established global investment and trading system)The possibility of leap-frogging; there can be “creation without destruction”; e.g. mobile vs. fixed line telephones; CDs vs. videotapes; debit cards vs. checksLearning from past mistakesHowever, the distribution of benefits from technical progress favors the innovators; e.g. the notebook computer; the camera; OEM manufacturers; appropriation of the benefits of learning-by-doing
Lawrence J. Lau, Stanford University 71
Savings Rate and the Degree of Income Inequality, 1995 (1)
Savings Rate and the Degree of Income Inequality
-40
-30
-20
-10
0
10
20
30
40
50
60
0 10 20 30 40 50 60
Income Share of the Highest 10 Percent
Savi
ngs
Rat
e
Lawrence J. Lau, Stanford University 72
Savings Rate and the Degree of Income Inequality, 2000 (1)
Savings Rate and the Degree of Income Inequality, 2000
-30
-20
-10
0
10
20
30
40
50
60
10 15 20 25 30 35 40 45 50 55 60
Income Share of the Highest 10 Percent
Savi
ngs R
ate
Lawrence J. Lau, Stanford University 73
Savings Rate and the Degree of Income Inequality, 1995 (2)
Savings Rate and the Degree of Income Inequality
-40
-30
-20
-10
0
10
20
30
40
50
60
0 2 4 6 8 10 12 14
Income Share of the Lowest 20 Percent
Savi
ngs
Rat
e
Lawrence J. Lau, Stanford University 74
Savings Rate and the Degree of Income Inequality, 2000 (2)
Savings Rate and the Degree of Income Inequality, 2000
-30
-20
-10
0
10
20
30
40
50
60
0 2 4 6 8 10 12 14
Income Share of the Lowest 20 Percent
Savi
ngs R
ate