Economics 320

University of Victoria, Department of Economics, Spring 2014

Overheads that Students can Download from Course Website

All Material Prepared by Carl MoskCopyright (2011): Carl Mosk *

* All rights reserved; none of this material is to be used without the written consent of the author.

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A The Great Divergence

Reading:

Collier: Part 1 (Chapter 1).

Easterly: Chapters 1 and 8.

Mosk: Chapter 1 and Appendix (pp. 353-370).

Sachs: Foreword, Chapters 1, 2, 3, and 4.

A.1 Calibrating the Great Divergence

A.1.1 Measuring Economic Development: Income per Capita

[1] Income per Capita, Supply Measures: Issues of measure

Scope

S1 – Non-marketed production (home production)

S2 – The underground economy

Netness

N1 - Avoiding double counting – want to focus on value added

Input-output table example (see page 4)

Valuation

Paasche and Laspeyres indices for output and for prices (see page 5)

V1 - The index number problem – deflating nominal output by a Paasche price index yields a Laspeyres output index; deflating nominal output by a Laspeyres price index yields a Paasche output indexV2 – Purchasing power parity (PPP) considerations: Penn World Table estimates (ICP) and International Comparison of

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Output and Productivity (ICOP) estimates – see page 6.

“Cooking the Books” – systematic governmental deception

Independence of the press and accounting agencies

Sectors

A, I and S – changing sectoral composition and economic development – productivity gain from shifting resources from A to I

[2] Demand Variables – the Macroeconomic Balance Equation (see pages 7-8)

A.1.2 The Great Divergence: Historical trends in PPP adjusted income per capita – Maddison’s estimates for regions of the world and selected countries

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Input-Output Analysis: Two Simple Examples

Table 1 The Basic Flow Table for a Two Sector Economy Without Government

Selling Sectors

Purchasing Sectors and Final Demand ComponentsA M C I Total

A$25

(5 bushels)$50

(10 bushels)$200

(40 bushels)$50

(10 bushels)$325

(65 bushels)M $100

(5 tons)$100

(5 tons)$400

(20 tons)$100

(5 tons)$700

(35 tons)Labor

(wages)$250 $350

Investors(profits & interest)

$50 $100

A – agriculture (wheat); M – manufacturing (steel); C – consumption demand; I – investment demand

In this example aggregate income equals $750.

Table 2 A Basic Flow Table for a Two Sector Economy (Without Government and Investment) Measured in Volumes (Wheat in bushels and Textiles

in Yards of Cloth)

Selling Sectors Purchasing Sectors and Consumption DemandA M C Total

A 25 bushels 20 bushels 55 bushels 100 bushelsM 14 tons 6 yards 30 yards 50 yards

Labor (person years)

80 180

Table 3 The Input Requirements per Unit of Output Selling Sectors Input Requirements (Purchasing Sectors)

A MA .25 .40M .14 .12

Labor (person years)

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Paasche and Laspeyres Indices

I Output Indices

Paasche output index: [(PX2 * X2) + (PY2 * Y2)]____________________ * 100

[(PX2 * X1) + (PY2 * Y1)]

Uses prices for the goods X and Y in the second period to calculate index of real output (output in the second period relative to output in first period = 100)

Laspeyres output index: [(PX1 * X2) + (PY1 * Y2)]____________________ * 100

[(PX1 * X1) + (PY1 * Y1)]

Uses prices for the goods X and Y in the first period to calculate index of real

output (output in the second period relative to output in first period = 100)

II Price Indices

Paasche price index: [(PX2 * X2) + (PY2 * Y2)]____________________ * 100

[(PX1 * X2) + (PY1 * Y2)]

Uses output weights for the second period to weight prices yielding price index with base in the first period = 100.

Laspeyres output index: [(PX2 * X1) + (PY2 * Y1)]____________________ * 100

[(PX1 * X1) + (PY1 * Y1)]

Uses output weights for the first period to weight prices yielding price index with base in the first period = 100.

X1 = output of good X in first period; X2 = output of good X in second period; Y1 = output of good Y in first period; Y2 = output of good Y in second period;

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PX1 = price of good X in first period; PX2 = price of good X in second period:

PY1 = price of good Y in first period; PY2 = price of good Y in second period.

Purchasing Power Parity (PPP) Considerations – Quotes from Angus Maddison (2000), Monitoring the World Economy,

1820-1992, pages 162-163.

I Three approaches for converting currencies into a common unit:

Use the exchange rate: “This is the simplest option, but exchange rates are mainly a reflection of purchasing power over tradeable items. For these goods inter-country price differences are reduced because of possibilities for trade and specialization. In poor countries where wages are low, non-tradeable items, like haircuts, government services or building construction are generally cheaper than in high income countries, so there is a general tendency for their exchange rates to understate purchasing power.”

Use purchasing power parity converters: “…the expenditure approach … is basically a highly sophisticated pricing exercise. It involves the collection of carefully specified price information by statistical agencies for representative for representative items of consumption, investment goods and government services. In the 1990 EUROSTAT exercise 2,553 prices were collected for specified sample items. These were allocated to 277 basic headings which were then aggregated to produce the PPP converters …. For countries not covered by the ICP [(International Comparisons Project)], Summers and Heston have devised short cut procedures …..”

[Note: For further details see the Penn World Tables at the following Internet website: http://pwt.econ.upenn.edu/]

Use International Comparison of Output and Productivity of University of Groningen Estimates: “This involves comparison of real output (value added) by industry of origin using census of production on output quantities as well as prices (for agriculture, industry and service activity)….”

II Geary-Khamis Approach

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“The Geary-Khamis approach …. Is an ingenious method for multilaterising the results which provides transitivity and other desirable properties … it is based on twin concepts of purchasing power parity of currencies and international average prices of commodities ….”

National Income Accounting Balance: The Aggregate Demand Side

I Basic Demand Structure

Y = GDP (Gross Domestic Product)

C = Consumption

I = Investment

G = Government Spending

X = Net Exports = Exports – Imports

DA = Effective (Aggregate) Demand = C+I+G+X = Y

Share of investment demand in aggregate demand = I/ DA

II Contributions to Growth in Aggregate Demand

Δ DA = ΔC + ΔI + ΔG + ΔX

Marginal contribution of investment demand growth = ΔI/ Δ DA

Marginal contribution of net export demand growth = ΔX/ Δ DA

II Savings/Investment Balance

Government’s Fiscal Balance Variables:

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F = government transfers to private sector

N = interest on government debt

T = taxes

Income from Abroad:

V = factor income from abroad plus transfer payments from abroad

Savings:

Sp = private savings = (Y+V+F+N-T) - C

Sg = government savings = (T-F-N)-G

Sr = rest of world savings = -(X+V)

Then:

Sp + Sg +Sr = [(Y+V+F+N-T)-C] + [T-F-N-G] –(X+V) =

Y-(C+G+X) = I

Thus

Sp + Sg +Sr = I

That is total domestic investment is the sum of domestic private (household and

corporate) saving, government saving, and “rest of world” savings which is the

negative of the trade balance.

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Table 3: The Great Divergence: Estimates of Population and Per Capita Income *

A: Estimated World Population (1,000s) and Growth Rate of World Population (%)

Population (1,000s) Growth rate (%)Year (AD) Population Period (AD) Growth rate (%)

1 230,820 1-1000 0.01 %1000 267,573 1000-1500 0.10 1500 438,428 1500-1820 0.27 1820 1,041,834 1820-1870 0.40 1870 1,271,915 1870-1913 0.80 1913 1,791,091 1913-1950 0.93 1950 2,524,324 1950-1973 1.93 1973 3,916,489 1973-2001 1.62 2001 6,149,006

B: Percentage of World Population in Regions

Region/Year AD 1 1700 1913 1950 2001Western Europe 10.7 % 13.5 % 14.6 % 12.1 % 6.4 %Eastern Europe 2.1 3.1 4.4 3.5 2.0Former USSR 1.7 4.4 8.7 7.1 4.7

Western Offshoots (United States, Canada, Australia, New Zealand)

0.5 0.3 6.2 7.0 5.5

Latin America 2.4 2.0 4.5 6.6 8.6Japan 1.3 4.5 2.9 3.3 2.1

Asia (excluding Japan) 74.2 62.1 51.7 51.4 57.4Africa 7.1 10.1 7.0 9.0 13.4World 100 100 100 100 100

C: Per Capita Income for Regions of the World (in 1990 international Geary-Khamis dollars)

Region/Year AD 1 1700 1913 1950 2001Western Europe 450 998 3,458 4,579 19,256

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Eastern Europe 400 606 1,695 2,111 6,027Former USSR 400 610 1,488 2,841 4,626

Western Offshoots (United States, Canada,Australia, New Zealand

400 476 5,233 9,268 26,943

Latin America 400 527 1,481 2,506 5,811Japan 400 570 1,387 1,921 20,683

Asia (excluding Japan) 450 571 658 634 3,256Africa 430 421 637 894 1,489World 445 615 1,525 2,111 6,049

Table 3 [Continued]

D: Growth Rates for Per Capita Income (%)

Region/Period 1000-1500

1500-1820

1820-1870

1870-1913

1913-1950

1950-1973

1973-2001

Western Europe

0.13 % 0.14 % 0.90 % 1.33 % 0.76 % 4.05 % 1.88 %

Eastern Europe

0.04 0.10 0.63 1.39 0.60 3.81 0.68

Former USSR 0.04 0.10 0.63 1.06 1.76 3.35 -0.96Western offshoots

0.00 0.34 1.41 1.81 1.56 2.45 1.84

Latin America

0.01 0.16 -0.03 1.82 1.43 2.58 0.91

Japan 0.03 0.09 0.19 1.48 0.88 8.06 2.14Asia

(excluding Japan)

0.05 0.00 -0.10 0.42 -0.10 2.91 3.55

Africa -0.01 0.00 0.35 0.57 0.92 2.00 0.19World 0.05 0.05 0.54 1.30 0.88 2.92 1.41

* Source: Angus Maddison, The World Economy. Volume 2: Historical Statistics (Paris: Development Centre of the Organisation of Economic Co-operation and Development, 2006): pp. 636-643.

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Table 4: Long-run Growth in Population, GDP and GDP per Capita in Japan and China, 1500-1998

A Levels of Population (in 1,000s) for Japan and China, 1820-1998

Date Japan China Japan/China (%)1820 31,000 381,000 8.14 %1870 34,437 358,000 9.621913 51,672 437,140 11.821950 83,563 546,815 15.281973 108,660 881,940 12.321990 123,540 1,135,185 10.881998 126,486 1,242,700 10.18

B Levels of GDP (Millions of 1990 Geary-Khamis International Dollars), Japan and China, 1820-1998

Date Japan China Japan/China (%)1820 20,739 228,600 9.07 %1870 25,393 189,740 13.381913 71,653 241,344 29.691950 160,966 239,903 67.101973 1,242,932 740,048 167.951990 2,321,153 2,109,400 110.041998 2,581,576 3,873,352 66.65

C Share of World GDP, Regions, and Japan and China, 1500-1990 (%)

Region/Country 1500 1820 1870 1913 1950 1973 1990World 100 % 100 % 100 % 100 % 100 % 100 % 100 %

Western Europe

17.9% 23.6 33.6 33.5 26.3 25.7 20.6

Western Offshoots (a)

0.5 1.9 10.2 21.7 30.6 25.3 25.1

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Asia (ExceptJapan)

62.1 56.2 36 21.9 15.5 16.4 29.5

Latin America 2.9 2.0 2.5 4.5 7.9 8.7 8.7Eastern Europe/Former USSR

5.9 8.8 11.7 13.1 13.1 12.9 5.3

Africa 7.4 4.5 3.7 2.7 3.6 3.3 3.1Japan 3.1 3.0 2.3 2.6 3.0 7.7 7.7China 34.17 22.42 7.75 3.9 1.8 7.0 11.6

Table 4 [Continued]

D Growth Rates for GDP per Capita, Japan, China, Hong Kong, South Korea and Taiwan, 1913-99

Country 1913-50 1950-99 1950-73 1973-90 1990-99Japan 0.9 % 4.9 % 8.1 % 3.0 0.9China -0.6 4.2 2.9 4.8 6.4

Hong Kong n.e. 4.6 5.2 5.4 1.7South Korea 1.5 4.9 4.4 6.8 4.8

Taiwan 0.6 5.9 6.7 5.3 5.3Difference

China – Hong Kong

n.a. -0.4 -2.3 -0.6 4.7

DifferenceChina – Taiwan

-1.2 -1.7 -3.8 -0.5 1.1

Notes: (a) Western Offshoots = United States, Canada, Australia, New Zealand.

n.e. = not estimated

Sources: Pages 126-7, 143, 146, 214-218 in Maddison (2006):

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Table 5

Structural Change in the Gross Domestic Product (GDP) of China, 1890-2004

A.1 The Composition of China’s GDP in 1890, 1913, 1933 (% in Each Sector) and Changes Between 1890 and 1933 in the Share of the Sectors

Sector 1890 1913 1933 Change in % 1890-1933

Farming, Fishery, Forestry

68.5 % 67.0 % 64.0 % -4.5

Handicrafts 7.7 7.7 7.4 -0.3Modern

Manufacturing0.1 0.6 2.5 +2.4

Mining 0.2 0.3 0.8 +0.6Electricity 0.0 0.0 0.5 +0.5

Construction 1.7 1.7 1.6 -0.1Traditional

Transport and Communications

5.1 4.6 4.0 -1.1

Modern Transport and

Communications

0.4 0.8 1.5 +1.1

Trade 8.2 9.0 9.4 +1.2Government 2.8 2.8 2.8 0.0

Finance 0.3 0.5 0.7 +0.4Personal Services

1.1 1.2 1.2 +0.1

Residential Services

3.9 3.8 3.6 -0.3

Total 100.0 100.0 100.0 n.e.

A.2 Index of GDP and Sector Outputs for 1933 (1914 = 100) and Growth Rates for GDP and the Sectors for the Period 1914/1933

Item Index Growth RateAgriculture 117.0 1.0 %

Modern Industry and 419.2 8.8

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TransportOther Industry and

Transport100.4 0.0

Services 125.2 1.3GDP 126.4 1.4

Table 5 [Continued]

A.3 Shares of Broad Sectors in GDP (%) and Changes in the Shares, 1890-1995Shares of Sectors

Sector 1890 1952 1978 1995Farming,

Fishery, Forestry68.5 % 58.6 % 33.7 % 23.2 %

Industry 8.1 9.9 34.7 41.1Construction 1.7 1.7 3.3 5.8Transport and

Communications5.5 2.4 3.5 5.2

Commerce and Restaurants

8.2 6.5 5.0 7.3

Other Services (Including

Government)

8.0 20.9 19.7 17.4

GDP 100.0 100.0 100.0 100.0Change in Shares of Sectors

Sector 1890/1995 1890/1952 1952/1978 1978/1995Farming,

Fishery, Forestry-45.3 -9.9 -24.9 -10.5

Industry +33.0 +1.8 +24.8 +6.4Construction +4.1 0.0 +1.6 +2.5Transport and

Communications-0.3 -3.1 1.1 +1.7

Commerce and Restaurants

-0.9 -1.7 -1.5 +2.3

Other Services (Including

Government)

+9.4 +12.9 -1.2 -2.3

A.4 Composition of Government Revenue Sources in 1753 and 1908 (%)Item 1753 1908

Land Tax 81.5 % 43.5 %Salt Tax 9.4 12.7

Native Customs 7.3 1.7

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Maritime Customs - 14.0Likin - 9.1

Miscellaneous 1.8 19.1Total 100.0 100.0

Table 5 [Continued]

A.5 Composition of Government Revenue and Expenditures (%) and Percent of GDP for Government Revenue and Expenditures, 1936

Share of RevenueRevenue/GDPCustoms Salt Tax Consolidated

TaxesOther (NotBorrowing)

33.3 % 22.5 % 16.5 % 27.7 % 2.8 %Share of Expenditure Expenditure/GDP

Military Indemnity/Debt Service Other33.0 % 24.9 % 42.1 % 4.0 %

A.6 Growth Rates for GDP by Sector, 1890-1995Sector 1890-1952 1952-1995 1952-78 1978-95

Farming, Fishery, Forestry

0.3 % 3.4 % 2.2 % 5.1 %

Industry 1.7 9.2 9.6 8.5Construction 1.6 8.7 7.2 11.1Transport and

Communications0.9 7.6 6.0 10.0

Commerce and Restaurants

0.8 5.9 3.3 9.9

Other Services (Including

Government)1.1 5.2 4.2 6.7

GDP 0.6 5.6 4.4 7.5GDP per Capita 0.0 3.8 2.3 6.0GDP per Worker 0.0 2.9 1.8 4.7Export Volume 1.6 9.2 6.4 13.5

A.7 Growth Rates for GDP, various Components of GDP, Population (P) and GDP per Capita (GDP/P), 1979-2000

Item 1979-84 1985-95 1996-2000GDP 8.8 % 9.7 % 8.2 %

Agriculture 7.1 4.0 3.4

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Industry 8.2 12.8 9.6Services 11.6 9.7 8.2

Foreign Trade 14.3 15.2 9.8Imports 12.7 13.4 9.5Exports 15.9 17.2 10.0

P 1.4 1.4 0.9GDP/P 7.1 8.3 7.1

Table 5 [Continued]

A.8 Growth Rates for GDP, Employment and Labor Productivity for GDP and for Major Sectors of GDP, 1952-1995

Sector 1952-78 1978-95Change Between

Two Periods (2) – (1)

AgricultureGDP 2.20 % 5.15 % +2.95

Employment 2.02 0.84 -1.18Labor Productivity 0.17 4.27 +4.10

Industry and ConstructionGDP 9.29 8.82 -0.47

Employment 5.84 4.83 -1.01Labor Productivity 3.25 3.81 +0.56

TertiaryGDP 4.18 7.86 +3.09

Employment 3.20 6.73 +3.53Labor Productivity 0.96 1.05 +0.09

Whole EconomyGDP 4.4 7.49 +3.09

Employment 2.57 2.62 +0.05Labor Productivity 1.78 4.74 +2.96Impact of Shift in

Sectoral Reallocation of Labor on GDP

Growth

0.92 1.44 +0.52

A.9 Growth Rate of Output per Worker by Broad Sector, 1978-2004Sector 1978-2004 1978-88 1988-2004Total 6.96 % 6.74 % 7.09 %

Agriculture 6.76 5.70 7.43Non-Agriculture 4.65 2.47 6.02Non-Agriculture:

State Owned4.87 3.30 5.86

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Non-Agriculture:Non-State Owned

5.59 3.89 6.67

Sources: For Panels A.1, A.3, A.6 and A.8 various tables in Maddison (1998). ForPanels A.2 and A.5 pages 15 and 272 in Rawski (1989). For Panel A.4page 176 in Perkins (1969). For Panel A.7 page 482 in Huang, Otsuka and Rozelle (2008). For Panel A.9 page 696 in Brandt, Hsieh and Zhu (2008).

B Population Growth, Agriculture and Food Consumption, Health and the Biological Standard of Living

Reading:

Easterly: Chapter 5.

Mosk: Chapters 2, 3; pages 174-185; and pages 294-300.

Sachs: Chapter 10.

B.1 Population Growth Prior to the Great Divergence: The Malthusian Model

[1] Organic and inorganic economies

Broad Stages in Long-run Economic Development

Organic Economy A (Natural energy sources – wind, water, fire)Hunting and Gathering

Organic Economy B (Natural energy sources – wind, water, fire)Settled Agriculture with Domesticated Animals

Crops – cereals (wheat, barley, rice, corn, sorghum, millet, sugar can); pulses (pea, lentil, bean, peanut); fibers (flax, hemp, cotton); roots, tubers (yam, potato, taro); melon (melon, cucumber, squash)

Animals – Major 5 (sheep, goat, cow (ox, cattle), pig, horse); and minor 9

Gradual development of natural immunity to diseases spread from animals to Humans (measles – cattle, rinderpest; tuberculosis – cattle; smallpox – cowpox or other livestock pox ; flu – pigs and ducks; pertussis – pigs, dogs; Falciparum malaria – birds)

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Approximate dates of “stages” of organic economy B in China:Plant domestication – by 7500 B.C.Animal domestication – by 7500 B.C.Pottery – by 7500 B.C.Villages – by 7500 B.C.Chiefdoms – 4000 B.C.Widespread metal tools – 2000 B.C.States – 2000 B.c.Writing – by 1300 B.C.Widespread iron tools – 500 B.C.

At higher stages of the organic economy (e.g. – Japan between 1700 and 1850)Extensive spread of proto-industrial (craft) productionFormal education spreads and basic literacy/numerical skills develop in

broad segments of the populationUrbanization and infrastructure (roads, canals, harbors) expansion

Inorganic Economy (exploitation of energy sources pent up in stocks of natural resources, e.g. in fossil fuels)

First Industrial Revolution – fossil fuels, steam power, iron and steel production streamlined, factory system, applications of steam to transport (ships, railroads)

Second Industrial Revolution – hydroelectric power, internal combustion engine (cars and airplanes, diesel engines), synthetic materials, applications of the germ theory of disease – growing demand for education and physical and financial infrastructure.

[2] The Malthusian model

B.2 The Demographic Transition

[1] The mortality transition

Mortality transition described in terms of decline in mortality from infectious/parasitic diseases and associated gain in life expectancy

Preston’s estimates of the influence of technological progress and education on the one hand, income per capita rise on the other hand, upon the gain in world life expectancy

[2] The fertility transition

Fertility transition described in terms of irreversible declines in parity progression ratios and the Hutterite index of marital fertility

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Economic models of the fertility transition:

The Chicago-Columbia human capital model

The Easterlin-Crimmins supply/demand model

B.3 Agriculture and Food Consumption: The Influence of Geography and Natural Endowments

[1] Jared Diamond’s ecological model (Guns, Germs and Steel) and the Transition from Hunting and Gathering to Settled Agriculture with Domesticated Animals

A Simple Graphical Model of the Transition from Hunting and Gathering to Settled Agriculture

Basic Thesis of Part II of the Diamond volume. The Eurasian Advantage:

“plant and animal domestication meant much more food and hence much denser human populations. The resulting food surpluses, and (in some areas) the animal-based means of transporting these surpluses, were a prerequisite for the development of settled, politically centralized, socially stratified, economically complex, technologically innovative societies ….”

Problems with/Nature of hunting-gathering that encouraged settled agriculture :

Availability of wild foods

Depletion of wild game

Development of technologies for processing and storing wild foods (sickles, baskets, mortars and pestles) encouraged domestication and settled agriculture

Greater density of food producers enabled them to displace, kill, hunter-gatherers (example: Maori over the Moriori in the Chatham Islands)

Reasons why the Fertile Crescent Made the Transition First

Climate “ …. the Fertile Crescent lies within a zone of so-called Mediterranean climate, a climate characterized by mild, wet winters and long, hot, dry summers”

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Flora Endowments: “…a second advantage … is that wild ancestors of many Fertile Crescent crops were already abundant and highly productive …” [wheat, barley]

Selfers: “ … the Fertile Crescent includes a high percentage of selfers – that is plants that usually pollinate themselves ….” [einkorn wheat, emmer wheat, barley]

Animals that could be Domesticated: “ …. its wealth in ancestors not only of valuable crops but also of domesticated big animals ….” [goats, sheep, pigs, cows]

Little competition from Hunting-Gathering: “ A final advantage of early food production in the Fertile Crescent is that it may have faced less competition from the hunter-gatherer lifestyle than in some other areas ….” [gazelle hunted and rapidly killed off]

[2] Ecological Constraints on Agriculture in the Tropics

Landes, The Wealth and Poverty of Nations

(1) climate – “in cold, northern winters, some animals simply curl up and hibernate; in hot, shadeless deserts, lizards and serpents seek the cool under rocks or under the earth itself …. in general the discomfort of heat exceeds that of cold …. damp, ‘sweaty’ climes reduce the cooling effect of perspiration … the real cooling effect will be canceled by the heat produced by the motor activity …. the easiest way to [combat these conditions] is not to generate heat; in other words, keep still and don’t work.”

(2) Insects and Parasites – “Heat … encourages the proliferation of life forms hostile to man. Insects swarm as the temperature rises, and parasites within them mature and breed more rapidly ….”

Examples: (2a) snail fever (schistosomiasis)(2b) sleeping fever (trypanosomiasis) – tsete fly transmitting vector

Gallop and Sachs

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(1) humid areas – humid tropical soils are low in nutrients and organic matter, susceptible to erosion and acidification

(2) arid areas – lack of irrigation due to flatness of river valleys(3) temperate countries – spend much more per agricultural worker

on research, mainly focus on their own domestic agricultural issues

B.3 Surplus Labor in the Agricultural Sector

[1] The Fei-Ranis Surplus Labor Model

Agricultural production function – surplus land and surplus labor at the extremes

Average and marginal productivity of farm labor initially wages in agriculture = average product of farm labor = wage in non-agriculture (e.g.: manufacturing, craft production)

First turning point – end of pure surplus labor in agriculture Second turning point – commercialization Surplus from agriculture that can be taxed away by governments,

used to create infrastructure promoting manufacturing

[2] Problems with the Labor Surplus Model: Analysis of Contribution of Workers and Hours Worked to Agricultural Farm Output in Japan, Circa 1930

Cobb-Douglas production function estimates Findings – workers “redundant”, hours not redundant Female textile worker wages and rural wage floor

B.4 Is an Agricultural Revolution a Prerequisite for Industrialization?

[I] Calculations by Bairoch

[II] How Did Early Industrializing Japan Achieve Balanced Growth, Agriculture

Expanding Simultaneously with Western Style Manufacturing?

The pre-1870 legacy: advanced productivity levels in some districts, extensive proto-industry activity in rural areas

Diffusion of best practice pre-1870 techniques – the importance of government and the landlord elite

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II.A Pre-1870 Japan: How and why did it Achieve Fairly High Levels of Agricultural Productivity, Especially in the Southwest?

[i] Different from Europe during period of expansion

European Model: Globalization and agricultural improvements, Enclosure and the Decline of Feudalism

Different climatic zones on Eurasian land mass – hydraulic societies in Asia different from non-hydraulic societies – water as a common-pool resource

Europe introduced new crops for Americas; proto-industry mainly developed in urban sector, growing in part because of burgeoning global trade; Europe in the Americas, the Indian Ocean and the South China Sea

Feudalism gives way to enclosure and the rise of the bourgeoisie in the European model

[ii] Japan: Autarky and Diffusion of Proto-industrialization to the Countryside

Japan – autarky regime from 1650s until 1850s – closed not open like Europe

Nature of bakuhan system (“feudal” of a sort, reasons for isolation, demilitarization of countryside): (1) infrastructure (roads, canalized rivers, castle towns and urbanization); (2) extending irrigation ditches, solving “tragedy of the commons” in water management; (3) proto-industry in cities initially, putting-out system; (4) spread of proto-industry to countryside, tax avoidance, eventual de-urbanization, solving “tragedy of the commons” problem in forest management.

B.5 How Important is Land Reform?

[1] Importance of developing managerial skills in agriculture before carrying out land reform

Problems in Latin America with latifundia

Share-cropping and tenancy in prewar Japan; attempts at land reform prior to World War I – reasons for relatively successful land reform under American occupation

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Land reforms in South Korea and Taiwan

China – peasant base for Communist party rule; collectivization and its problems; limited privatization prior to big industrialization drive of 1980s

[2] Importance of withdrawing labor from agriculture as a way of easing land reform – influence of industrialization and the demographic transition in fertility

Japan – 1955s and 1960s; spread of part-time farming/part-time factory work

China – younger generation working in cities at factory jobs; sending remittances back to countryside

Problems in Latin America when industrial sector does not grow quickly

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Table 6

Population, Education and Human Development in China and Japan, 1640-2004

A Population Size and Dynamics

A.1 Estimates of China’s Population Size by Maddison, Various Indices, and Alternative Official Estimates (for the Period 1750-1850), 1640-2000

Year

Maddison EstimatesAlternative

Official Estimate

Number (1000s)

Index (1950 = 100)

Index (1760 = 100)

Index (1640 = 100)

1650 123,000 22.5 44.8 94.6 -1700 138,000 25.2 50.3 106.2 -1750 260,000 47.6 94.7 200.0 179,5391800 341,600 62.5 124.4 262.8 295,2731850 412,000 75.4 150.0 316.9 429,9311860 377,000 69.0 137.3 290.0 -1870 358,000 65.5 130.4 275.4 -1880 368,000 67.3 134.0 283.1 -1890 380,000 69.5 138.4 292.3 -1900 400,000 73.2 145.7 307.7 -1910 423,000 77.4 154.0 325.4 -1920 472,000 86.3 171.9 363.1 -1930 489,000 89.4 178.1 376.2 -1940 518,770 94.9 188.9 399.1 -1950 546,815 100.0 199.1 420.6 -1960 667,070 122.0 242.9 513.1 -1970 818,315 149.7 298.0 629.5 -1980 981,235 179.5 357.3 754.8 -1990 1,135,185 207.6 413.4 873.2 -2000 1,275,392 233.2 464.5 981.1 -

A.2 Population Totals (P), Birth (b) and Death Rates (d) per thousand population, the Natural Rate of Increase (nri = b – d), and Urbanization (u%), China, 1950-84

Period P (1,000s) b d nri u%1950-54 570,328 37.3 16.7 20.6 12.1 %

24

1955-59 644,294 30.5 12.2 18.3 15.61960-64 677,974 31.7 14.3 17.4 18.31965-69 765,306 35.2 8.6 26.7 17.71970-74 870,816 29.3 7.4 21.9 17.21975-79 949,824 19.6 6.8 12.8 17.81980-84 1,012,576 19.1 6.6 12.5 20.8

2000 n.e. n.e n.e n.e 36.2

Table 6 [Continued]

A.3 Life Expectancy for Males (LFM) and Females (LFF), Infant Mortality Rate for Males (imrm) and Females (imrf), Total Fertility Rate (TFR), and Mean

Household Size (MHS), China, 1929/31-2000Date(s) LEM LFF Imrm imrf TFR MHS1929-31 25.0 24.0 n.e. n.e. n.e. n.e.

1950 42.2 45.6 145.9 130.2 n.e. n.e.1955 n.e. n.e. n.e. n.e. 6.3 n.e.1960 n.e. n.e. n.e. n.e. 4.0 n.e.1982 66.5 69.4 36.5 34.5 2.9 4.411990 66.9 71.0 32.2 36.8 2.3 3.962000 71.0 74.8 20.8 29.2 1.6 3.44

A.4 Infant Mortality Rate (imr), Life Expectancy for Males (LEM) and for Females (LEF), Gross Reproduction Rate (grr) and Net Reproduction Rate (nrr),

Japan, 1891/95 – 1996/2000Period imr LEM LEF grr nrr

1891-95 - 42.8 44.3 - -.1901-05 152.0 43.9 44.9 - -.1911-15 156.7 44.3 44.7 - -.1921-25 159.3 42.3 43.2 n.e. n.e.1926-30 136.6 44.8 46.5 n.e. n.e.1931-35 120.4 46.9 49.9 n.e. n.e.1946-50 65.3 54.8 58.4 2.06 1.691951-55 48.0 63.6 67.8 1.34 1.201956-60 35.9 65.3 70.2 1.01 0.951961-65 23.4 67.7 72.9 0.98 0.951966-70 15.4 69.3 74.7 0.99 0.961971-75 11.2 71.7 76.9 1.01 0.981976-80 8.4 73.4 78.7 0.87 0.861981-85 6.3 74.8 80.5 0.87 0.851986-90 4.8 75.9 81.9 0.80 0.791991-95 4.3 76.4 82.9 0.72 0.71

25

1996-2000 3.5 77.7 84.6 0.67 0.67

Table 6 [Continued]

A.5 Population (P) and an Index for Population with 1950 = 100 (INDP), Birth (b) and Death Rates (d), the Natural Rate of Increase (nri), Urbanization (u%),

Proportion of Population in the Six Big Cities (b6c%), Japan, 1600-2000Period/Year P

(1,000s)INDP b d nri u% b6c%

1600 12,000 14.3 - - - - -1650 17,180 20.4 - - - - -1700 27,690 32.9 - - - - -1720 31,280 37.2 - - - - -1730 32,080 38.1 - - - - -1750 31,100 37.0 - - - - -1800 30,650 36.4 - - - - -1850 32,280 38.4 - - - - -1872 33,110 39.4 - - - - -

1886-90 39,130 46.5 28.8 20.8 8.0 - -1891-95 40,864 48.6 29.0 21.4 7.6 - -

1896-1900 42,906 51.0 31.7 21.1 10.5 12.4 n.e.1901-05 45,525 54.1 32.5 21.0 11.5 15.0 n.e.1906-10 48,031 57.1 33.6 21.5 12.1 17.3 n.e.1911-15 51,305 61.0 34.5 20.7 13.9 17.5 n.e.1916-20 54,673 65.0 33.7 24.1 9.6 18.9 9.81921-25 58158 69.1 34.7 21.9 12.8 21.6 11.11926-30 62,581 74.4 33.4 19.3 14.1 24.0 11.81931-35 67,377 80.1 31.6 17.9 13.7 33.0 18.31936-40 71,014 84.4 28.8 17.3 11.5 38.3 20.01941-45 73,116 86.9 31.2 16.3 14.9 n.e. n.e.1946-50 79,948 95.1 32.2 12.3 20.0 35.3 11.91951-55 80,065 95.2 21.9 8.7 13.2 56.3 15.91956-60 91,962 109.3 17.7 7.7 9.9 63.5 16.51961-65 96,403 114.6 17.5 7.2 10.3 68.1 17.31966-70 101,553 120.7 17.8 6.8 11.0 72.2 18.11971-75 109,062 129.7 18.7 6.5 12.2 75.9 16.91976-80 115,133 136.9 14.9 6.1 8.7 76.2 16.01981-85 119,342 141.9 12.6 6.2 6.4 76.7 15.71986-90 122,692 145.9 10.7 6.4 4.3 77.4 15.51991-95 124,888 148.5 9.8 7.0 2.7 77.4 15.0

26

1996-2000 126,216 150.0 9.5 7.5 2.0 78.7 15.2

Table 6 [Continued]

A.6 The Pace of the Demographic Transition in Japan, 1930-1960: Values of Age Standardized Death Rates (asdr), Infant Mortality Rates (imr), and the Hutterite

Index of Marital Fertility (Ig) for the Prefectures of Japan Classified by Percentage of Male Labor Force Engaged in Primary Industry in 1930 (pmlpi)

Mortalitypmlpi Age Standardized Death Rate (asdr) Infant Mortality (imr)

1908 1930 1950 1960 1920 1960Under 30 %

2572 1897 1075 712 184 24

30%-49% 2213 1921 1131 848 161 3250%-54% 2404 1969 1184 765 169 3555%-59% 2119 1825 1145 755 158 3460% and

over2065 1985 1277 815 163 38

Fertility (Ig)pmlpi Rural Urban

1930 1950 1960 1930 1950 1960Under 30 %

0.52 0.50 0.30 0.43 0.44 0.28

30%-49% 0.54 0.50 0.29 0.43 0.45 0.2850%-54% 0.57 0.50 0.28 0.46 0.44 0.2855%-59% 0.58 0.53 0.30 0.48 0.45 0.2860% and

over0.60 0.56 0.42 0.50 0.49 0.29

B The Biological Standard of Living and the Human Development Index

B.1 Male Standing Height (msh) at Ages 6, 12 and 18 and Estimates of the Human Development Index (HDI), Japan, 1901-2000

Male Standing Height (msh) at Ages: Human Development IndexPeriod 6 12 18 Year HDI

1901-10 106.7 133.6 159.2 1910 0.611911-20 106.9 134.4 160.8 1920 0.641921-30 107.7 136.2 161.6 1930 0.651931-40 108.8 138.2 162.9 1940 0.70

27

1941-50 108.5 138.2 162.9 1950 0.691951-60 110.3 139.3 165.0 1960 0.751961-70 113.4 144.9 157.7 1970 0.831971-80 115.3 148.6 169.0 1980 0.891981-90 116.4 150.4 170.6 1990 0.90

1990-2000 116.8 152.2 171.1 2000 0.92

Table 6 [Continued]

C Education

C.1 Average Years of Schooling in China and Japan (Years of Education per Person Aged 15-64) and the Ratio (Japan/China), 1950-1992

Year China Japan Japan/China1950 1.60 9.11 5.691973 4.09 12.09 2.961992 8.50 14.86 1.75

C.2 Indices (1960 = 100) for the Number of Senior and Junior Middle Schools in Cities, Towns, and Rural Districts, China, 1964-78

Period Senior Middle Schools Junior Middle SchoolsCities Towns Rural Cities Towns Rural

1964-65 99.3 100.0 100.0 105.2 94.5 94.41971-75 328.7 175.1 3,369.7 91.3 104.6 701.91976-78 540.6 277.3 7,483.9 77.9 133.1 1,250.9

C.3 Years of Schooling Completed (SCY) and Estimated Rates of Return on Schooling: High School to College (COLR), High School to Technical School

(TECR), Junior High to High School (HSR) and Primary to Junior High (JHR): Urban China, 1988-2001

Period SCY Estimated Rates of ReturnCOLR TECR HSR JHR

1988-89 4.3 13.3 % 4.5 % 11.3 % 15.6 %1990-94 5.2 20.3 9.9 11.4 14.21995-99 7.6 28.4 13.6 17.1 14.32000-01 10.2 38.0 17.0 21.0 15.1

C.4 Estimated Rates of Return to Schooling by Ownership Sector, China, 1988-2001

Period State Sector Urban CollectiveEnterprises

Non-publicEnterprises

1988-89 3.4 % 4.6 % 8.4 %

28

1990-94 4.3 4.1 9.41995-99 6.6 6.4 10.62000-01 8.8 8.0 11.6

Table 6 [Continued]

C.5 Advancement Rates from One Level to the Next Higher, China, 1980-99

Period

From Primary to

JuniorSecondary

From Higher Secondary Schooling to Institutions of Higher Education

From General

Secondary

[1]

From Technical Secondary, Teaching

Training Secondary and Vocational Training

Secondary[2]

Total

[1] +{2]

1980-84 68.3 % 12.4 % 9.9 % 22.3 %1985-89 68.9 26.6 17.6 44.31990-94 78.3 34.0 19.3 53.31995-99 89.6 48.4 22.5 22.5

From Junior Secondary to Higher Secondary

Period To General Secondary

To Other Higher Secondary

TotalTechnicalSecondary

Teaching Training

Secondary

Vocational Training

Secondary1980-84 30.0 % 2.7 % 1.9 % 5.5 % 40. 1 %1985-89 23.1 4.5 2.1 10.6 40.21990-94 21.5 6.2 2.3 13.4 43.41995-99 22.9 8.8 2.2 14.2 48.1

C.6 School Enrollment Rates for Children Aged 12-18 in China, 1989 and 2000Age (Group) 1989 2000

Male Female Male Female12-13 93.1 % 92.7 % 96.8 % 92.2 %14-15 77.4 68.9 84.9 82.916-17 38.3 31.2 64.7 57.9

18 17.2 16.1 34.5 40.0

29

Table 6 [Continued]

C.7 Growth in the Number of Teachers and the Number of Students in Various Types of Schools, Japan, 1886-1940

Type of School

Teachers Students1886-1900

1901-20 1921-40 1886-1900

1901-20 1921-40

Elementary 0.1 % 4.0 % 2.4 % 2.4 % 3.6 % 2.0 %Middle (Male)

12.7 6.0 19.4 17.5 5.8 5.3

Middle(Female)

19.4 20.2 7.3 40.7 21.1 8.9

High School(Male)

28.7 1.3 8.7 18.1 2.2 6.2

University 2.9 9.9 13.5 6.9 9.0 15.0Vocational(Regular)

23.3 13.4 8.0 31.0 15.0 9.2

Vocational(Continuance)

n.e. 24.5 24.5 n.e. 59.9 6.3

C.8 Estimates of the Demand and Supply of Engineers in Japan, 1891-1940

Period

Supply: Students of Higher Education in Science and

Engineering Estimated Growth in Demand (a)

EstimatedDemand

Growth minus Supply Growth

Percentage of All Higher Education Students

Estimated Growth Rate of

Graduates in Science and Engineering

1891-95 15.8 % -13.7 % 20.5 % +34.21896-1900 10.9 3.1 4.3 +10.51900-05 7.7 12.1 14.4 -5.71906-10 7.8 17.6 16.9 -8.81911-15 10.2 11.5 13.3 -4.51916-20 13.1 10.1 16.1 -1.71921-25 14.2 17.3 11.4 -11.2

30

1926-30 15.7 2.1 7.1 -0.11931-35 11.8 8.3 6.1 -8.11936-40 14.3 3.7 13.9 +4.3

Table 6 [Continued]

C.9 Enrollment Rate for Compulsory Schooling (COENR), and Advancement Rates: From Upper Secondary Schools to High Schools (HSAD); From High Schools to Universities (UNAD); From High Schools to Junior Colleges (JCAD); and From

High Schools to Universities or Junior Colleges (UNJCAD), Japan, 1950-2004Period COENR Advancement Rates

HSAD UNAD JCAD UNJCAD1950-54 99.7 % 47.0 % 7.9 % 2.1 % 10.0 %1955-59 99.8 52.7 8.3 2.1 10.41960-64 99.8 64.0 11.0 3.1 14.11965-69 99.8 74.7 13.3 5.0 18.31970-74 99.9 86.9 21.3 8.3 29.61975-79 99.9 93.0 26.8 11.3 38.11980-84 100.0 94.1 25.3 11.0 36.21985-89 100.0 93.9 24.9 11.4 36.31990-94 100.0 95.0 26.9 12.5 39.41995-99 100.0 95.9 35.0 12.2 47.22000-04 100.0 96.0 40.8 8.3 49.0

Notes: n.e. = not estimated.

(a) Growth in demand for engineers is based on combining growth in the number of employees in railroads and public utilities with the growth in prime mover horsepower installed in manufacturing.

Sources: Panel A.1 from page 169 of Maddison (1998) and from pages 281-82 of Ho (1959). Panel A.1 from page 15 of Poston and Yaukey (1992) and from page 138 of Wang and Mason (2008). Panel A.3 from page 295 of Bramall (2009), from page 228 of Poston and Yaukey (1992) and from page 138 of Wang and Mason. Panel A.4 from pages 357-8 in Mosk (2008). Panel A.5 from page 38 of Miyamoto (2004) and page 357 in Mosk (2008). Panel A.6 from page 296 in Mosk (2008). Panel B.1 from page 366 in Mosk (2008). Panel C.1 from page 63 in Maddison (1998). Panel C.2 from page 188 in Bramell (2009). Panel C.3 from page 186 in

31

Cai, Park and Zhao (2008). Panel C.4 from page 207 in Cai, Park, and Zhao (2008). Panel C.5 from page 231 in Hannum, Behrman, Wang and Liu (2008). Panel C.6 from page 236 in Hannum, Behrman, Wang and Liu (2008). Panel C.7 from pages 46-7 in Mosk (1995). Panel C.8 from page 83 in Mosk (1995). Panel C.9 from Japan. Ministry of Internal Affairs and Communications and Statistical Research and Training Institute (2009).

Withdrawing Labor From the Agricultural Sector

QA = A f(L*, K*, LA*)

Where A is an index of total factor productivity andL* = augmented labor (service flow); K* = augmented capital (service

flow) and LA* = augmented land (service flow)

L* (Augmented labor)

L* = h e(h) W where h = average hours worked per worker; e(h) efficiency of an hour worked per worker; and W = number of workers

To release W from the agricultural sector:

(1) increase h; (2) increase e(h) – e(h) depends upon educational level and

health of workers in farming and upon incentives

or augment land or augment labor through mechanization or both

LA* (Augmented Land)

Augment land through (1) irrigation; (2) fertilizer; and (3) new seed varieties (e.g.: Green Revolution Modern Varieties of rice)

From Land Augmenting to Labor Augmenting Productivity Advance

32

When the ratio of wages to land rents is low (w/rLA) augment the inelastically supplied, scarce factor of production, namely land; when the ratio of wages to land rents rises, gradually switch to augmenting labor by increasing the input of fixed capital (e.g.: mechanization).

Table 7

Labor Force Supply and Demand in China and Japan, 1880-2004

A Japan

A.1 Workdays per Worker (wdpw) and per Male Equivalent Worker (wdpmew) in Japanese Agriculture, 1880-1940

Item 1880 1900 1920 1930 1940wdpw 113 131 163 151 163

wdpmew 131 150 187 173 192

A.2 Means and Standard Deviations for Hours Worked per Worker Unit (HPW) and for Consumption per Consumer Unit (CPC) in Yen for Farm Households in

Japan Surveyed in 1929: Classified by the Ratio of Consumer Units to Worker Units (C/W) and by the Number of Worker Units per Cultivated Land Area (W/CL)

GroupHPW CPC

Mean Standard Deviation

Mean Standard Deviation

Classified by the C/W RatioC/W < 1.1 3020 988 267 107

1.1 < C/W < 1.2

3092 1127 230 69

1.2 < C/W < 1.3

2947 642 230 69

1.3 < C/W < 1.4

3177 977 204 57

1.4 < C/W < 1.6

3369 922 212 94

1.6 < C/W 3650 1043 187 61All families 3170 959 219 81

Classified by W/CL RatioW/CL < .015 3329 1094 264 110

.015 < W/CL < .02

3296 905 213 68

.02 < W/CL < 3243 970 233 94

33

.025.025 < W/CL <

.033203 983 215 67

.03 < W/CL < .035

2896 796 214 74

.035 < W/CL < .04

3299 1460 201 69

.04 < W/CL 2779 767 177 54

Table 7 [Continued]

A.3 Real Daily Wages: Nominal Wages Deflated by the Consumer Price Index (CPI), 1934-36 = 1, and Wage Differentials, Japan, 1885-1914

PeriodReal Daily Wages Wage Differential:

Manufacturing/AgricultureAgriculture ManufacturingMales Females Males Females Males Females

1885-89 0.73 0.48 0.86 0.39 1.18 0.811890-94 0.87 0.59 0.80 0.40 0.92 0.681895-99 0.96 0.71 0.82 0.40 0.85 0.561900-04 0.91 0.70 0.91 0.42 1.00 0.601905-09 0.82 0.66 0.89 0.41 1.09 0.621910-14 0.88 0.67 0.90 0.44 1.02 0.66

A.4 Nominal Daily Wages (Yen) Deflated by Price Index for the Sector (1934-36 = 1), Japan, 1885-1914

PeriodAgriculture Manufacturing

Males Females Males Females1885-89 0.65 0.42 0.51 0.231890-94 0.67 0.45 0.50 0.251895-99 0.75 0.55 0.54 0.261900-04 0.77 0.59 0.62 0.281905-09 0.72 0.58 0.60 0.331910-14 0.77 0.59 0.67 0.32

A.5 Nominal Daily Wages (w), Nominal Labor Productivity (q) and Labor’s Share in Value Added (S%), Japan, 1895-1914: Cotton Spinning and Cotton

Weaving

PeriodCotton Spinning Cotton Weaving

Wages (w) q S% Wages (w) q S%Male Female

1895-9 0.22 0.14 0.63 25.7 % 0.24 0.13 1.53 9.8 %1900-4 0.34 0.21 0.51 46.6 0.37 0.22 1.32 18.2

34

1905-9 0.43 0.26 0.92 32.1 0.44 0.27 1.06 27.61910-4 0.49 0.31 0.88 39.8 0.53 0.34 1.90 19.2

Table 7 [Continued]

A.6 Percentage Shares of the Labor Force in Three Broad Sectors of the Economy (P = Primary, S = Secondary, and T = Tertiary) and Relative Labor Productivity in the Sector (Calculated as Percentage of GDP in the Sector Divided by Percentage of

Labor Force in the Sector, Times 100), Japan, 1951-2000Period Percentage of the Labor Force in: Relative Labor Productivity in:

P S T P S T1951-55 38.5 % 24.5 % 37.0 47.9 141.3 126.81956-60 32.9 26.7 40.4 45.2 142.0 117.01961-65 26.2 30.9 42.9 40.5 132.6 112.91966-70 19.8 33.8 46.3 39.1 121.4 110.51971-75 13.9 35.9 50.0 38.9 115.6 106.41976-80 11.5 34.7 53.6 38.7 109.5 107.41981-85 9.3 34.3 56.1 34.8 107.1 107.01986-90 7.9 33.6 58.0 33.2 106.6 106.01991-95 6.1 33.6 59.9 32.8 97.1 109.1

1996-2000 5.3 31.7 62.5 28.4 91.7 111.0

B China

B.1 Percentage of Population of China in Agriculture and Non-Agriculture, 1933: Working, Students, Elderly or Unemployed and IdleCategory Percentage of Total Population (or

Percentage of Category if Noted)Agricultural

Agricultural 73.00 %Working in Agriculture 42.46

Working Only in Agriculture 23.76Children Under Age 7 14.24

Students 1.02Persons Over Age 65 2.20Unemployed or Idle 13.07 % (17.90 % of Agricultural

Population)Non-Agriculture

35

Working Ages 7 – 64 27.0Working in Factories 0.2 %

Working in Handicrafts 2.4Children Under Age 7 5.3

Students Age 7 and Over 1.15Unemployed or Idle 10.39 % (38.48 % of Non-Agricultural

Population)

Table 7 [Continued]

B.2 Percentage of China’s Labor Force in Three Broad Sectors of the Economy (A = Agriculture or Primary, I = Industry or Secondary, and S = Services or

Tertiary) and Relative Labor Productivity in the Sector, 1952-2000 (b)

Year Percentage of the Labor Force in; Relative Labor Productivity in:A I S A I S

1952 84.0 % 7.0 % 9.0 % 59.5 300.0 322.21970 81.0 10.0 9.0 49.4 460.0 144.41980 69.0 18.0 13.0 43.5 272.2 161.51985 62.0 21.0 17.0 45.2 204.8 170.61990 60.0 21.0 19.0 45.0 200.0 163.21995 52.0 23.0 25.0 38.5 213.0 124.02000 50.0 51.0 27.5 32.0 226.7 120.0

B.3 Percentage of Employed Labor Force in China in Primary (P), Secondary (S) and Tertiary (T) Sectors of the Economy; Percentage of the Employed Labor Force

That is Urban (U) or Rural (R); and Percentage of the Employed Urban Labor Force in State Owned Enterprises (USOE), 1978-2004

PeriodPercentage of the Employed Labor Force in: SOE % of

Urban Labor

P S T U R

1978-89 70.2 % 17.5 % 12.4 % - - -1980-84 67.2 18.5 14.3 - - -1985-89 60.5 21.8 17.7 - - -1990-94 57.8 21.9 20.3 27.0 % 73.0 % 60.5 %1995-99 50.5 23.3 26.2 29.7 70.3 49.72000-04 49.2 22.1 28.7 33.6 66.4 29.6

Notes: See the heading in Panel A.6 above for the method of computing labor productivity in the sectors. Basically the A sector in Panel B.2 corresponds to the P sector in Panel A.6; the I sector in Panel B.2 corresponds to the S sector in Panel A.6; and the S sector in Panel B.2 corresponds to the T

36

sector in Panel A.6. However these correspondences may not be exact.

Sources: Panel A.1 from page 61 of Mosk (1995). Panel A.2 from varioustables in Mosk (1983). Panels A.3 – A.5 from page 113 in Mosk (2008). Panel A.6 from page 359 in Mosk (2008). Panel B.1 from pages 10-1 in Feuerwerker (1977). Panel B.2 from page 272 in Bramall and page 482 of Huang, Otsuka, and Rozelle (2008). Panel B.3 from page 168 in Cai, Park and Zhao (2008).

Table 8

Agriculture in China and Japan, 1400-2006

A Land Use Patterns, Circa 1993

Country Land area(000 ha)

Arable land & permanent

crop area

Proportion Arable

(%)

Population(000s)

Arable Land per head of population

A.1 Eurasian Regions with Long-standing Settled AgricultureChina 959,696 95,975 10.0 % 1,178,440 .08Europe 487,696 135,705 27.8 506,910 .26India 328,759 169,650 51.6 899,000 .19Japan 37,780 4,463 11.8 124,753 .04

A.2 Countries of SettlementUnited States

980,943 187,776 19.1 293,172 .73

Canada 997,614 45,500 4.6 28,386 1.58Australia 771,336 46,486 6.0 17,769 2.62

Brazil 851,197 48,955 5.8 158,913 .31

B Agriculture in Japan, 1910-2004

B. 1 Indices (1960-64 = 100)

Period Arable Land Area (IALA)

Paddy FieldsActuallyPlanted(IPP)

Farm Households

(IFH)

Adult Farm HouseholdMembers

Fully Engaged in

Farming(IFW) (a)

Rice Output(IRO)

1910-19 95.9 91.8 93.1 n.a. 63.61920-29 98.5 95.3 93.3 n.a. 69.51930-39 98.6 97.0 94.0 n.a. 74.31940-44 95.8 94.3 n.a. n.a. 71.71955-59 96.7 98.9 n.a. n.a. 93.0

37

1960-64 100.0 100.0 100.0 100.0 100.01965-69 97.8 99.4 93.4 79.2 106.91970-74 93.9 82.8 89.1 66.3 94.11975-79 90.9 81.2 82.9 55.5 98.31980-84 89.4 70.0 78.2 51.6 82.51985-89 87.9 67.0 73.4 49.9 85.11990-94 85.1 64.4 49.4 38.2 79.31995-99 81.6 58.7 43.9 32.6 77.32000-04 78.6 51.9 38.5 31.3 69.0

Table 8 [Continued]

B.2 Relative Indices, Percentage of Arable Land in Paddy (ALP%) and Adult Farm Household Members Fully Engaged in Farming per Farm Household

(FWPFH)

Period

Relative Indices (in Rice Production)

ALP% FWPHLand

Productivity(IRO/IPP)

Farm Household

Productivity(IRO/IFH)

Adult Farm Worker

Productivity(IRO/IFW)

1910-19 69.3 68.0 n.a. 50.5 % n.a.1920-29 72.8 73.0 n.a. 51.1 n.a.1930-39 76.6 77.7 n.a. 53.8 n.a.1940-44 n.a. n.a. n.a. 53.9 n.a.1955-59 n.a. n.a. n.a. 55.3 n.a.1960-64 100.0 100.0 100.8 55.9 1.91965-69 107.5 114.6 135.6 57.5 1.61970-74 113.7 105.7 143.1 58.2 1.41975-79 121.1 118.6 177.3 56.7 1.31980-84 117.9 105.6 160.1 55.5 1.31985-89 127.1 116.0 170.5 54.6 1.31990-94 123.0 160.8 209.3 54.3 1.51995-99 131.8 176.0 237.1 54.6 1.42000-04 132.8 179.3 220.5 54.7 1.6

B.3 Percentage Growth Rate for Inputs (Labor)

PeriodNumber of Workers Workdays

Male Female Total Per Worker1935-45 -1.7 2.0 -0.9 -1.01945-55 1.5 0.3 1.3 0.41955-65 -3.5 -2.5 -2.7 0.3

B.4 Percentage Growth for Inputs (Variable and Fixed Capital)

38

PeriodFixed Capital

Variable Capital(Current Inputs)

Machinery &Implements Total Fertilizers Total

1935-45 -0.2 -1.4 -5.0 -6.61945-55 3.1 2.0 13.5 15.01955-65 11.5 7.8 3.6 8.5

Table 8 [Continued]

B.5 Percentage Growth Rates of Relative Prices for Inputs Relative to Agricultural Output Price

Period

Labor and Land Fixed Capital Variable Capital(Current Inputs)

LaborWages

CultivatedLand Prices

Machinery &

ImplementsTotal Fertilizer Total

1920-30 1.9 2.9 0.3 1.3 -1.7 -1.21955-65 6.1 4.3 -3.2 -0.9 -5.0 -4.51960-70 7.2 -1.1 -7.1 -1.1 -5.4 -5.0

B.6 Percentage Growth Rates of Productivities of Labor and Land

Period Labor Productivity Land Productivity

Relative Contribution to Labor Productivity

Growth of Land Productivity Growth

(%)

Per Male Equivalent

(1)

Per Workday

(2))

Per Paddy-field

equivalent(3)

Per Hectare ofCrop Area

(4)

(3)/(1) (4)/(2)

1935-45 -1.7 -0.9 -1.5 -0.7 88 % 78 %1945-55 2.2 1.9 2.9 2.1 132 1111955-65 6.9 6.5 3.4 4.3 49 66

C Agriculture in China, 1400-2006

C.1 Growth Accounting for Growth in China’s Grain Ouput, 1400-1957(Assuming a Constant Level of Per Capita Grain Consumption)

PeriodAnnual Compound Growth Rates Share of

Total FactorProductivity

Output Labor Land Capital Total FactorProductivity

39

1400-1770

0.32 % 0.19 % 0.05 % 0.06 % 0.01 % 4 %

1700-1850

0.59 0.35 0.06 0.05 0.12 21

1850-1957

0.45 0.27 0.06 0.07 0.04 10

Table 8 [Continued]

C.2 Indices (1950-54 = 100) for Agricultural Output and Grain Consumption, 1950-78

Item 1950-56 1957-63 1964-78Sown Area

Grain 102.5 100.8 98.2Cotton 105.1 94.8 97.0

Yield per HectareGrain 103.5 106.3 160.7Cotton 105.6 125.6 217.1

Grain Output, Population, and Per Capita OutputGrain Output 106.4 107.3 157.8Population (b) 102.3 116.1 146.5

Per Capita Output 103.8 92.6 107.3

C.3 Value Added (in 1987 Yuan)Item 1933 1952 1957 1978 1995

Per Head 277 225 241 235 439Per Worker 789 748 812 781 1591Per Hectare Cultivated

1353 1185 1374 2265 5563

C.4 Indices (1955 = 100) for Fertilizer Output, Fertilizer Consumption, and Fertilizer Imports (Tons)

Item 1955-59 1960-64 1965-66Output 286.9 690.1 1345.6

Consumption 172.4 306.8 617.5Imports 127.5 156.8 332.6

C.5 Growth Rates for Value Added and Tons of Grain Produced

Period Value Added (1980 Prices)Value Added (Comparable Tons of Grain

40

Prices)Farming AgricultureCollective Farming

1955-81 2.8 % 3.2 % 2.6 % 2.8 %1963-81 3.3 3.6 2.9 3.5

Family Farming1981-2006 4.5 5.6 4.2 1.31984-2006 4.3 5.5 3.9 1.0

Table 8 [Continued]

C.6 Growth Rates of Farm Output, Input, and Total Factor ProductivityItem 1952-57 1957-78 1978-87 1987-94

Gross Farm Output

3.70 % 2.32 % 5.77 % 4.28 %

Farm Gross Value Added

3.05 1.72 5.52 3.62

Farm Inputs 6.36 2.54 4.35 4.83Non-Farm

Inputs12.12 8.98 8.43 6.67

Farm Employment

1.35 1.92 0.49 0.58

Farm Labor Productivity

1.66 -0.19 4.99 3.05

Irrigated Area Cultivated

6.46 2.41 -0.16 1.32

Non-irrigated Land Cultivated

-0.79 -2.08 -0.6 -1.49

Augmented Land

1.79 0.18 -0.32 0.34

Other Capital 7.81 4.43 5.00 3.48Total Factor Productivity

0.63 0.57 4.56 2.67

C.7 Indices for Industrial Inputs into China’s Rural Economy (1965=100)Item 1962-64 1970-74 1975-78

Kilowatts of Power 64.6 300.0 646.9Millions of Tons of Chemical Fertilizer

54.8 264.0 399.6

Cement (Millions of Tons)

37.7 311.1 575.9

Irrigation/DrainageEquipment

69.2 270.0 572.1

Tractors 75.8 328.2 704.6

41

Power Tillers n.e 273.3 1222.2Total Horsepower

per Cultivated Hectare

76.7 310.0 692.5

Table 8 [Continued]

C.8 Growth Rates for Agricultural GDP and Value Added Produced in Various Sub-sectors of Agriculture, 1970-2000

Item 1970-78Reform Period

1978-84 1985-95 1996-2000GDP 4.9 % 8.8 % 3.8 % 4.2 %Grain 2.8 4.7 1.7 0.03Rice 2.5 4.5 0.6 0.3

Wheat 7.0 8.3 1.9 -0.4Total Cash Crop Area

Sown2.4 5.1 2.1 -0.4

Cotton -0.4 19.3 -0.3 -1.9Meat (pork,

beef, poultry) 4.4 9.1 8.8 6.5Fishery 5.0 7.9 13.7 10.2

Notes: (a) Farm household members aged 15 and over who work full time in farm production.

(b) The population estimates used here are those appearing in Maddison (2006: pg. 292).

n.e. = not estimated.

Sources: Panel A data from page 28 of Maddison (1998). Panel B.1 and Panel B.2 data from various tables in Japan. Ministry of Internal Affairs and Communications and Statistical Research and Training Institute (2009). Panel B.3 – Panel B.6 data from pages 248-9 in Mosk (2008). Panels C.1 and C.4 from pages 74 and 82 in Perkins (1969). Panels C.2 and C.8 from

42

pages 472 and 479 in Huang, Otsuka and Rozelle (2008). Panels C.3 and C.6 from pages 71 and 75 in Maddison (1998). Panel C.5 from page 228 in Bramall (2009). Panel C.7 from pages 80-1 in Rawski (1979).

Table 9: Pressure on Arable Land and Incidence of Landlord/Tenancy Disputes, Japan, 1925-1940

Prefecture/Region

Arable Land per Farm Households (Hectares)

PercentageChange

in Numberof Farm

Households

Percentage of Landlord/Tenant Disputes in

Region1925 1940 Percentage

Change,1925/40

1917-31

1932-41

Change in Percentage(Absolute)

Japan 1.08 1.09 +1.4 % -1.2 % 100 % 100 % 0

Hokkaido 4.6 5.3 +17.0 +5.8 2 5.6 + 3.6

Tohoku 8 25.8 + 17.8Aomori 1.5 1.5 - 5.0 + 16.8Iwate 1.4 1.3 - 8.4 + 12.8

Miyagi 1.4 1.4 + 1.5 + 10. 3Akita 1.5 1.5 - 4.4 + 9.9

Yamagata 1.4 1.4 - 4.7 + 11.8Fukushima 1.4 1.4 - 2.6 + 4.5

Kanto 10.3 12.8 + 2.5Ibaraki 1.2 1.2 - 0.6 + 2.2Tochigi 1.3 1.3 - 2.7 + 9.4Gumma 1.0 1.0 + 2.5 + 4.4Saitama 1.0 1.0 + 3.5 - 4.2Chiba 1.2 1.2 + 1.7 + 0.4Tokyo 0.9 0.8 - 10.3 - 10.4

Kanagawa 0.9 0.9 - 4.5 - 5.2

Chubu * 23.1 18.2 - 4.9Niigata 1.3 1.2 - 5.1 + 2.0Toyama 1.2 1.2 - 1.1 - 3.7Ishikawa 1.0 0.9 - 1.0 - 8.6

Fukui 0.9 0.9 + 8.2 - 8.2Yamanashi 0.7 0.7 - 10.3 + 2.0

43

Nagano 0.8 0.8 - 0.5 - 0.1Gifu 0.8 0.8 - 3.6 - 3.6

Shizuoka 0.8 0.8 - 0.8 + 0.2Aichi 0.8 0.9 + 9.2 - 9.4Mie 0.9 0.8 - 2.0 + 1.0

Table 9: Pressure on Arable Land and Incidence of Landlord/Tenancy Disputes, Japan, 1925-1940 [Continued]

Prefecture/Region

Arable Land per Farm Households (Hectares)

PercentageChange

in Numberof Farm

Households

Percentage of Landlord/Tenant Disputes in

Region1925 1940 Percentage

Change,1925/40

1917-31

1932-41

Change in Percentage(Absolute)

Kinki 34.9 % 13.6 % - 21.3Shiga 0.8 0.9 + 11.0 - 8.1Kyoto 0.8 0.8 - 0.2 - 6.8Osaka 0.7 0.7 - 3.7 - 12.0Hyogo 0.7 0.7 + 0.02 - 6.5Nara 0.7 0.7 - 1.9 - 30.7

Wakayama 0.6 0.7 + 4.5 - 2.5

Chugoku 8 7.5 - 0.5Tottori 0.9 0.9 + 4.9 - 3.7

Shimane 0.8 0.8 - 1.2 - 9.7Okayama 0.8 0.8 + 5.4 - 6.0Hiroshima 0.6 0.6 + 9.6 - 10.7Yamaguchi 0.9 0.9 + 4.2 - 11.2

Shikoku 5.7 6.8 + 1.1Tokushima 0.7 0.7 - 3.0 + 1.7

Kagawa 0.6 0.6 + 6.4 - 3.6Ehime 0.9 0.7 - 15.5 - 1.1Kochi 1.5 0.9 - 37.2 - 10.5

Kyushu 8 9.7 + 1.7Fukuoka 1.0 1.0 - 0.7 - 4.5

Saga 1.1 1.1 + 4.3 - 5.7Nagasaki 0.8 0.8 + 1.2 - 4.1

Kumamoto 1.2 1.1 - 4.1 - 3.0

44

Oita 0.8 0.8 - 0.3 - 5.6Miyazaki 1.3 1.1 - 13.5 + 13.0

Kagoshima 1.1 0.8 - 25.9 + 6.1

Okinawa 0.7 0.7 - 8.8 + 4.4

B.6 Health and the Biological Standard of Living

[1] The Human Development Index (HDI)

[2] The Biological Standard of Living (BSL)

Secular trends in the anthropometric measures for adults – terminal levels in the biological standard of living

Human growth for children and youths – tempo of growth

[3] World Health Organization (WHO) Measures of Absolute Poverty – Using the Anthropometric Measures for Children and Young Adults

C Savings and Investment

Reading:

Easterly: Chapters 3, 4 and 9.

Mosk: Chapters 4, 5, 6, 7, 8, and 9.

C.1 Sources of Growth Accounting, the Harrod-Domar Model, Convergence and the Swann-Solow Model

[1] Sources of Growth Accounting

Logic of growth accounting and the Cobb-Douglas aggregate production function

Denison’s interpretations – the importance of structural change, scale economies, and accumulation

45

[2] The Harrod-Domar Model

s/v = G(Y)

warranted rate of growth, knife-edge property of economy

[3] The Swann-Solow Model

Interpretation issues: steady states; transitions from one to another; savings rate and golden rule; population growth rate; capital-widening versus capital deepening

why isn’t there more investment in low per capita income countries (Lucas hypothesis issue)?

[4] The Endogenous Growth Model

Overcoming diminishing returns to capital accumulation learning by doing and using capital – social externalities stock of ideas as public goods research and development expenditures as share of investment in

capital technology embodied in capital (capital vintage)

C.2 Infrastructure

[1] Human Capital Enhancing Infrastructure (Education)

Investing in Education: Demand and Supply Considerations

Demand

I.A Expected Rate of Private Return of Return

Cost/benefit calculus

Interpretation issues: (1) general versus specific skills – issue of firm specific human capital and studies of influence of general literacy on achievement on internationally standardized mathematics and sciences tests; (2) signaling and certification and job match issue, internalization of labor; (3) social status? Marriage markets?

46

I.B Income per capita and its size distribution

Gini coefficient, Lorentz curve, quintiles, quartiles, deciles, etc.

I.C Demographic variables

Life expectancy and fertility

Age structure (vital rates and age structure interrelated in the long-run)Supply

I.D Private sector or public sector?

Social as opposed to private returns? How best to achieve efficient allocation of resources (brain drain issue, etc)?

I.E Standards – the Weberian Bureaucracy/Capitalism thesis

I.D Externalities

Different levels of schooling: complements or substitutes?

Declining rate of return within educational category as more and more people get a certain level of education.

An Example of Supply/Demand Interaction: Japan’s Ministry of Education Interacts with the Market: The Expansion of Education in Pre-1938 Japan

A dualistic educational system meeting the needs of an expanding industrial economy

The “ronin” rate as a signal and Ministry of Education policy Information flows back from market demand to the bureaucracy:

rejection rates, ranking of schools, “rōnin” rates and the cram schools

[2] Financial and Physical Infrastructure

Financial Infrastructure Build-up

Rotating savings and credit associations in developing countries – drawing from a “pot,” small groups

Financial depth and more sophisticated systems with currency, banks, lender of last resort, equity markets

47

Example: the development of financial infrastructure in Meiji Japan (financial infrastructure led growth): National banks and drive to create convertible currency, Bank of Japan Act of 1882, Overloan policy of Bank of Japan, the zaibatsu

The Infrastructure Driven Growth Hypothesis for Japan

Evidence from international cross-sections

48

Table 10

Growth Accounting Equation and the Aggregate Production Function

From the basic multiplicative aggregate Cobb-Douglas Production Function that assumes constant returns to scale (or rather captures them in the A variable):

Q = A(K*)α(L*)β(LA*)[1-(α+β)]

where:

Q = flow of output (GDP); K* = flow of services from augmented capital; L* = flow of services from augmented labor; and LA* = flow of services from augmented labor; and A = index of total factor productivity

We can derive the basic growth accounting equation:

G(Q) = G(A) + α G(K*) + β G(L*) + [1-(α+β)] G(LA*).

In the table we discuss issues involving the measurement and interpretation of each of the five major variables, Q, A, K*, L* and LA*.

Variable How is the Variable Comments on Interpretation

49

Augmented or Adjusted? of AugmentationG(Q)

Aggregate OutputGrowth

Adjust the flows of commodity and service

output for quality

Adjustment involves index number problems and assumptions about the

values of components of products and services

G(A)Total Factor Productivity

Growth

Underlying growth in total factor productivity are (1) scale economies (stemming from geographic externalities and those internalized by firms); (2) structural change in the composition of output; and (3) technological and organizational change.It is possible that all three factors are correlated with G(K*).

G(K*) Through changes in the quality of capital, for

instance due to the changing vintage (age) of capital.

Controversy surrounds the question of whether

changes in technology are embodied in K*.

Table 10 [Continued]

Variable How is the Variable Augmented?

Comments on Interpretation of Augmentation

G(L*)

Raw labor input is augmented by changes in

the efficiency of labor e(L). Underlying changes in the efficiency of labor are (1)

changes in the demographic, educational composition of the labor force; and (2) changes in

the health of the labor force; and (3) changes in hours

worked (H) per worker; and (4) changes in incentives that impact work intensity

per hour worked.

The four factors underlying efficiency of labor may be

shaped by (1) the organization and

management of production units; (2) the quality of

managers; (3) the range of opportunities open to workers (shaped by

geographic barriers and barriers to achieving

socioeconomic mobility, for instance through acquiring education, hence by public

policy)

G(LA*)

Land – for instance agricultural land – is

augmented through the application of fertilizers and

Technological progress in agriculture may have a land augmenting bias due to the

relative price of land

50

irrigation. Land is also augmented by converting it from one use to another, for instance from wasteland or

forest to arable land

services relative to labor services or due to the

elasticities of supply of labor and land (e.g.:

inelastically supplied land tends to promote

augmentation of land.

In principle in analyzing the sources of growth it is important to decompose the growth of each of the three factors of production into their components, namely:

G(K*) = G(qK) + G(K) where qK captures the average quality of capital services and K is the flow of raw unadjusted capital services.

G(L*) = G[e(L)] + G(L), where the average efficiency of labor e(L) depends upon hours worked H; intensity of work effort per hour worked; the demographic structure of the labor force (shaped by age and gender composition); the level of education and health of the population, especially those employed in the labor force; and barriers to exploiting potential opportunities (e.g.: geographic isolation from markets may be a barrier); and incentives provided by the way production units are managed. L is raw labor input.

G(LA*) = G(qL) + G(LA) where qK is the average quality of land that depends upon land use practice.

Table 11

Expansion of Infrastructure and Industry in China and Japan, 1880-2000

A The Penetration of Infrastructure, China and Japan Compared, Circa 1920 and 2000(a)

Item

Road Length (km) RailroadsElectricityGenerated

(kw-hours)

Total Paved Track(km)

Operation-km

FreightVolume(ton-km)

PassengerTraffic

(passenger-km)

Per PersonChina, 1920

n.e. 0.00006 0.00002 n.e. 15.5 8.6 n.e.

China, 2000

n.e. 0.02 0.00004 n.e. 11,822 355.4 971.7

Japan, 1920

15.8 n.e. 0.24 0.28 177.5 32.1 913.3

Japan,2000

9.2 7.0 0.19 0.22 174,401 170.6 8,599.5

Per Land Area (Per Hectare)China, n.e. 0.00003 0.00001 n.e. 7.7 4.3 n.e.

51

1920China, 2000

n.e. 0.02 0.00006 n.e. 15,711 472.3 1,291.4

Japan, 1920

23.4 n.e. 0.36 0.42 262.9 47.5 1,352.9

Japan,2000

30.9 23.6 0.65 0.73 585,919 573.0 28,891.0

B Infrastructure and Industry in Japan, 1880-1985

B.1 The Expansion of Railroads and the Disappearance of Traditional Transportation in Japan (Rikusha and Small Boats, Kobune), Indices with

1920-21 = 100 (b)

PeriodRailroads (Operation-km) Traditional Transport

National Regional Street Total Rikusha Kobune1900-09 35.6 104.4 n.e. 45.1 162.6 266.61910-19 85.1 66.7 92.5 78.6 111.9 168.21920-29 115.9 141.8 113.2 120.9 70.5 86.81930-41 159.4 207.4 109.1 162.6 23.3 77.5

Table 11 [Continued]

B.2 Electricity Generated (GEN), Electric Lights (LIGHT), Wattage in Lights (WATT), and Electrified Cars on Railroads (CAR): Indices with 1920-21 = 100

Period GEN LIGHT WATT CAR1910-14 30.4 30.0 47.8 46.11925-29 143.4 232.0 247.2 179.91935-39 724.2 555.0 732.2 190.4

B.3 Number of Electric Lights (LIGHT) and Electricity Supplied (ELEC): Indices with 1920-21 = 100 for Japan and the Tōkaidō Industrial Belt (INB) and the

Percentage for the Tōkaidō Industrial Belt (INB%) (c)

PeriodLIGHT ELEC

Japan INB INB% Japan INB INB%1910-19 41.7 51.4 65.2 % 70.4 74.7 45.31930-37 163.1 160.4 40.2 339.6 386.7 48.9

B.4 Powered Factories as a Percentage Classified by Number of Workers in Factories (POW%) and Composition of Inanimate Power Sources for

Manufacturing: STEAM (Steam Engines and Turbines), (INCOM) Internal

52

Combustion Engines, and Electric Motors (ELEC)POW% Classified by Number of Workers Composition of Power Sources

Year 5-29 30-99100 and

Over Year STEAM INCOM ELEC1909 20.5 % 69.7 % 88.4 % 1910 80.6 % 6.6 % 21.8 %1919 54.3 88.6 99.3 1920 31.3 3.4 58.91930 80.1 95.3 99.6 1930 15.6 1.2 81.8

B.5 The Expansion of Transportation, 1955-70: Indices for Transportation Flows with 1965 = 100

YearCargo Passenger

Total RailMotor

Vehicle Sea Total RailMotor

Vehicle Bus1955 31.5 73.1 19.8 35.7 31.0 54.7 16.6 30.91970 262.1 109.4 286.4 179.6 313.7 122.1 396.3 113.1

Table 11 [Continued]

B.6 Index for the Price of Transport (TRANSPI) Relative to the Consumer Price Index (CPI): 1880-1939 and 1955-85

Period CPI(1)

TRANSPI (2)

Relative Cost of Transport: (2)/(1)

Pre-1940: Indices with 1934-36 = 1001880-99 16.7 25.4 154.01920-39 111.7 112.5 101.4

Post-1950: Indices with 1980 = 1001955-59 22.9 26.7 116.71980-89 108.1 106.6 98.7

B.7 Expansion of Manufacturing: Indices of Industrial Production, Value Added Weights, 1980 = 100: Sub-sectors Other Than Machinery

Period Total

Heavy Industry Sub-sectors Light Industry Sub-sectors

Iron & Steel

Non-ferrous Metals Chemicals

Textiles Food &Tobacco

53

1931-35 4.3 2.5 3.7 2.6 26.2 18.91956-60 13.4 12.4 13.4 12.1 36.5 31.61966-70 51.0 56.5 52.2 45.1 83.1 70.91971-75 75.8 84.0 77.6 71.4 100.5 86.1

B.8 Expansion of Production of Machinery: Indices of Industrial Production, Value Added Weights, 1980 = 100: Machinery Sub-sector as a Whole and for

Important Sub-sectors of Machinery ProductionPeriod Total Non-electric

MachineryElectric

MachineryTransportEquipment

PrecisionMachinery

1931-35 0.8 2.1 0.2 0.6 0.81956-60 6.7 9.1 4.0 7.6 5.71966-70 37.5 29.1 29.1 42.9 22.01971-75 62.7 52.2 52.2 73.7 34.6

Table 11 [Continued]

C Infrastructure and Industry in China, 1895-2005

C.1 Expansion of Traditional and Modern Freight Transport, 1895-1936

Year

Volumes (Million tons-km) Transported by:

Share Carried by

Modern Equipment

(Steam Ship and Rail)

Index of Total

Volume(1895 = 100)

Rail Steam Ship Junk

1895 0.2 5.2 24.1 16.8 % 1001915 7.3 16.3 35.8 36.2 189.81933 12.8 25.9 51.2 41.2 291.31936 14.6 26.6 54.3 41.4 309.0

C.2 Expansion of Railroad Track and Services and Length of Motor Roads, 1895-1983: Indices with 1949 = 100

RailroadsLength of Freight (ton-

54

Year Track (km) km) Passenger-km Motor Roads

1895 1.9 0.8 0.8 n.e.1915 48.2 31.8 25.7 n.e.1933 72.5 69.6 54.7 88.91949 100.0 100.0 100.0 100.01957 122.5 731.5 277.9 314.81979 n.e. n.e. n.e. 1,081.51983 236.7 3,612.0 2,380.8 n.e.

C.3 Output of Chinese Industry in 1933 Prices (In Billion Yuan)Sector 1933 1952 1957

Factories 0.74 1.35 3.12Handicrafts 2.22 2.33 2.66

Mining 0.23 0.68 1.40Utilities 0.16 0.39 0.89

Total 3.35 4.75 8.07Share of Handicrafts

(%)66.3 % 49.05 32.96

Table 11 [Continued]

C.4 Growth Rates for Major Sectors of GDP as Estimated by Yeh and by Rawski (“Preferred Estimates” Given by Rawski), 1914/1936

Item Yeh RawskiAgriculture 0.8 % 1.4 – 1.7 %

Modern Industry 7.7 8.1Handicrafts 0.7 1.4Construction 3.5 4.6

Modern Transportation/Communications

4.0 3.0

TraditionalTransportation/Communications

0.3 1.9

Trade 1.1 2.5Finance 2.9 5.0

GDP 1.1 1.8 – 2.0

C.5 Share of Regions in China’s Manufacturing Output in 1933 and Percentage of Firms in Each Region That are Chinese

55

Region Share of Region Share of Chinese FirmsChina Proper (Excluding

Manchuria) 85.8 % 78.1 %Shanghai 39.7 69.2Kiangsu 8.7 97.8

Other 37.3 82.9Manchuria 14.2 41.1

C.6 Cost (Yuan) for a Bale of 20-Count Yarn in Chinese and Japanese Mills in China, 1930s

Item Chinese Mills(1)

Japanese Mills(2)

Difference(1) – (2)

Contribution to Total

Difference (%)Wages 10.5 5.8 4.7 20.2 %Power 5.5 4.8 0.7 3.0

Machine Repairs

1.8 0.6 1.2 5.2

Materials 1.7 0.5 1.2 5.2Salaries 1.2 0.6 0.6 2.6

Sanitation 0.2 0.5 -0.3 -1.3Management 2.5 2.0 0.5 2.2

Taxes & Interest

15.0 2.7 12.3 52.8

Total 43.7 20.4 23.3 100.0

Table 11 [Continued]

C.7 Growth Rates for Light and Heavy Industry, 1952-99Period Light Heavy

1952-78 8.7 % 11.9 %1978-89 15.4 12.91989-99 15.1 16.6

C.8 Relative Labor Productivity (Yuan per Worker) of Labor in Commune and Village Enterprises, 1978-83

Period

% of Employment in

Industry(1)

Labor Productivity in

Agriculture(2)

Labor Productivity in

Industry (3)

Ratio (2)/(3)

1978-89 75.8 % 658.5 2278.5 28.9 %1980-81 82.5 845.0 2773.5 34.01982-83 86.7 1290.0 3304.0 39.0

56

C.9 Indices for Employment in Textiles and Apparel (INDEM), 1980 = 100, Employment per Firm (SIZE), Share of Sector in Total Exports (EXPS), and Share

of China’s Textiles Exports in World Exports (WEXPS), 1980-2005Year INDEM SIZE EXPS WEXPS1980 100.0 132.5 19.8 % 4.6 %1990 247.6 148.3 20.1 7.52000 161.6 387.6 19.8 14.72005 194.8 271.8 15.4 24.1

C.10 Indices for Output (INDO), Employment (INDEM) and Output per Man Year (INDLP) and Ratio of the Difference Between Exports and Imports Relative to

Output (EX-IM/O), Steel Industry, 1980-2005Year INDO INDEM INDLP EX-IM/O (%)1980 100.0 100.0 100.0 -12.1 %1990 179.0 129.1 138.8 -2.42000 346.4 103.3 335.5 -7.92005 952.0 115.2 827.0 -1.5

Table 11 [Continued]

C.11 Share of Chinese Bank Loans by Type:

Period Industrial Infrastructure

AgriculturalTown and

VillageEnterprises

PrivatelyOwnedFirms

JointVentures

1995-99 21.7 % 1.8 % 4.2 % 5.9 % 0.5 % 2.6 %2000-05 15.4 1.8 5.2 5.3 0.9 2.2

Notes: (a) In the case of Japan circa 2000 the figures for railway track are for 1984. The figures for Japan’s road length and electricity generated are for 1921, not 1920. Figures on paved road length are not available for Japan until 1936. In order to estimate China’s paved road length for 2000 I relied on an estimate of 11 vehicles per km of roads, multiplying by the number 11 the number of reported vehicles.

57

(b) In the case of traditional transport the indices for 1930-41 are actually for 1930-38.

(c) In the case of electricity supplied, the figures for

n.e.: not estimated.

Sources: For Panel A the sources for Japan are various tables in Japan. Ministry of Internal Affairs and Communications and Statistical Research and Training Institute (2009); for China the sources are various tables in the following: China. National Bureau of Statistics (2004), Maddison (1998, 2006), Mitchell (2003), Rawski (1989), United Nations (2004) and World Bank (2002). For Panels B.1 – B.4 various tables in Mosk (2001). For Panels B.5 and B.6 various tables in Mosk (2005). For Panels B.7 and B.8 page 251 of Mosk (2008). For Panels C.1, C.2, C.4, C.5 and C.6 varioustables in Rawski (1989). For Panel C.3 page 146 in Maddison (1998). For Panels C.7 and C.8 various tables in Bramall (2009). For Panels C.9 and C.10 various tables in Brandt, Rawski and Sutton (2008). For Panel C.11page 521 in Allen, Qian and Qian (2008).

Table 12

Income per Capita in Selected Asian Countries (Figures in 1990 International Geary-Khamis Dollars) and Income per Capita Relative to that for China

A Income per Capita (1990 International Geary-Khamis Dollars)

Period China Japan Taiwan Hong Kong

South Korea

India

1950-54 513 2292 1066 2379 842 6401955-59 644 3141 1339 2828 1082 6981960-64 605 4799 1700 3688 1158 7741965-69 714 7287 2386 4948 1533 7991970-74 812 10615 3640 6466 2579 8511975-79 928 12166 5022 8535 3754 9171980-84 1205 14069 6749 11536 4671 10011985-89 1694 16478 9319 15216 6899 1158

58

1900-94 2130 19411 11144 19119 9853 13561995-99 2964 20913 14374 20979 12583 1681

B Income per Capita Relative to China’s Income per Capita

Period Japan Taiwan Hong Kong South Korea India1950-54 4.46 2.08 4.66 1.64 1.261955-59 4.87 2.08 4.40 1.69 1.091960-64 7.99 2.83 6.13 1.93 1.291965-69 10.23 3.35 6.93 2.15 1.121970-74 13.07 4.47 7.95 3.17 1.051975-79 13.13 5.40 9.18 4.04 0.991980-84 11.75 5.60 9.61 3.88 0.841985-89 9.74 5.51 8.96 4.06 0.691900-94 9.20 5.25 9.02 4.64 0.641995-99 7.07 4.85 7.12 4.26 0.57

Source: Maddison (2006): pages 304-305 (Table C3-c).

Table 13

Growth Accounting for Japan, Hong Kong, South Korea, Taiwan and China, Mainly Post-1950

A Japan

A.1: Long-Run Estimates, 1888-1990 for the Growth in Labor Productivity

Period [1]

Capital-Income Share

[2]

Labor Productivity

[3]

Capital-labor ratio

[4]Total Factor Productivity

(TFP) Growth

[5]Contribution

of TFP Growth

[4]/[2] (%)A.1.1 Pre-World War II

1888-1900 0.33 2.08 5.74 0.19 9 %1900-20 0.39 2.68 6.07 0.31 121920-37 0.43 2.29 2.75 1.11 481928-37 0.47 3.04 2.23 1.99 65

A.1.2 Post-World War II

59

1958-70 0.33 8.19 11.60 4.36 531970-90 0.28 3.78 7.44 1.70 45

A.2 Estimates of Sources of Growth of National Income, 1953-71

A.2.1 Growth in Income, Total Factor Input and CapitalNationalIncome(Output)

TotalFactorInput

Capital

Total InventoriesNonresidentialStructures &Equipment

Dwellings InternationalAssets

8.81 3.95 2.10 0.73 1.07 0.30 0.00A.2.2 Growth in Land and Labor

LandLabor

Total Employ-Ment

Hours ofWork

Age-SexComposition Education Unallocated

0.00 1.85 1.14 0.21 0.14 0.34 0.02A.2.3 Total Factor Productivity Growth

Total (Growth inOutput per

Unit of Total Input)

Advancein

Know-ledge &Innovat-

ion

Economiesof

Scale

Improved Resource Allocation

Contraction ofAgriculturalEmployment

Contractionof Non-

AgriculturalSelf

Employment

Reduction of

InternationalTrade

Barriers4.86 1.97 1.94 0.64 0.30 0.01

Table 13 [Continued]

A.3 Sector Specific Estimates of Total Factor Productivity Growth, 1961-1995

Top Ten (Over 1961-95 Period) Bottom Ten (Over 1961-95 Period)Sector 1961-73 1961-95 Sector 1961-73 1961-95

Air Transportation

6.95 % 3.11 % Water Supply -3.92 % -2.12 %

ElectricMachinery

4.18 2.93 Other Industries

-2.85 -2.05

Gas 2.86 2.36 Publishing -2.32 -1.49Trade 4.54 2.32 Agriculture -2.24 -1.43

Precision Machinery

3.39 2.19 Education 2.32 -0.63

Communications 1.79 2.01 RailwayTransportation

0.67 -0.59

Other Mining 5.45 1.73 Coal -0.63 -0.52

60

(Not Coal)Chemicals 2.91 1.65 Building &

Construction-0.94 -0.34

Vehicles 2.47 1.53 Foods -0.08 -0.29Public Services 3.91 1.46 Medical

Services0.25 -0.22

Table 13 [Continued]

B Estimates for the Growth in Labor Productivity: Hong Kong, South Korea and Taiwan, 1960-1999

Period

[1]

Capital-Income Share

[2]

Labor Productivity

[3]

Capital-labor ratio

[4]Total Factor Productivity

(TFP) Growth

[5]Contribution

of TFP Growth

[4]/[2] (%)B.1 Hong Kong

1966-70 0.34 4.1 5.9 2.1 51 %1970-80 0.358 6.0 5.4 4.0 671980-90 0.399 5.7 6.5 3.2 551990-99 0.391 1.9 6.5 -0.7 -36

B.2 South Korea1970-80 0.478 3.6 9.6 -1.0 -271980-90 0.429 6.2 8.7 2.5 401990-99 0.389 4.4 8.6 1.1 25

B.3 Taiwan

61

1960-70 0.485 7.0 10.9 1.7 241970-80 0.476 5.4 10.7 0.3 21980-90 0.435 6.2 6.7 3.2 521990-99 0.417 6.3 8.6 2.7 43

Table 13 [Continued]

C China

C.1 Growth Accounting Estimates for China, 1952-2005Contributions to Growth of National Domestic Product (GDP)

C.1.1 Growth of Output and Inputs

Period Growth inGDP

Average Growth of Inputs

Capital Raw LaborEducation-Enhanced

Labor

Total FactorProductivity

Growth (TFP)

1952-2005 7.0 7.7 1.9 2.6 2.11952-78

1952-78 4.4 5.8 1.9 2.5 0.51952-57 6.5 1.9 1.2 1.7 4.71957-78 3.9 6.7 2.0 2.7 -0.51957-65 2.4 5.2 1.5 2.1 -1.01965-78 4.9 7.7 2.4 3.1 -0.2

62

1978-20051978-2005 9.5 9.6 1.9 2.7 3.81978-85 9.7 9.2 3.4 4.5 3.21985-90 7.7 6.9 2.5 2.9 3.11990-95 11.7 9.1 1.4 1.9 6.7

1995-2000 8.6 10.5 0.9 1.6 3.22000-05 9.5 12.6 1.0 1.8 3.1

C.1.2 Percentage Shares of GDP Growth Attributable to:Capital Education-Enhanced

LaborTotal Factor Productivity

Growth (TFP)1952-2005 47.7 % 21.4 % 30.9 %1952-78 56.3 32.7 11.0

1978-2005 43.7 16.2 40.1

C.2 Various Estimates of Total Factor Productivity Growth, 1980s and 1990s, Range (a)

Data Used 1980s 1990sNational Level GDP Data 2.1 – 3.7 (4 estimates) 0.3 – 2.8 (4 estimates)

Provincial Level GDP Data 0.4 – 5.5 (4 estimates) 1.8 – 6.3 (3 estimates)Industry Level Data 3.1 – 6.5 (2 estimates) 0.5 – 3.8 (2 estimates)

Table 13 [Continued]

C.3 Estimates of Total Factor Productivity Growth in Independent-Accounting Industrial Enterprises, 1980-1996 (b)

PeriodState Owned Enterprises

Collectively Owned

EnterprisesOther Domestic

Enterprises

Foreign Invested

Companies1980-84 2.1 3.1 n.a. n.a.1984-88 3.8 5.2 n.a. n.a.1988-92 2.1 3.1 2.1 1.11992-96 -1.1 4.3 3.1 0.71980-96 1.7 3.9 n.a. n.a.

Notes: (a) Some of the estimates for the 1980s cover the period from the late

63

1970s until the early 1990s. For the 1990s estimates for the second half of the decade tend to be lower than those for the first half of the decade.

(b) n.a. = not available.

Sources: For Panel A.1 page 34 of Kim (2001). For Panel A.2 page 98-9 of Denison and Chung (1976). For Panel A.3 pages 173-4 of Nakajima, Nomura, and Matsuura (2004). For Panel B page 36 of Kim (2001). For Panel C.1, page 839 of Perkins and Rawski (2008). For Panel C.2 page 416 of Bramall (2009). For Panel C.3 page 540 of Huang (2008).

D Politics and Policies

Reading:

Easterly: Chapters 11, 12, and 13.

Collier: Chapters 2 and 3.

Sachs: Chapters 5, 6, 7, 8, and 9.

D.1 The Influence of Income Distribution Upon Political Stability

[1] Why do we care about income distribution?

Welfare

Classical theory of cardinal utility, utilitarian theory, “greatest good for greatest number,” critique of mercantilism

64

Ordinal utility theory in 20th century: Pareto optimality, theory of second best as a modifying viewpoint

Sen: capabilities, constraints – income and education (can the most talented succeed? Can individuals reach their full potential?)

Political stability

Middle class hypothesis, Marxist stage theory, democracy, free press, checks and balances in government

Savings and the macroeconomic balance

Possible influences of income distribution on savings – Keynesian, Friedman style consumption functions, logic of Kuznet’s U-shaped law regarding savings

Human Development and the Biological Standard of Living

Externalities imposed by poor health of the less well off, spillover onto the elite who can not insulate themselves completely

[2] Quartiles, quintiles and deciles in the size distribution of income and the Gini coefficient

Contrast with the functional distribution of income

[3] The Kuznets law regarding the relationship between income distribution and economic development

The “U” shaped Kuznets hypothesis

Why have many East Asian countries experienced “miracle growth,” enjoying relatively high growth rates for income per capita coupled with relatively equal income distributions?

Background to thinking of Kuznets

US economic history – “robber baron” period at end of 19th century; Progressives demand social legislation

Social programs and nascent welfare state during New Deal – influence of Progressive demands

65

Europe – the “Third Way” – influence of rise of international labor movement and Bismarck’s social welfare policies in Germany, subsequent Fascist corporatism in Italy, Germany – and Scandinavian collectivism/ small open economies problem in Denmark, Sweden, etc.

What about Miracle Growth in East Asia? Does it contradict the Kuznets hypothesis?

Land reform; importance of access to education for everyone; social “fairness”

Relatively late development of the welfare state

Corporate paternalism

Family system – responsibility of eldest son for carrying for aged parents (Confucian influence?)

Protectionism for agriculture, small business – use of industrial policy to shore up small business

Getting infrastructure out to local areas – South Korean example

Table 14

Gini Coefficients Estimated by the United Nations or the CIA and Ratios of Consumption or Expenditure Shares of Richest (upper 10%) to Poorest households (lowest 10%) Estimated by UN or CIA – R/P - for Selected Countries, Circa 2005

Country Gini (UN) Gini (CIA) R/P (UN) R/P (CIA)Latin America

Argentina 51.3 49.0 40.9 35.0Bolivia 60.1 59.2 168.1 157.3Brazil 57.0 56.7 51.3 49.8

El Salvador 52.4 52.4 57.5 55.4Mexico 46.1 46.1 24.6 24.6

Venezuela 48.2 48.2 48.3 50.3Europe

Denmark 24.7 24.0 8.1 12.0Finland 26.9 26.0 5.6 5.7

66

France 32.7 28.0 9.1 8.3Germany 28.3 28.0 6.9 6.9

U.K. 36.0 34.0 13.8 13.6Asia

India 36.8 36.8 8.6 8.6Japan 24.9 38.1 4.5 4.5

South Korea 31.6 35.1 7.8 8.6Africa

Kenya 42.5 44.5 13.6 18.6Namibia 74.3 70.7 128.8 129.0Senegal 41.3 41.3 12.3 12.4Uganda 45.7 45.7 16.6 16.4Zambia 50.8 50.8 32.3 32.3

Zimbabwe 50.1 56.8 22.0 20.2North America

Canada 32.6 32.1 9.4 9.5United States 40.8 45.0 15.9 15.0

Source: http://en.wikipedia.org/wiki/List_of_countries_by_income_equality (February 13, 2008)

D.2 Political Stability and Civil Conflict

Table 15Growth Rates for Income per Capita (gy) and Percentage of Years with Negative Income per Capita Growth Rates (yng%): Countries Classified According to the

Number of Years Prior to the First Year of the Observation Period When Current Nation State Established (yes)

Panel B.1: Countries for which “yes” is less than or equal to 1

Countrygy yng%

Number and Nature of Crises

Crisis period

Non-Crisis Period

Crisis period

Non-Crisis period

Algeria -2.27% 3.14% 66.7% 27.6% 2 (1962, 1991-98) ComplexAngola -2.95 1.99 63.6 9.1 1 (1975-98) Complex

Bangladesh 5.19 1.12 50.0 19.2 1 (1974-5) Regime transition

Benin 2.66 1.20 30.0 41.4 1 (1963-72) Regime transition

67

Burkina Faso -3.92 0.66 100.0 52.6 1 (1980) Regime transitionBurundi 4.93 -0.62 36.4 61.5 2 (1963-73; 1988-98)

ComplexChad 0.06 0.34 56.3 33.3 1 (1965-96) Complex

Comorus -7.16 -1.21 100.0 54.6 1 (1995-6) ComplexCyprus 1.82 5.23 28.6 20.0 2 (1963-8; 1974) Complex

The Gambia -2.35 0.78 100.0 57.6 1 (1994) Regime transitionGhana 1.83 0.74 75.0 42.1 2 (1972; 1978-84) Regime

transitionsGuinea-Bissau -28.22 4.84 100.0 45.8 1 (1998) Complex

Guyana -2.04 2.32 33.3 36.7 1 (1978-80) Regime transition

Kenya -2.24 1.76 100.0 42.4 1 (1991-93) Ethnic warLesotho 2.16 2.28 33.3 40.6 2 (1970; 1994-8) Regime

transition-1; Complex-2Madagascar -1.52 -.97 75.0 64.7 1 (1974-5) Regime

transitionMali -1.59 0.07 75.0 50.0 1 (1990-3) Ethnic war

Morocco 2.93 2.51 27.8 28.0 2 (1963-5; 1975-89) Regime transition-1; Ethnic

war-2Mozambique -3.44 0.07 62.5 62.5 1 (1976-92) Revolution

Niger -3.23 -1.51 100.0 59.5 1 (1996) Regime transitionNigeria 0.21 1.05 61.6 38.5 2 (1964-70; 1980-5)

ComplexPapua New

Guinea-022 -1.21 54.6 69.2 1 (1988-98) Ethnic war

Rwanda -2.20 1.93 46.2 33.3 2 (1963-66; 1990-8) Complex

Table 15 [Continued]

Panel B.1: Countries for which “yes” is less than or equal to 1 [Continued]

Countrygy Yng%

Number and Nature of CrisesCrisis period

Non-Crisis

Period

Crisis period

Non-Crisis Period

Senegal -0.44% -0.30% 45.5% 48.2% 2 (1962-4; 1991-8) Regime transition-1; Ethnic war-2

Sierra Leone

-1.78 0.52 54.6 45.8 2 (1967-71; 1991-8) Regime transition-1; Complex-2

Uganda 1.67 1.93 39.4 25.0 1 (1966-98) ComplexZambia 0.71 -1.30 66.7 69.0 2 (1968-72; 1996) Regime

transitionsZimbabwe 1.26 2.62 56.3 31.3 1 (1972-87) Complex

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Panel B.2: Countries for which “yes” is greater than 1

Countrygy Yng%

Number and Nature of CrisesCrisis period

Non-Crisis

Period

Crisis period

Non-Crisis period

Argentina 1.62 1.52 40.0 35.3 2 (1966; 1973-80) Regime transition-1; Complex-2

Brazil 2.23 1.22 16.7 21.0 1 (1964-5) Regime transitionChile -4.38 3.22 50.0 15.9 1 (1973-6) Complex

Columbia 1.94 1.87 7.1 23.3 1 (1984-8) RevolutionDominicanRepublic

1.13 3.28 33.3 16.7 1 (1961-6) Complex

Ecuador 6.33 1.54 0.0 31.0 1 (1970-2) Regime transitionEgypt 2.77 2.50 25.81 2.39 1 (1986-1998) Revolution

El Salvador

-1.66 2.09 46.7 10.3 1 (1977-92) Complex

Ethiopia 0.13 0.80 35.3 30.0 1 (1961-94) ComplexGreece 4.05 3.53 0.0 20.9 1 (1967) Regime transition

Guatemala 1.36 1.34 25.8 25.0 1 (1966-96) ComplexHaiti 11.56 3.16 0.0 53.3 1 (1991) Regime transitionIndia 2.54 - 27.3 - 1 (1952-98) Ethnic war

Indonesia 3.04 5.08 22.2 9.1 3 (1956-66; 1975-92; 1977-98) Complex (all three)

Iran0.64 5.58 40.9 19.1 3 (1952-5; 1963; 1977-98)

Regime transition-1; Revolution-2; Complex-3

Israel 2.83 4.35 21.9 8.3 1 (1967-98) Ethnic warJordan -3.71 3.47 50.0 34.2 2 (1957; 1967-71) Regime

transition-1; Revolution-2Table 15 [Continued]

Panel B.2: Countries for which “yes” is greater than 1 [Continued]

Countrygy yng%

Number and Nature of CrisesCrisis period

Non-Crisis

Period

Crisis period

Non-Crisis Period

Korea, South 4.43 5.56 25.0 12.5 2 (1961-3; 1979) Regime transition-1; Revolution-2

Mexico 2.27 2.04 0.0 18.6 1 (1994) Ethnic warNicaragua -5.28 0.81 83.3 43.8 1 (1978-90) ComplexPakistan A -3.16 3.49 50.0 7.1 1 (1958-61) Complex

69

Pakistan B 2.37 3.52 13.6 33.3 2 (1971-7; 1983-98) Complex-1; Ethnic war-2

Panama 4.23 2.52 0.0 26.2 1 (1968-9) Regime transitionPeru -0.35 2.21 41.2 22.2 2 (1968; 1982-97) Regime

transition-1; Complex-2Philippines 1.13 2.44 26.7 7.1 1 (1969-98) ComplexRomania -5.48 5.02 100.0 21.6 1 (1989) Revolution

South Africa -0.46 2.03 60.0 10.4 2 (1976-7; 1984-96) Revolution-1; Complex-2

Sri Lanka 2.80 1.56 5.9 11.1 2 (1971; 1983-98) Revolution-1; Complex-2

Syria 8.73 2.84 20.0 30.3 2 (1958-63; 1981-2) Revolution; Complex-2

Thailand 4.40 4.98 7.7 11.1 3 (1957; 1967-83; 1991-8) Regime transition-1; Complex-

2 & 3Turkey 2.30 3.02 30.0 16.7 2 (1971: 1980-98) Regime

transition-1; Complex-2United

Kingdom1.97 2.49 23.1 0.0 1 (1969-94) Ethnic war

Note: The State Failure Taskforce Report (Phase III) divides “state failure events” into the following five categories:

(1) Revolutionary wars – episodes of sustained violent conflict between organization and politically organized challengers that seek to overthrow the central government, to replace its leaders, or seize power in one region.(2) Ethnic wars – episodes of sustained violent conflict in which national, ethnic, religious, or other communal minorities challenge governments to seek major changes in status.(3) Adverse regime changes – major, abrupt shifts in patterns of governance, including state collapse, periods of severe elite or regime instability, and shifts away from democracy toward authoritarian rule.

Table 15: Notes [Continued]

(4) Genocides and politicides – sustained policies by states or their agents, or, in civil wars, by either of the contending authorities that result in the deaths of a substantial portion of a communal or political group.(5) Complex – complex events are made of two or more temporarily linked wars and crises. If events overlap or if four years or less separate the end of one event and the onset of the next, they are combined into complex events

D.3 Politics and Policies

[1] Implementing policies depends upon politics

70

The importance of bureaucratic independence, corruption, and transparency for the effectiveness of policies

How free of political pressure is the Japanese bureaucracy? An example.

[2] The classical Marxist stage theory and the bourgeois state

The Marxist stage theory of how feudalism gives way to capitalism: a Eurocentric thesis

The late developer theory of Gerschenkron How interventionist was the Meiji government? An example

[3] Politics and Policies: Bureaucratic Insulation versus Middle Class Democracy

Bureaucratic insulation (economic development first, then democracy)

3.a Civil law background to this view; bureaucracy relatively free to pursue “rational” policies free of pressure public, free from pressure from industries regulated

3.b Emphasis on coordination policies including buildup of infrastructure, bureaucracy having a longer run view of growth issues than do entrepreneurs in particular industries.

3.c Politics may not be “good” – consistent with military rule (e.g.: Park government in South Korea, military cabinets in Japan from 1932 to 1938)

3.d Matters for debate – how independent was the bureaucracy in Japan? Over-protection for declining industries? Pork-barrel politics? China today?

3.e Belief is that “catch-up” high speed growth requires setting targets and priorities above what comes out of the market (market failures exist, externalities and public goods required.

Middle Class Consensus (democracy first, economic development later)

3.f Common law background to this view; “Washington consensus” and views of neo-conservatives in the United States – Neo-Liberalism as a theory

3.g Desired characteristics – (1) political competition (democracy, free press); (2) transparency and accountability in government (frequent elections); (3) rule of law and independent judiciary; (4) private property rights; (5) low levels of corruption in government, regulation is market friendly and aimed at ensuring competition.

71

3.h Markets will flourish in this environment. Market oriented growth is the best road for economic development.

[4] Types of policies: Command, stabilization, regulation and coordination

Industrial and infrastructure building policies in Japan and South Korea: How do they work? How effective are these approaches?

Infrastructure expansion in pre-1938 Japan: some examples (steam railroads, hydroelectricity, developing paved road networks

Infrastructure and the promotion of rural development in South Korea

Industrial policy in postwar Japan: pros and cons

E Openness and Diversity

Reading:

Collier: Chapter 4; Parts 3-5 (Chapters 6, 7, 8, 9, 10, and 11).

Easterly: Chapters 2, 6, 7, 13 and 14.

Sachs: Chapters 11, 12, 13, 14, 15, 16, 17, and 18.

E.1 Trade

[1] The concept of trade openness – problems with the simple definition in terms of the volume of trade flows relative to national income

Trade in the macroeconomic balance equation

[2] Structure of a country’s tariffs and the rate of effective protection for an industry

[3] Comparative Advantage versus Gravity Model Theories of Trade

Historical Background: Phases of the International Economic Order

Great Britain and Free Trade, 1850-1914; Continental and American Resistance to Free Trade Policies

72

Deterioration in the International Economic Order: 1914-1950; the drive towards autarky, the geopolitical challenges to the gold standard and an open trade regime

A Revamped International Economic Order after 1950: American leadership and multilateralism

The heyday of American support for multilateralism

Catch-up due to convergence, bilateral trade deficits and erosion of American support for multilateralism

Economic Theories of Trade

Comparative Advantage: Ricardian Theory and Factor Supplies

Improving the terms of trade The risk of static efficiency losses: the Latin American

experience during the 1930s when the terms of trades of most Latin American countries deteriorated

The New Economic Geography: Scale Economies and the Gravity Model

Monopolistic competition differentiated from monopoly and from oligopoly

The Input-Output Structure of an Economy and Scale Economies

The Basic Leontief Model

Implications of Input-Output for Trade Policy: Scale

Economies and Backward and Forward Linkages

The East Asian Experience: From Import Substitution to Export Promotion And Miracle Growth

The Prewar Experience of Japan, Korea and Taiwan

Aggregate economic characteristics of growth: industrialization as a model of development in Japan, implications for Korea and Taiwan

73

Proceeding through the product cycle: the “flying geese” theory of trade

The zaibatsu and the shinzaibatsu in Korea (models for the postwar Korean chaebol.) Korea shifts to industrialization during the 1930s.

The Postwar Experience of Japan, Korea and Taiwan

Aggregate economic characteristics of Miracle Growth

The keiretsu and the chaebol in post-1950 East Asian development

Limits to the keiretsu/chaebol model: small business and government managed large enterprises in Taiwan

The Latin American Experience: From Export Orientation to Import Substitution Industrialization to Export Promotion

Latin America’s Prewar Export Orientation and the Changing Terms of Trade

Aggregate economic characteristics of export led growth: single commodity concentration in open economies; deteriorating terms of trade; underdeveloped infrastructure, including financial, and dependence on foreign capital

The ISI Experience in Latin America

Dependency theory, structuralism at the United Nations Economic Commission for Latin America (ECLA) and ISI (the Prebisch thesis)

Center/periphery theory

Engel’s law for consumption and the theory of the declining terms of trade for raw materials and foodstuffs

Aggregate economic characteristics of inward-looking industrialization and the “exhaustion” problem

Appraising ISI: Automobiles (dependency/structuralists versus Neo-liberalism.)

The Gravity Model and Regional Trade

74

Regional Trade Blocs and Gravitational Pull

Geopolitics and the international economic order: changes due to declining support for multilateralism in the developed world

Regional economic growth engines and gravitational pull Regional trade blocs and regional political gravitation: to what

extent do they overlap? To what extent do they diverge? Does economic regionalism undermine global multilateralism and

global economic integration?

E.2 International Migration

[1] The cost/benefit economic logic of international migration

Individuals and families in shaping emigration from developing countries

The importance of remittances

[2] Crossover in international migration

[3] Political barriers to international migration in countries of net in-migration

Resistance to diversity: the problem of ethno-linguistic fragmentation and the heterogeneity of preferences

[4] Regional trade agreements and regional migration flows

E.3 International Aid

[1] Putting international aid in perspective: comparison with international remittances from international migration and comparison with capital flow association with international trade

[2] The debates over international aid

How effective is international aid? How important is conditionality?

75