EC104: The World Economy: History & Theory (EC104)
Institution
The University Of Warwick (UoW)
This document contains all the notes from the synchronous and asynchronous lectures throughout the year and is split up lecture by lecture. It DOES NOT include the readings from Power and Plenty and The History of the Global Economy but these notes are also available on my account.
EC104: The World Economy: History & Theory (EC104)
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EC104
T1 L1: Pre-Modern Growth: pre-1500: Overview of World Economic History:
Value of production∈a year
How economists measure economic growth: GDPpc =
Population
GD P pc 1−GD P pc 0
in rates:
GD P pc 0
Modern economic growth: Modern economic growth is sustained growth of GDPpc (>0 rate)
The different periods of growth and their characteristics: World
economic performance was much better in the second millennium than
in the first. Between 1000 and 1998 population rose 22-fold and per
capita income 13-fold. In the previous millennium, population rose by a
sixth and per capita GDP fell slightly. The second millennium comprised
two distinct epochs. From 1000 to 1820 the upward movement in per
capita income was a slow crawl… since 1820 world development has
been much more dynamic e.g. Western Europe annual average growth of GDP per capita
was 0.14% between 1000-1820 but 1820-1998 it was 1.51%
Similar trend increases can also be seen in international trade, migrants, literacy rates and
life expectancy from 1820 onwards. Child mortality also fell rapidly from 1820 of around
30% for the countries which recorded the data to near zero now.
Different regions performed differently: W. Europe, its offshoots, Japan grew faster than
the rest -> convergence among the rich
Asian Tigers: notable catch up post 1950 followed by the BRICs
Africa on the whole diverged.
Overall the rich/poor gap became larger since the 19th century – there has been both
convergence and divergence.
19th century was different as trade was different – you had empires and transport revolution
which led to the global trade liberalisation.
This has led to debate about the timing of the start of globalisation
O’Rourke and Williamson (2002) said trade alone was insufficient for globalisation – you
need price convergence as well.
Did 1492 and 1498 show price convergence? Very little. Trade in luxuries reflects arbitrage
opportunities. Vast majority of the population remained poor. Little impact on growth or
Standard of Living.
Integration of markets needs more than trade – it needs movement of K and L
19th century transport revolution caused price of coal per ton to fall from 8
shillings in mid 18th century to just 4 shillings at end of the 19th century.
Fall in mark-up on goods shows increased competition/availability of goods.
Theory of 19th c. globalisation: Costly transportation, countries depend more
on their own resources – prices determined by domestic endowments ->
closed economy (price divergence across countries).
Cheaper transportation, countries depend less on their own resources – prices determined
by global endowments -> open economy (price convergence across countries).
,Endowments: Land and Labour
Evidence of 19th c. globalisation: Before 1820 Land/LAB positivity related to w/r
More people lower wages in a closed economy
After 1820 Land/LAB negatively associated with w/r
More people higher wages in a global economy
This helps to explain why divergence accelerates as some economies remain closed.
19th c. launched new epoch in world history (modern economic growth) for countries that
engage in this process – we will discuss the divergence further.
T1 L2: Pre-Modern Growth: pre-1500: Determinants of Growth:
Production function: Y = A K α L1−α where A is residual growth. Total factor productivity.
Growth accounting: Consider the following transformation of a Cobb-Douglas production
function: Y = A K α L1−α → ln Y =ln A+ α ln K + ( 1−α ) ln L
∂ lnY ∂ ln A ∂ ln K ∂ ln L
→ = +α + ( 1−α )
∂t ∂t ∂t ∂t
Ẏ Ȧ K̇ L̇
→ = + α + ( 1−α )
Y A K L
Hence, we can disaggregate the change in output over time into its proximate sources:
Growth of output = Residual Growth (TFP) + Growth of K contribution + Growth of L contribution
Proximate sources of growth: i.e. ones you can measure directly such as Labour and Capital
accumulation, Human capital accumulation, Technological change
Deep determinants of growth: these are not in our production function such as Institutions,
Geography and Demography.
Importance of Institutions and Geography on growth: Institutions are the “humanly
devised constraints that shape human interactions.” [North, 1990]
There are formal institutions such as the legal system, the political system, the economic
system, the education system and the healthcare system (e.g. NHS)
There are informal institutions such as culture -> morals, customs, norms -> ‘rules of thumb
that aid in decision making’.
Geography precedes development of institutions and influences them.
Classical growth models argue no wedges (A, K, L alone)
Institutions: frictions to classical model – limiting growth
Geography: may explain (very) long-run growth differences.
Diamond’s theory of growth: Theory is that it is easier to spread agricultural practises from
places that share the same latitude rather than the same longitude.
All countries that have had an agricultural transition for the longest, GDP per capita is
higher. Positive relationship between these two variables. However, there are certain
exemptions such as if you take groups of countries, such as the ones in Sub-Saharan Africa.
Basic growth (Geo & Inst) correlations: Sachs 2003 argued that geography mattered –
latitude: For example, if you are close to the equator: tropical soil is fragile and infertile;
high evaporation and unstable water sources; lack of dry season, or long summer days for
,crop gains; high prevalence of pests and parasites; ecological conditions favouring infectious
diseases; prevalence of disease conditions affects the ability to work; high transport costs
This is backed up by data from Easterly and Levine that the further away from the equator
you are the higher the GDP per capita you have.
Mayshar et al (2018): Geography – crops: Traditional view: hierarchies and states
emerge with surplus after Neolithic revolution (when agriculture develops), from hunter
gatherer to agricultural societies.
However, not all regions developed complex hierarchies.
Therefore, it is not about agricultural productivity but crop appropriability as well.
Soil suitability for different crops. Cereals are storable, roots and tubers perish and this
means that places relying on roots/tubers never reached complex hierarchies. All historically
large states based on agriculture relied on cereals.
Mayshat et al (2018): Geography matters but it is not the only thing that matters.
Institutions matter too. The more complex states are the more developed they are today.
Malthusian Economy and Malthusian Trap: Basic principle: population would outrun food
supply. Land supply is fixed – diminishing L returns. Any increase in income per capita will
result in population growth. BUT population growth is limited by food growth.
Mathematically: 1) Mt = a – bwt deaths are a negative function of resources food
2) Bt = c + dwt more resources, more births
3) Wt = e – fPt more population -> lower wages
4) Pt + 1 = Pt + Bt - Mt population tomorrow = population today + balance between B and D
If wages were to increase (wt), then births increase and deaths decrease by 1 and 2,
therefore, 4 increases. But increase of population means births decrease and deaths
increase (which is the reverse). Therefore population is bounded by wages and vice versa
Malthusian Trap: Growing at its natural population rate outruns food supply. The
vast majority of the population lives at subsistence (0-growth). Regulation mechanisms
(keeping P and w bounded): positive checks (↑ M ) and preventive checks (↓ B ¿
Validity of the Malthusian model: Explains pre-modern growth of P and w rather well
– long run stagnation. However, it fails to explain modern economic growth -> cannot
explain sustained rises of GDPpc
However, the assumptions change with MEG (which we will explore later): Industrial
Revolution leads to gains in L-productivity, increased growth rate of resources above
population (which allows you to escape the Malthusian trap); IR brings sustained growth
instead of intermittent shocks; in time, as income rises fertility comes down (Demog trans.)
Demographic transition: From high fertility to low fertility. However, the speed of the
decrease in mortality relative to the decrease in fertility matters for population size matters.
Allows for the escape from the Malthusian trap. Decreased prevalence of positive checks
(lower mortality) due to medical advances, less famines etc. Increased importance of
preventive checks such as contraception, women working which causes less fertility
↓ M ∧↓ F may not be simultaneous or in that order. P may stall (if fertility falls before
mortality) or balloon (if mortality falls before fertility).
, Quality-Quantity trade off: Becker’s model which explains the fall in fertility. Parents derive
utility in both quantity and quality of children. Low income elasticity for Quantity and high
for Quality. ↑household income will ↑ Dql but ↓ Dqt −¿ latter dominates: fewer kids
Why does the ↓ Dqt dominate? ↑cost of raising children; decline in need for social insurance
T1 L3: Pre-Modern Growth: The World Economy pre-1500: 3 episodes of non-sustained
growth:
Evidence of pre-modern growth in the Islamic World: Death of founder in 632AD,
conquests proceed into the 8th century. They extended territory: starting in the Arabian
Peninsula, extending into Persia, Greece, Rome and the W Mediterranean.
However, how do we measure pre-modern growth as there was no
national accounting until the late 1800s?
You can see on the right that the origins of authors was centred in the
Islamic World – economic activity was not really in Western Europe before
the Industrial Revolution.
Golden Age of Islam 7th – 13th c. Production of science and culture under 3
Caliphates -> Rashidun 632-661, Umayyad 661-750 and Abbasid 750-1258
Chaney (2013) “Revolt on the Nile” – Link between economic crises and political
instability. In the context of Islamic Egypt (641 – 1517): agricultural yields strongly
influenced by the Nile. Yields affected by floods and droughts which could induce famines -
↑ prices, hoarding, social unrest. Social unrest rose influence of religious leaders (judges)
which led to potential for successful coordination revolt against political power (as religious
leaders had enough power to do this due to their position of influence). Therefore, judges
were less likely to be removed during shocks as they controlled popular support and
therefore governments had to keep them on side as they could cause revolt if they turned
against the government. When judges changed therefore, never coincided with
drought/flood.
Michalopolous et al (2018): investigated the motives behind the spread of Islam and
showed that proximity to pre-600 trade networks predicted adherence to Islam.
Evidence of pre-modern growth in China: Two periods of economic growth (efflorescences,
not MEG) – early Northern Song (960-1127) and Late Ming (1405-33)
Pre-late 1800s, GDPpc estimates were based on population/urbanisation as if cities are
growing, it must be that the agricultural sector is producing enough surplus to allow people
to move into cities. You could also look at stats such as minting of coins which indicates the
existence of industry and the number of public servants which indicates the existence of
services.
Findlay and O’Rourke 2007: Narrative Evidence: Song peak -> increase in cultivated
area, new high-yielding rice variety – Malthusian economy – higher output allows for higher
population growth. Growth of industry and service sector.
Late Ming Voyages – Great naval expeditions mounted before Europeans did it. Fleet of 200-
300 ships and up to 28,000 men which was the largest up until WW1.
Bai and Kung (2011): documents clash of civilisations lasting more than 2000 years.
Importance of the Sino – nomadic conflict in shaping China -> nomadic economies were
heavily dependent on grazing (rainfall). Less rainfall brings higher probability of conflict ->
drought leads to crop failure and that to famine and civil unrest.
Shiue (2017): Relationship between education and fertility in China 13 th -20th c. Q-Q
trade-off present 17th to the 19th c. Fertility choices respond to economic incentives.
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