The World Before 1800: Stagnation or Development PDF

The world before 1800: stagnation or (slow) development? Contents of this chapter 1. The Great Divergence a. A very short history of the world before 1800 b. GDP per capita before 1800 c. Population growth and income per capita 2. Malthus's theory of population...

The world before 1800: stagnation or (slow) development? Contents of this chapter 1. The Great Divergence a. A very short history of the world before 1800 b. GDP per capita before 1800 c. Population growth and income per capita 2. Malthus's theory of population a. Basic idea b. Greg Clark's Malthusian model c. Preventive checks: The European Marriage Pattern and the Chinese demographic system 3. Adam Smith's theory of market integration and specialization a. Basic idea b. Illustrations 4. Combining both theories: a race between diminishing returns and learning by doing a. Basic idea b. Evidence c. One salient example: London and preindustrial growth in England 5. So, why was growth so slow? ‘Bad’ institutions and little innovativeness 6. Wrap up 7. Bibliography 1 1. The Great Divergence a. A very short history of the world before 1800 Starting point: the great divergence from c. 1800 Source: Gregory Clark, A Farewell to Alms. Princeton University Press, 2007, p. 2. The Sixteen-Page Economic History of the world Source: Gregory Clark, A Farewell to Alms. Princeton University Press, 2007, pp. 1-2. 2 b. GDP per capita before 1800 Is this true? ‘Real’ numbers (GDP/cap int. 1990 US-Dollars) – not the logarithmic scale. Problem of not development in India, unequal globalization Source: Broadberry (2021), Fig. 2, p. 45 & Figure 4, p. 47. 3 Living standards in 1990 international US dollars since the (European) Middle Ages - Malthusian traps or not? B F E C D A Source: Broadberry (2021), Table 2, p. 38. By and before 1750 most societies were poor by modern standards. The GDP of Britain and the Netherlands in 1800 (A) is similar to that of Nigeria in 2016 (or to Austria in 1880, 1916 or 1946), that of India is similar to that of Afghanistan or Niger in 2016 (or 65% of that of Italy in 1AD). Sustained growth/development (with slowdowns) in Britain since (at least) 1280 (B), in the Netherlands since (at least) 1348 (C), and in Japan after 1450 (D). But stagnation of incomes in Italy (E), Spain and Germany (not shown), and decline in China to 65% of 1020 level/85% of 1450 level by 1800 (F). In 979, the Song dynasty had unified Inner China after the „Five dynasties and Ten kingdom“ era; in 1450, Ming China was just before the start into an era of relative maritime isolation (class 1, p. 12) as well as in need of intensified defense against invasions from the North. At the same time (next slide), in all places discussed above (plus others) population grew (cf Malthus) at least since 1500, after the shock of the Black Death (1348-51). 4 c. Population growth and income per capita European population 400 BCE to 2000 CE Source: Persson/Sharp (2015), p. 48. Population (in mio.) and GDP per capita in 1990 international dollars, 1500-1800 GDP per capita Population GR GR 1500 1800 % per year 1500 1820 % per year GB 1068 2082 0.22 3.9 21.2 0.53 Netherlands 1141 1974 0.18 1.0 2.3 0.28 Belgium 1467 1497 0.01 1.4 3.4 0.28 France 1063 1126 0.02 15.0 31.3 0.23 Italy 1408 1327 -0.02 10.5 20.2 0.20 Spain 783 849 0.03 6.8 12.2 0.18 Portugal (1530) 742 1002 0.10 1.0 3.3 0.36 Germany 1101 1121 0.01 7.2 19.4 0.31 Poland 592 566 -0.01 4.0 10.4 0.30 Sweden 1104 857 -0.08 0.6 2.6 0.48 Egypt 680 600 -0.04 4.0 4.2 0.01 Turkey 482 600 0.07 6.3 10.1 0.15 India (1600) 682 569 -0.09 135.0 209.0 0.20 China 790 649 -0.07 103.0 381.0 0.41 Japan (1450) 548 828 0.12 15.4 31.0 0.22 Mexico (1595) 468 819 0.27 2.5 6.6 0.44 US (1650) 563 1242 0.53 1.2 10.0 1.23 Sources: Broadberry (2021), Table 2, p. 35; Maddison dataset (2018 version), and Pfister (2022) for GDPs per capita; Maddison dataset (2010 version) and Pfister (2022) for population data. Own interpolations based on these data. Some of the estimates, especially for population, are rather guesses. Annual growth rates calculated as compound growth rates. 5 From 1500 populations grew relatively fast all over Europe (in Britain, population increased more than by factor 5!), which is in part due to recovery from the 1348/51 Black Death epidemic that killed about 30-40% of the European population and returning pandemics over the next century that prevented population recovery. In part, this led to higher agricultural productivity (more land per worker), provided some possibilities for women and less favored population groups, but it also hit cities particularly hard and this affected commercial infrastructure especially in less densely integrated areas (where the plague also arrived later, although not necessarily less deadly). Outside Europe, the impact of the Black Death is less clear, but, for example, in Mexico, the arrival of European conquerors and European diseases (e.g., smallpox) reduced the population between 1500 and 1600 (datapoint in the table) from maybe 7.5 to 2.5 million, before (some) recovery began. Similar disasters happened to the indigenous inhabitants of what became the United States, while population growth there after 1650 is the result of continued inflow of European immigrants as well as high fertility among them and their offspring, in a situation of abundance of agricultural land, as well as use of some of the land with enslaved people brought from West Africa. In terms of GDP per capita, the account is more mixed: Strong growth in Britain, Netherlands, Japan, Mexico and the US (see above on these two), as well as in Portugal (but with crisis before 1800). Near stagnation most other Continental European countries Marked decline in China, India (and Sweden). Overall, growth rates even in the fastest growing economies were not very impressive. Remember from week 1: Why was growth slow before 1750/1800? Very local no domestic or international markets -> little specialization no way of dealing with most obstacles or ‘challenges’ of geography Inefficient and poor unproductive agriculture → no scope for specialization and urbanisation too much fertility and too little (general) education Badly organized (and exploitative) serfdom, mita, guilds political and economic institutions unfavourable to investments and innovations little (elite) knowledge and too little of it oriented towards practical problems Status quo oriented and with zero sum mentality society and culture unfavourable to change (conservatism, traditionalism) and individual initiative (community orientation, exploitation logic of elites) Kishtainy: merchants not very popular (Aristotle to Thomas Aquinas), condemnation of interest and money hoarding people saved and invested too little and were not very innovative 6 2. Malthus’s theory of population a. Basic idea “An essay on the principle of population, as it Affects the Future Improvement of Society with Remarks on the Speculations of Mr. Godwin, Mr. Condorcet, and Other Writers.” (London 1798; more details week 3, History of Economic Thought). Basic idea: Arithmetic (linear) increase in food production, geometric (exponential) increase human reproduction leads to Malthusian trap. (Like Covid19-cases growing exponentially, hospital capacity increasing linearly.) FOOD PRODUCTION FOOD REQUIRED FOOD PRODUCED DEMOGRAPHIC CRISIS TIME The basic idea behind this: an agricultural society Why would strong population growth lead to trouble? What to do against it? Or how to use it? Source: W. Sheperd, Historical Atlas, 1923, taken from Wikipedia. 7 b. Greg Clark’s Malthusian model no red. solution, just more poor people Greg Clark (2007) formulated a simple model based on Malthus’ main ideas He uses three assumptions: 1. Birth rates (BR) differ across societies because of cultural reasons, but increase with living standards (reproduction) 2. Death rates (DR) decline as living standards increase Models also work if instead we model independent constant death rates, i.e., a horizontal line in the model 3. Living standards decline if population increases (consequence of more people with essentially the same resources) implication: Society with stagnating population (“Malthusian equilibrium”, BR=DR, no population growth or decline) → life expectancy is the inverse of death rates: if 33 of 1000 people die each year, life expectancy is around 30 (try calculating with 1/3 dying every year). So, in a (productivity) stagnating society you have to restrict births to live long (on average); this is what Malthus called “preventive check”. Otherwise, nature will increase mortality and thereby reduce population with “positive checks” If you want all the details, read the background text “02_Clark 2007 ch 01 02-1.pdf” in Canvas or watch the videos here. A simple model: Malthus according to Greg Clark Source: Clark (2007), p. 22. 8 There are three axes in this graph: one for income (horizontal, repeated), one for birth and death rates (vertical) and one for population (vertical). These axes can be used to illustrate the causal relationships implied in the assumptions, and their consequences: To represent the assumption that as income/person increases, birth rates increase, we draw an upward sloping line on the upper graph (higher income -> higher birth rate, mark as BR) To represent our assumptions that as income/person increases, death rates decrease, we draw a line that is downwards sloping in the upper graph (higher income -> lower death rate, mark as DR). Finally, to represent that as population increases, income per person decreases, since for example more people have to cultivate the same area of land (see slide 18), we draw a downward sloping line in the lower graph (higher income per person -> lower population, or, higher population -> lower income per person) (mark as POP). The precise slope and shape (linear) of these lines is not central to the model (see Clark’s chapters and videos linked on p. 8). The point where BR=DR (intersection of both lines) is the point where population does not grow (Malthusian equilibrium, equilibrium = *). To the income that corresponds to this (y*) corresponds a population (N*) that can be stably fed by this income per capita. At higher income levels, population increases because birth rates rise and death rates fall, at lower income levels the opposite happens. Both processes make population and income return to the equilibrium. If we are outside this equilibrium, if population suddenly declines for example (an earthquake, a pandemic, a war), fewer people (N0 < N*) have a higher income per person (y0 > y*) than before, because they can work with more resources per head (e.g., more land per person in agriculture). This higher income leads to lower death rates and higher birth rates at y0. However, now BR>DR (more babies born than people die), so population grows. As a consequence for an increasing population, in the model incomes decline (less resources per person), and that leads to (again) rising death rates and falling birth rates (as per our assumptions, moving along the lines as the arrows indicate). This continues until population has grown to N* again, with income y* and BR=DR – we are back at the equilibrium The same happens inversely if for some reason population is larger than N*. Such sudden overpopulation cannot be sustained by an income lower than y*. Population thus will shrink as DR>BR (more people dying than babies born) In a way, this model describes a biological model of populations in general, if incomes are thought as basic food, you can also apply this to wolves in a forest, rabbits on a roundabout or elephants in the savanna. But, if humans can adapt their fertility behaviour, the level of N* and y* can be influenced by „reproduction restrictions“ (customs/rules, etc. implementing „preventive checks“ 9 The logic of the lower panel in a nutshell: diminishing marginal returns Initially/at populations lower than N* land/resources per worker is high (newly settled area) High income means high BR and low DR (disequilibrium) As population increases, land/worker ratio falls (or worse land has to be cultivated) Income per head falls in consequence (diminishing returns), causing BR to fall and DR to increase Lower income per head  worse nutritional status  higher risk for diseases and exposure to epidemics. In long run, the economy settles at an equilibrium with constant population (y*, N*) Basic assumption here: One factor varies (labour), the other is fixed (land). If the other factor would also increase, the results would be different (e.g., constant returns to scale). Birth rate change What if the birth rate schedule increases? More babies at any given income (people marry earlier, religion demands having many children) Source: Clark (2007), p. 26. This means that BR line shifts up to BR1 - more babies for any given income/productivity -; for a while population grows (BR1>DR), until a new equilibrium is reached (intersection BR1=DR) with more people and lower income (N1*>N0*, y1* less people dying at any given income is like more babies being born at any given income. On the other hand, everything that increases death rates (war, disorder, disease), in the logic of this model is helpful for material living standards. 11 Technological change What if technology improves? (more income for any given population) Source: Clark (2007), p. 28. Now the “Population” line shifts outward: any given population initially has a higher income per capita – everybody is more productive. Better technology means that the same resources produce more and make more consumption possible. One example would be the introduction of the potato from the South American Andes into Europe – potatoes yield many more calories per plot of land (and corresponding worker) or the introduction of the heavy plough in European agriculture. But an increase in income means more births and less deaths, and more births and less deaths depress income, so that in the long run, only population increases (N1* > N0*, but y*=y*; “extensive growth”). So, the only way to increase incomes permanently in this model is to lower population (by shifting upwards the death rates schedule or – more desirable – shifting downwards the birth rate schedule). We are back at the “preventive check”. 12 c. Preventive checks: The European Marriage Pattern and the Chinese demographic system Late marriages in (Western) Europe reduced fertility (“European Marriage Pattern”): Europe also practiced family planning within marriage. Later and non-universal marriage decreased effective fertility. This made diminishing returns less of a problem in Western Europe. This marriage pattern existed since somewhen in the early middle ages in Western Europe, and probably spread together with the agricultural model underlying the Manorial system, which relied on (dependent) family-farms and a mix of grain agriculture and animal husbandry. Also, the Catholic Church (schisma of 1054 between Catholic and orthodox churches) incentivized clan formation and large households like in the Roman Empire. These ‘survived’ as family patterns in the orthodox and Islamic societies in Southern and Eastern Europe, and were also widespread outside Europe (including in China). In Europe, this difference is generally illustrated as the Hajnal line, a line from St. Petersburg to Trieste, described by Hajnal (1965). Source: https://en.wikipedia.org/wiki/Hajnal_line 13 What we know about women, 16th to 19th century Age of first Lifetime marriage celibacy rates Denmark 27.8 11.3 Norway 27.1 17.3 Austria 26.8 28.0 Netherlands 26.5 9.5 Germany 26.1 11.4 Scotland 26.0 20.7 Switzerland 25.9 19.6 Bohemia 25.2 14.4 England 25.2 11.3 Portugal 25.0 22.7 Spain (North) 24.2 10.0 Ireland 24.2 15.8 Italy (North) 24.1 11.8 mean 23.9 13.2 France (Center) 23.3 10.9 Spain Centre 22.9 7.2 Poland 22.8 6.2 Spain (South) 22.1 10.4 Italy (South) 22.1 12.1 Greece 21.9 5.3 Hungary 20.4 4.0 Romania 20.3 2.9 Croatia 20.0 2.0 Russia 20.0 9.3 Ukraine 19.6 2.0 Serbia 19.6 1.1 Bulgaria 19.1 0.6 Source: Dennison/Ogilvie (2014, 654). In consequence, fertility would be much lower in Denmark than in Serbia or Bulgaria. This might explain differences in income levels, but it is only one contributing factor to the difference in economic performance (as that is ultimately driven more by technology than by population, see below). 14 Female age of first marriage in Asia Taken from Broadberry 2021, Table 6, p. 38 This would hint at high-fertility patterns in Asia, but there is also the hypothesis that arranged marriages (among children) had a negative effect on marital intercourse frequency in China/India (difficult to change roles), and thus on fertility. Also, infanticide (due to son preference) seems to have been spread more widely in Asia and less common in Europe, although recent work by Beltrán Tapia (2016) finds that “Contrary to previous interpretations arguing that there is little evidence of gender discrimination resulting in excess female mortality in infancy and childhood, the results suggest that this issue was much more important than previously thought, especially in Southern Europe. The unbalanced sex ratios observed in some regions are not due to random noise, female miss-reporting or sex-specific migration. (…) The actual nature of discrimination, either female infanticide, the abandonment of young girls and/or the unequal allocation of resources within families, however, remains unclear and surely varied by region.” For more on marriage patterns and their origins and social implications, read also de Moor/van Zanden (2010), “Girl power: the European marriage pattern and labour markets in the North Sea region in the late medieval and early modern period”, and Lee/Wang (1999), “Malthusian Models and Chinese Realities: The Chinese Demographic System, 1700-2000” (and their book One Quarter of Humanity. Malthusian Mythology and Chinese Realities, 1700–2000, which is the source for Broadberry’s data on China reported in the table above). 3. Adam Smith’s theory of market integration and specialization a. Basic idea Adam Smith explains underdevelopment by lack of division of labour and lack of capital. Both have their roots in lack of integrated markets. An isolated village (like the one introduced on p. 7, or in class 1, p. 10) would have to perform all economic activities itself  lack of specialization and division of labour If ‘extent of the market’ (population density, transport facilities) increases, people can specialize and exchange/trade with each other creates efficiency gains from specialization, for example through undisturbed dedication to one thing, i.e., ‘economies of practice’, which leads to higher skill levels  weavers specialize in cloth production and farmers specialize in food production, weavers get better at weaving, farmers get better at farming As a result, specialized producers have different opportunity costs of producing ‘all other things’ (the weavers get worse at farming if they don’t do it anymore). On the basis of increased efficiency and rising opportunity costs (and their basis, economies of practice), exchange enable higher total production and thus higher consumption/living standards 15 But specialization can only be achieved and sustained if aggregate demand is sufficient increase of population density decreases transaction costs lower transaction costs (through more efficient transport, property rights, getting rid of artificial barriers) make transactions over larger areas possible. ‘Economies of practice’ will allow an economy to develop, but this will ‘stagnate’ at a certain level of efficiency once gains from specialization are exhausted – every new specialist has to improve through experience over time (and then dies) Efficiency can continue to increase if there is also ‘learning by doing’, the development of superior technological knowledge and tools that are transferrable between producers E.g., repetition not only improves existing skills, it might lead to discovery of new ways to do the same task and produce things  transferrable skills and tools if specialization is sustained and markets are large, investment in/invention and use of specialized (more capital intensive) tools or more division of labour is more likely to pay off But falls in demand can also reverse this (see page 15) For example, when the (Western) Roman Empire collapsed in the 5th Century (and population shrank due to epidemies, violence and probably lower birth rates)  newly built ships and houses were of much lower quality, pottery looked much more unsophisticated (home-made instead of factory produced).  markets disintegrated, making ships unnecessary, cities unviable (no food available) and large pottery-production plants unprofitable (no access to large markets).  See Scheidel (2017, 264-269) and Ward-Perkins (2005) for more. Karl Gunnar Persson has developed a simple model similar to Clark’s to visualize this. Larger markets make more division of labour possible, and division of labour increases productivity: Persson (2008): “Greg Clark is a master of the art of using one-liners in telling stories and Farewell to Alms: A Brief Economic History of the World is no exception. It offers the Malthusian hypothesis of population growth leading to misery as an all-purpose vehicle for all human history, except for the last 200 years. However, his Malthusianism is at times more evangelical than empirical and analytical. (…) Peter Skott and I worked on this in 1985/6 and did not, unfortunately, think of making technological progress endogenous. Observing, as we did, that densely populated areas seemed to have higher income and productivity levels, it would have made sense to link the rate of technological progress to population as has been done recently in New Growth Theory. That would have turned the Malthusian story upside down and focused on what really constrains pre-industrial economies: slow technological progress, which might be stimulated by population growth! Big history relies on simple stories. It is not big history we need but better history.” 16  Source: Persson/Sharp (2015), p. 30. Division of labour depends on size of population – bigger population enables specialization and „economies of practice“ (A→B) and if sustained better technologies (B→C). There is – collapse of Roman Empire – the danger of population shrinking (C→D) and technologies being forgotten (D→A).  We do see something that might fit A→B→C repeatedly after 1500 (especially in Netherlands and Great Britain, and Japan). New, more capital-intensive technologies only make sense if output is large enough. Source: Paul Sharp‘s presentation for Persson/Sharp (2015), ch. 2. More capital-intensive technologies have higher average costs at lower production volumes than less capital-intensive technologies, that would then explain why they are abandoned in situations like C → D in the graph above (leading to D → A ). See p. 16 for an example. Take-away: While for Malthus population growth is a major problem, for Smith is entails the possibility of division of labour and higher productivity and living standards (if agriculture meets the challenge of feeding those not specialized in agriculture). Outside demand might stimulate agriculture. One consequence would be urbanization, if non-agricultural activities (that do not depend on land) cluster. 17 b. Illustrations Roman Empire and European recovery in Northern hemisphere lead emissions in Greenland ice cap. Source: Persson/Sharp (2015), p. 42. Lead polution, shipwrecks and the Rise and Fall of the Roman Empire, as an illustration of the general Smithian mechanism Source: Morris (2011), p. 288, 308. Please note that the vertical scale in both graphs is the same. In both cases the level of lead pollution and shipwrecks in 1CE [i.e., year 1] is set to 100, and the two time series are indexed to that value. Lead is used to smelt silver, which is used to make coins, and thus money for markets (as long as nobody trusts paper money). As population rises and falls (see p. 5), lead pollution and shipwrecks rise and fall, which indicates that markets (silver coins, transport) evolved and retreated. Archeologists also report basically no minting activity in Britain (as an example) between ca. 410 and 625, when Anglo-Saxon kings produced new coins in very small amounts, and coin production seems to have recovered somewhat more only in the 8th or 9th Century. 18 Windmills as an example of learning by doing and increasing capital intensity: Dutch windmill types The challenge is to move the head of the mill into the wind with less and less effort. The first mill is made of wood, and almost the whole mill is turned around, which requires significant manpower. The second only has the upper body turned around by workers walking on a gallery. The third has only the head moved around, which requires less workers and allows the mill itself to be made of bricks and more resistant and durable. Windmills were the main non-animated power source besides watermills before the invention of the steam engine. Non-animated power sources are relevant as energy input into the economy, as human and animal power require food and feed, which needs to be produced in agriculture (and feeding animals – horses, for example – competes with human food production for the same area). From 12th C. From about 1400 From about 1600 Source: https://de.wikipedia.org/wiki/Windmühle. The pictures are from Northern German museums. 19 4. Combing both theories: a race between diminishing returns and learning by doing a. Basic idea From sections 2 and 3 follows a race between two different sets of forces. Or, in a simpler graph: I write ‘Malthusian’ and ‘Smithian’ because neither Smith nor Malthus explained their theories in the ‘modern’ economics concepts/terms used in the textboxes. NB: Smith did not argue that Malthusian mechanisms did not exist (see here in the Wealth of Nations, the paragraph starting with „Every species of animals“). Malthus also recognized agricultural change but saw it as too slow to be a solution to the (his?) fundamental problem. 20 b. Evidence The first piece of evidence is evolution of the European population on p. 5: there were clearly ups and downs. What is more difficult to say is whether the collapse of the Roman Empire and the Black Death of 1348/51 were Malthusian positive checks, as epidemics and environmental factors played an important role in both, in complicated ways, as did collapse of political order, which also played a role in the non-favourable evolution of the Indian and Chinese economies in the centuries before 1850 on pp. 3-4 (Harper 2018, Campbell 2016). Because data is best, we will focus on the period from about 1500, as on pp. 3-5 above. What we see here is, remember: in most places growing populations and stagnating incomes per capita - this looks like a Malthusian scenario with occasional technological change (p. 12), that is offset for the most part by population growth, i.e., income does not decline, but growth is ‘extensive’. In some countries, in the European context mostly Britain and the Netherlands, we saw slowly rising incomes and marked population growth. Estimates of agricultural productivity, 1300-1800 Source: Allen (2003) Agricultural productivity did not change much in Italy, Spain, Germany, Belgium (the Austrian Netherlands), but did increase in Netherlands and England, especially after 1600. In Belgium it stagnated on a high level. This means, agriculture met the challenge of growing populations somehow. How did (European) agriculture manage to become more efficient? Examples of changes in agriculture before 1800 Use of animals for ploughing: Invention of better harnesses and of horseshoe Invention of better ploughs (or ploughs better suitable to local soils), e.g. the mouldboard plough which cut deeper into the soil and released more nutrients for plants Intensification of land use more intensive crop rotations (less fallow) 21  Draining wet lands so they could be cultivated, irrigation infrastructure for dry lands. Incorporation of nutrient-restoring crops into rotation (pulses like clover and lucerne), which could be used as fodder for animals Using animal fertilizer (and in some parts urban night soils) Using seed drills to increase the share of seed actually leading to plants Keeping animals in barns instead of on land Requires solving some animal health problems Allows to milk them better, to collect and treat fertilizer more efficiently, and to use them all year round Reacting to increasing demand from cities for higher value foodstuffs and use of animals for raw materials Gardening for vegetables and fruits close to, say, London and Amsterdam provision of wool, hides and skins, etc., for export industries (not food-related) Production of meat and dairy products (milk, butter, cheese) Increasing urbanization Population not only grew, but became more urban – people left agriculture, in England and the Netherlands more than elsewhere. Italy was a forerunner from 1200 but stagnated after the Black Death. Source: Persson/Sharp (2015), p. 41. The increasing size of cities, in this case, particularly London, also indicates increasing division of labour, specialization, and probably economies of practice. But not all cities experienced such growth, agglomeration, and diversification (e.g., Winchester apparently did not experience growth while economic activity centred on London). The growth of London (and Amsterdam) was not just fueled by increasing national/domestic agricultural productivity, but also by market integration with other countries, where grain production was cheaper (more land per person, but maybe also due to institutions that prevented wages to rise, like serfdom). This process was similar to the pepper market example in week 1, but within Europe. Imports of pepper, nutmegs, clove, sugar, tobacco into Europe also contributed to the growth of cities like Amsterdam, London, Liverpool or Bristol, all hubs of European trade and trade with newly conquered territories outside Europe, where Europeans frequently re-organized economies in a very exploitative way. 22 Number of different occupations in cities Source: Persson/Sharp (2015), p. 40. Market integration after 1500, one example: Price ratios for rye: Price in the Netherlands (Groningen) divided by price in Baltic (Gdansk), 1500-1800 Source: Price database Robert C. Allen; W. Tijms, Groninger Graanprijzen (Groningen 2000); Ratios of decadal averages of prices in grams of silver per liter. Shaded area: interpolated (no data). Remember the pepper price example in session 1, p. 9. The technique here would be dividing England prices by India prices in that graph. 23 c. One salient example: London and preindustrial growth in England A real-life example of how all that might have worked together: London and the Industrial Revolution In the 17th Century, London became a trade hub for British international trade with the European continent and the newly acquired British colonies in India, North America and the Caribbean people went there because income was higher or because there were jobs (in trade, in ports, in the Navy, as servants) which did not exist in the countryside Based on Wrigley (1967), “A Simple Model of London's Importance in Changing English Society and Economy 1650-1750”, between 1650 and 1750, the population of London increased by 275,000 people (from 400,000 to 675,000), or 7% to 12% of all English population (urbanization and ‘Londonization’ of England) To make this possible, agricultural productivity must have increased, since more non-farmers could be sustained (the rest of English cities did not decline in population). Wrigley calculated productivity growth of 0.1 to 0.2% per year (not much, but a slow and continuous displacement of the productivity schedule). Following Malthus/Clark, this would make population grow: Agricultural improvement, specialization and productivity growth. London’s impact on England In London itself, however, sanitation was bad and life expectancy was short (about 27 years, compared to 35–38 years in Britain as a whole, see week 1, p. 13) Crude death rates exceeded crude birth rates by at least 10 per 1,000, so the population out of itself would shrink by 1% per year (some 5,000 persons in 1600, when London probably had 500,000 inhabitants) – sanitation was bad, many parts were like slums today. some 7,000-10,000 people would have to go there every year to overcome the “burial surplus” and make the city grow as calculated above, and these were on average rather young Outside London, birth surplus was maybe 0.5% per year (50 per 1,000). But those going to London made up a significant share of those who survived to age 20. Since death rates were higher in London, this would slow down population growth for all of England, without brining it to a halt 24 So, death rates were higher than without London, leading to a (naturally) shrinking population in London, and a lower population in England (ceteris paribus) than if London had not existed/grown. But, since both happened at the same time Population did not decline as a consequence of the higher death rates, but grew less than otherwise, because increasing incomes fostered population growth. This is because the effect of the death rates is offset in part by the effect of technological change which also goes along with urbanization – and urbanization would lead to Smith-like learning by doing, etc, and thereby sustainably repeated outward shifts of the “Population” line, which we can understand as the Smith/Persson version of that schedule (y0 to y2 and further, the dashed line), with a non-stable situation to the right of the Malthusian subsistence income sustained by (mainly) repeated technological change due to more division of labour and increased agricultural efficiency and food imports (in exchange for exports of manufactured products, so international division of labour) plus the ‘burial surplus’ produced by bad sanitation in London (and possibly, different fertility in cities in comparison to the countryside, and thus social change – this would be a change in the birth rate schedule, which is not modelled here). 25 5. So, why was growth so slow? ‘Bad’ institutions and little innovativeness Institutions are the rules of the game therefore define and influence the opportunities and choices of individuals Individuals will only take actions that are economically rewarded; whether this is the case or not depends on the institutional framework are usually explained by their efficiency-enhancing effects, e.g., because they internalize externalities and decrease transaction costs but this does not need to be the case: if institutions and therefore incentives are not working in favour of ‘social welfare’, the expansion of productive potential (necessary to overcome diminishing returns from inputs and current level of technology) can be slowed down Institutional persistence and economic (in)efficiency Since they are social choices, institutions can be changed Theory in its most simple form would suggest that competition will ensure that more efficient institutions will replace inefficient ones (because they are pareto-efficient) However, institutions are made in a political process, which does not necessarily follow an economic logic of competition and efficiency (but one of political power):  winners from a new situation have to be able to “overrule” potential losers that benefit (extract “rents”) from current arrangements (“vested interests”) in a political process (the field of political institutions where economic institutions are made). the political process does not. Therefore, inefficient institutions can exist and survive because they serve the interests of social groups with political power. Examples are often interpreted as monopolies or cartels – in the following we focus on serfdom Serfdom Serfdom was the institutional framework of much of agricultural production in Europe, and similar systems existed in other parts of the world (see remarks in week 1, p. 10, and illustration on p. 9) The rise of serfdom Labour shortage (population decline after the collapse of the Roman Empire) Large insecurity – warlords, invasions, little centralized authority High concentration of land in the hands of lay and ecclesiastical landowners What state there was cooperated with the aristocracy (and church was part of it) Small and declining independent peasantry (but still a substantial part, maybe 30%, but with large regional variety) So, under serfdom, landlords (which with low population density would not have been able to charge land rents) offered protection for land rents and social control Asymmetry in weapons and access to higher authorities and world outside the Manor Landlords offered lighter burden in areas with higher opportunity income for runaway serfs 26 Why was serfdom persistent, despite its inefficiencies? Serfdom meant labour was not free Serfs given small plot for subsistence agriculture A percentage of output was given to the lord as rent And / or forced work on the lord’s estate (corvée) No freedom to leave for a ‘better’ lord, control over marriages, inheritance, etc. No labour markets No real land markets No competition between lords for serfs (sort-of cartel) High monitoring costs and incentives for serfs to shirk when working for the lord Little incentive for specialization or innovation, no urbanization Decline of serfdom (in Western Europe) Consensual and driven by market forces: Relative peace and stability enabled population growth, this made land valuable – and led to commutation of many serf obligations to money payments Growing incentives to defect to cities, other estates, areas of land reclamation → gradual relaxation of labour services After Black Death (1348-) situation turned around, landlords were competing for scarce labour; in a more stable environment, they could not easily undo former consensual reforms Earliest decline in the Low Countries; enabled transition to more sophisticated land and labour markets In Southern and Eastern Europe either serfdom did not emerge (latifundia agriculture and extended families) or, because of low population densities, the commutation did not happen and the (milder) shock of the Black Death led to a retightening (‘second serfdom’) of conditions until the mid-nineteenth century (e.g., Russia: 1860). Other market-unfriendly institutions Open fields (in agriculture) communal agriculture on shared fields instead of individual’s farmers production decisions – said to minimize risk, but heavily ‘do as always done’-bias Usury laws that restricted financial development, lending and investments (but permitted land rent, based on the idea (Kishtainy, ch. 3, yields of land are ‘natural’, but yields of money or not) Monopolies, privileges and bounties (subsidies) for all sorts of economic activities granted by governments on non-economic grounds (corruption, patronage, etc.) Adam Smith saw mercantilist economic policy as a system of such market restricting and distorting practices, although he tolerated some for national security and other reasons 27 Guilds local (privileged) groups of people with the same profession - cartels of bakers, butchers, etc., often seen as cartels who regulated/limited access to, training in a profession and the marketing of products, thus restricting ‘free’ markets might have helped to standardize learning by doing (through training and quality standards) Ogilvie, The European Guilds: An Economic Analysis: “I am in a way sad to say that (my analysis) found very little evidence that guilds solved failures in markets for quality or human capital investment or innovation. Instead […] they imposed entry barriers, they manipulated markets in favour of their own members, they oppressed their employees – guilds were associations of […] small business owners – and, I am sorry to say, they ripped off customers.” In general: lack of inclusive institutions (‘democracy’, ‘accountability’) that might make sure that everybody’s interests are taken into account when rules are made, and that thus everybody can reap the fruits of investments and inventions. 6. Wrap up More division of labour and less diminishing returns made development possible, based on market- friendly institutions Source: Persson/Sharp (2015), p. 68. London’s impact on England shows how population growth and market integration fuelled division of labour and productivity gains, while also (somewhat) slowing down population growth. Some of this relied on creation of economic hubs in a growing world economy that relied on conquest and exploitation outside Europe. Also, as London grew (and burned down repeatedly), heating with wool became a problem and coal-fired houses with chimneys, made of brick replaced wooden dwellings with open fires for a large part of the population. This meant increasing energy use (in heating, brick-making, etc.) which accompanied the rise of London, urbanization and increasing division of labour. So, The growth of London was also the (slow) start into higher consumption per capita (heating houses with coal) – Amount of energy used to produce GDP/income 28  1000 Energy Intensity of GDP (MJ/1000 50000 1990$) 40000 35000 100 5000 30000 25000 20000 15000 500 10 10000 1756 1560 1609 1658 1707 1805 1854 1903 1952 5000 GDP capita 1990 US$ 0 1893 1930 1560 1597 1634 1671 1708 1745 1782 1819 1856 1967 Per capita energy consumption (GJ) Source: data from Warde (2007) and Broadberry et al (2015) / Maddison dataset 2013 – since 1872 energy use per GDP declines (i.e., how much energy is needed for a given amount of income/production value), but absolute energy use per person still increases (also not corrected for exported or imported energy in commodities) – ‘rebound effect’. 29 7. Bibliography Allen, R.C. (2003). Progress and poverty in early modern Europe. Economic History Review 56(3), 403-443. Beltrán Tapia, F. (2019). Sex ratios and missing girls in late-19th-century Europe. 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