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S1 Introduction to course
Essential of the course is: a) Why do economies grow? b) What does economic development mean to people? Between countries, inequality has been falling for the last decades. Yet, within-country inequality has been rising in all most countries. 75% of income inequalities are now within-country! For a long time, wages and productivity grew together. From the '70s, their growth has started to diverge and has continued ever since. When the development of productivity is greater than the growth of wages, unsustainable inequality will be created, leading to the rich becoming richer and the poor becoming poorer
"The great globalization lies":
"Openness to trade always hurts some people in society." Meaning that when a country/region grows mainly thanks to a specific sector, only those within that sector enjoy the growth. Other people will be driven away since the cost of living in the area will increase to match the richer salaries and not the unchanged ones. The course is centered around five major questions:
- What are the significant determinants of the growth of regions/countries?
- How does the distribution of economic activity within and across countries and regions arise and develop?
- Can this distribution be influenced by regional/development policy?
- How does economic development affect the allocation of resources and rewards within societies?
- What are the demographic aspects of development, and what is women's (changing) role in the development process?
S2: Regional Economic Distribution
In the discussion over regional economic distribution, there is the debate over what a "region" really is… by changing the definition, you obtain significantly different results "Capital regions tend to be the most productive of their countries with few exceptions, which is usually a direct result of having a higher population. Higher population typically lead to higher productivity which in turn attract more people increasing productivity leading to a virtuous cycle for the city, which however also increases regional disparity within the state Benefits from being co-located with others: Manufacturing supply side: o Thick labor markets of the specialized workforce. o lower transport costs and concentration of suppliers Services demand side: o Attract more customers (market thickening), also more concentrated in the specific sector that the cluster specializes in Both knowledge spillovers: o Benefits from knowledge produced by others through pure externalities (agglomeration) and knowledge exchange (clusters). o Knowledge spillovers.
N.B.=” knowledge sharing” most of the time means stealing ideas and employees from other companies with the risk of the same happening back to you. Krugman and others show us that the spatial distribution of economic activity ends up being concentrated. The lower the transportation costs, the more concentrated economic activity; this raises the question of what determines the initial distribution of economic activity. Davis and Weinstein (2002). 3 main theories: I. Random growth: City/population and economic growth is a random process. The city size distribution in a given country follows a mathematical regularity known as Zipf's law. If we rank cities in the base of economic output in a Country, by dividing the rank, we see an equal division in the population (half rank= half population) II. Locational fundamentals: The characteristics that facilitate city growth are randomly distributed. City growth is determined by location characteristics that are randomly distributed. This theory still builds upon Zipf's law E.g., Coastal locations have transport and food advantages, Flat open plains have advantages over mountain ranges, Natural resources (oil, gold, coal, etc.) provide benefits over locations without such endowments. Many places have none of these characteristics, some have a few, and few will have them all. Such a process can also explain Zipf's law. III. Increasing returns: (Marshall & Krugman). Economic activities benefit from being co-located: Knowledge spillovers (reverse engineering, labor mobility) (in)formal collaborations Input and output market thickening These benefits vary over time (especially great reasons for concentration in and after the industrial revolution) and across industries, with shifts in the location of density and with not all industries being equally affected. However, path-dependent processes might diminish these variations (Path- dependency= the idea that past choices influence the future), leading many people to stay in a city even after their employer failed. They could move elsewhere, and the fact that people remain might spur new growth. Davis and Weinstein analyze almost 8000 years of population data for Japan, an isolated State historically. Predictions: Increasing returns: variation in population density should be much higher in modern times than in agricultural and pre-agricultural economies. No persistence in the most densely populated regions especially compared to locational fundamentals Random growth vs. locational fundamentals: the main difference between these two theories is the effect of large shocks on population density. long-lasting (unexpected increase) vs. only short-term (locational fundamentals) effects. Sufficiently large shocks should also have permanent effects according to increasing returns as it would alter the region's relative position. Empirical evidence: There has always been a great deal of variation in population density and persistence in the degree of regional variation, which doesn't fit with increasing returns and random growth, but holds locational fundamentals Population shocks – a natural experiment: WW2 Bombings. 66 cities were targeted, half of the structures and 2/3 of the productive capacity in these cities were destroyed. Random growth - shocks should be permanent
Benefits of Cluster: I. Sorting= Clusters attract more productive people and firms II. Sharing= Large market attract specialized suppliers and creates a large home market. III. Matching= Specialized labor is matched efficiently to jobs in which those people or most productive IV. Learning= Knowledge spillovers, labor mobility, and collaboration lead to geographically bound knowledge flows Assuming interconnectedness between companies in a region, see Knoben (2008). Firms in agglomerated areas are more likely to connect to other local firms. Still, some firms are physically in the middle of the cluster but not connected. In contrast, others are not physically present in the cluster but still interconnected. Can a company in the middle of the geographic concentration be 'outside' the cluster if it only does business with outsiders? Yes, according to Funk (2014). And those outsides of the cluster (geographically speaking) can still benefit from it. The network dimension of clusters seems dominant over the geographical proximity element of clusters. However, it is easier to be physically present in the cluster, at least at the onset of the firms, to build the network with existing firms and suppliers. Once it is established, one can move out and still remain interconnected. Thanks to digitalization, many cost-minimizing effects of agglomerations have diminished, making it not necessary to be "place-bound." Services used to place specific become footloose – tradability, and IT makes codification of knowledge more accessible. This can reduce the distribution chain, causing revenue concentration in the hands of fewer people in the producing companies. This causes the emergence of Winner takes all markets: when one firm can take (almost) the entire market because scaling and transportation costs are nearly zero. There are no trickle-down effects as the product and/or service is delivered digitally, so no local retailers or supply chain is needed. Activities will cluster in fewer and fewer cities to work digitally. They will attract more people leading to a higher likelihood of new big companies. "Even as old reasons for clustering have diminished with globalization, new influences of clusters on competition have taken on growing importance in an increasingly complex, knowledge-based, and dynamic economy." (Porter 2000, p15) However, working digitally lacks social depth and trust since there is no face-to-face interaction. It will make surface-level exchange and services more accessible, but not anything below that. This is why geography still matters and probably will for a long time, especially for knowledge sharing of "Tacit Knowledge," which is the knowledge transferable only by sitting next to someone and guiding them throughout the process. Technology is excellent at maintaining relations and communities, not so good at creating them! No two clusters are the same, but some dimensions/characteristics seem key The concentration of economic activity Centered around a particular industry/technology Knowledge is produced and exchanged within the cluster What do clusters produce Three 'products' of personal relationships, face-to-face communication, and networks of individuals and institutions that interact:
- Increases in (static) productivity thanks to specialized inputs and employees, access to information, complementarities, access to institutions and public goods and incentives, and performance measurement
- Increasing innovation and productivity growth is easier to perceive buyer's needs, technological opportunities, and (un)intended knowledge exchange risk of lock-in/groupthink.
- Stimulating new business formation with Spin-offs/outs Attracting start-ups from elsewhere due to favorable locations But clusters are also experts at 'killing' start-ups since the relationship between the cluster and performance is ambiguous at regional and firm levels. Some firms will benefit from being in the cluster, while others would be better off moving out. Different types/dimensions of clusters: Urbanization – diversity effects (essentially the old-fashioned agglomeration) +: proximity of diverse economic activities, complementary products/services, and technology -: input competition and high costs of doing business Localization – specialization effects +: imitation, business interaction, and labor mobility -: output competition, imitation risks Knowledge intensity – sticky knowledge effects +: knowledge externalities (e.g., patent citation effects), easier collaborations (f-2-f effects) -: spill-outs, presence of skillful competitors Policymakers worldwide try to establish new clusters, but efforts fail because there is no recipe to replicate clusters. However, it is a topic that really interests policymakers since it can lead to considerable economic growth in the desired region. To wrap it up : Cluster: A geographical concentration of interconnected companies, specialized suppliers, service providers, firms in related industries, and associated institutions in a particular field that competes and cooperates. This is an excellent (deceptively nice) definition, which hides a lot of variety in clusters (content and scale). The benefits of clusters are linked primarily to face-to-face contact, personal relationships, and the resulting knowledge exchange; however, clustering is not always beneficial to (all) firms Policy instruments are imperfect at 'creating clusters' since the location of clusters is often primarily due to chance/luck.
S4 (Regional) Economic Growth
Growth will determine more than other income levels in the long run because a State with higher growth will eventually catch up with others. Given its importance, it is not surprising that there is a long history of studies/models about economic growth: Harrod-Domar model Solow-model Endogenous growth theory
The Harrod-Domar model
g = s/Θ – δ g= Growth rate Growth only depends on:
- saving rates s
- (Inverse of) capital productivity Θ
So, the trick to 'developing' successful clusters is making sure that the growth poles of the future are located in your area. However, it is impossible to know the future growth poles. So, the best' strategy' is to attract and retain as many start-ups as possible before they blow up.
Evolutionary growth theory
Like in Darwin's original Evolutionary Theory, there are random mutations (innovations), and successful ones are retained. Successful mutations will lead to replication and attract new similar but related companies to the area. Mutation : company develops a new product/process/service called a 'routine.' firms with modifications will compete with companies that follow the old routine to provide the same service Selection : companies with the best routine survive the competition. Replication : Routines passed on through imitation of the successful companies and spin-offs. Replication processes are influenced by geographical space. Once the routines settle somewhere, they trigger a path-dependent and geographically bounded process of selection, replication, and further mutations. This is because "innovations" are often simply recombination of already existing ideas circulating in poles where distinguished people are because of a breakthrough mutation. This triggers a new line of thinking within-cluster theory: The importance of related variety (see Aarstad et al. paper). According to this theory, both clusters and cities with diverse specialties can push new mutations that bring different technologies and skill sets together, leading to: Reduced the risk of lock-in Increases the likelihood of inventions To Wrap it Up Economic growth is significant Models predict decreasing return to scale unless new inventions emerge Technological progress is endogenous and spatially bound to regions/clusters; hence we observe significant differences in growth rates between regions within the same country Cluster emergence is an evolutionary process that starts with new innovations/routines that cannot be directly steered by policy (in terms of moving firms) but can be influenced by them.
S5 specialization vs. diversification. How to stimulate the
regional economy? GUEST LECTURE I
Regional economic policy has two extreme aims: I. Equity : reduce differences in welfare between regions. Stimulate/support industries in less well- developed regions II. Efficiency : stimulate best performing regions or industries. Increase in overall welfare at the national level also to poorer areas through the "trickle-down" effect. In the Netherlands, the primary approach is called "Top Sector," which relies heavily on efficiency by forgoing the regional dimension by simply focusing on the best-performing sectors and industries in the country. The main criticism is its lack of a regional plan. This approach also stimulates high regional competition. In the "Top Sector" approach, this is done by attracting massive (and usually foreign) companies in the specific sectors ignoring regional development. Attracting big companies to poor regions results in cathedrals in the desert, which might move out again in the short term.
Regional conditions matter for firm success. In the long term, focusing on the regional dimension is more fitting since it is not wise to keep investing heavily in what is performing well already because extreme specialization increases sensitivity to shocks. EU 'Smart Specialization Strategies focus on: Avoid top-down, spatially blind policies Tailor-made interventions, acknowledging place-specificity of natural, institutional resources, and knowledge (Im)material linkages between places Focus on transformation: stimulate new activities rooted in the regional resources The S3 uses region-specific interventions to transform regional economies to sustain their long-term growth by playing on the region's strengths.
From specialization to related diversification
What happened to Detroit is known as "lock-in" or extreme specialization in one specific region, making it an easy target for decline if the sector stalls or gets drastically innovated somewhere else in the world. "Rather than attempting to capitalize on the possibilities offered by the emergence of superior new substitute technology, firms vigorously defend their position through the accelerated improvement of the old technology." Rothwell & Zegveld, 1985 Adaptation: Increasing specialization of resources to "perfectly fit the existing environment" mainly through innovations reproducing existing structures. Adaptability: Notice and respond to new developments (market, technology) High adaptation but low adaptability means that the region will have increased productivity when things go well but an absurdly high risk of failure. Vice versa, high adaptability, but low adaptation means good resistance to shocks but lower overall productivity… related diversity is the best of both worlds by building on the overlap in the knowledge base of different industries. How to identify related diversity? There are many different indicators, the most telling of which is an analysis of firms' knowledge base through their employees, therefore an analysis on Human Capital. What is human capital? Education (generic) Working experience (sector-specific) Measuring firms' skill-relatedness by looking at inter-sectoral mobility because you can understand which sector has a joint knowledge base specific to the industries. Inter-sectoral job flows, therefore, indicate (partial) overlap in knowledge How to improve related diversification? This can be done by considering how the existing structure affects new opportunities through a process of "Branching out" (Frenken & Boschma 2007). Confirmed by empirical evidence: Industries related to the current regional portfolio develop, grow, and survive while unrelated existing industries eventually disappear. Identify industries associated with the existing regional portfolio potential using skill-relatedness. For each regional 'top sector': identify the related industries. Implications for regional policymakers: Stimulate different but related industries Being active in various markets means being less sensitive to shocks
The human development approach focuses on improving people's lives ; it gives people more freedom and opportunities to live lives they value. T herefore, it is, fundamentally, about more choice. It is about providing people with opportunities, not insisting that they use them. Focus at the beginning on three dimensions (HDR, 1990, p.10): I. Leading a long and healthy life II. Being educated III. To enjoy a decent standard of living Since then, the concept of HD has evolved continuously. Human Development Index (HDI) Indicates the level of human development of a country in just one number; this is a strategic choice to make it as simple as GDPc, but at the same time covered a much broader concept of development. Three dimensions: I. Health is indicated by the country's life expectancy at birth. II. Education is indicated by the country's mean years of schooling and expected years of education III. The living standard is indicated by the gross national income (GNI) per capita Criticized because still too crude to measure development well. The HDI is the geometric mean (because it punishes a country for having a lower value in one of the three categories) of the three indices. The differences between the regions of a country are key. In the wealthy West, remote areas primarily enjoy the same infrastructures as the capital region. Still, there is a basic infrastructure in the capitals in the developing world but little outside of that context. Subnational indicators are needed to develop effective policy measures to address economic, social, and medical problems. Factors influencing development Spread of knowledge: There is a strong correlation between income growth and Human development (measured through HDI). However, no increase in national income is needed to improve health and education. There has been a spread of knowledge worldwide; developing countries could improve health by taking over the innovations developed in rich countries. Likewise, a strong connection between learning and education space shows an increased demand for education in emerging countries. For improvement in education and health, no increase in National income is needed Institutions & policy: a strong correlation between inequality and human development; this can be easily understood. Inequality means that the lowest groups get minimal resources, including education and health. Solution: Taxing the high-income earners and (company) profits to increase public spending on health, education, and other services which benefit all population groups. Labor market and migration: low-income countries have difficulty developing because they are highly agricultural. They are a non-productive sector with much of the farming products kept for internal consumption. There are high migration waves towards cities and more prosperous countries in low-income countries, promoting further poverty in rural areas. Technology & innovation: in the last 20 years, there has been a mobile phone revolution also in poor countries; mobile phones are expected to stimulate economic growth due to more efficient markets and lower economic growth, also giving producers a higher insight into the market prices of goods and are less dependent upon others. Stimulating the development of the new service sector based around technology. Demographics (next lecture):
S7 Poverty traps in developing countries. Guest lecture
What are the signs of poverty traps?
- Stagnant low real GDP per capita : Countries suffer stagnant low-income levels over long periods.
- Social immobility : poor individuals remain poor, and wealthy individuals become richer over time. The two can occur together or separately: Low income at the country level could occur, with considerable income mobility at the individual level. Rising income at the country level could coincide with pockets of stagnation at the personal level within the country In some countries where incomes are high or are rapidly rising, social mobility remains high. Poverty traps could be due to differential access to resources: The poor are endowed with poorer or fewer resources, cannot borrow, and do not have a buffer to recover from shocks, and network with other poor people, causing signaling or learning effects. Poverty may also occur if deprivation drains psychological resources, or the poor have immutable traits Why do people stay poor? I. The poor have the same opportunities as everyone else, so if they work in low-earning jobs, they must have traits that make them unsuitable for other occupations. II. The poor face different opportunities and do low-earning jobs because they are born poor. Poverty is a consequence of individuals operating with an unfavorable external environment III. The poor have to engage in a day-to-day struggle for survival, and there may be a self- reinforcing dynamic at work through the choices that are made under extreme scarcity that keep those with poor initial endowments off human capital, poor over time and across generations Working lives of women in rural Bangladesh allocate over 80% of hours worked to three activities:
- Casual wage labor/ maid services
- Agricultural labor
- Livestock rearing Casual wage and agricultural labor are hired daily without guarantee of future employment. Poor women allocate most of their work to low-return, irregular, casual jobs and stay poor. More affluent women specializing in high-return, regular livestock rearing become richer How will poor women behave when they are given cows? S-shaped wealth dynamics: At the threshold, some women in the program slide back into poverty while others accumulate assets over time. Poverty threshold = 2.3 (450$, which is approximately the price of a cow). Long run differences (especially after year 4) between those who received the asset transfer and those who did not suggest that it is difficult for households to escape poverty without any intervention. Among those above the poverty threshold, net earnings are due to increases in revenues from self-employment, suggesting beneficiaries switched into new occupations they had been excluded from. Behavioral poverty traps: Poverty makes households less optimistic about the future and less willing to save and put the effort. Those in poverty devote much of their effort to meet their daily needs, reducing their ability to
I. An increase in income will entice women to have more children (children are ‘normal goods’). II. An increase in income will lead to a lower rate of death. III. An increase in population will reduce per-capita income because the output is (i) limited by a fixed factor of production: land, and (ii) faces diminishing returns to labor. At any population level, the per-capita income will either (Inversely) lead to more deaths or births, bringing per capita income to a new level that will, again, influence the birth and death rate in a cycle that will eventually lead to an equilibrium. Technological progress has a short-term positive effect on per capita output, which is lost in favor of a long-term increase in population. Iron Law of Wages: Real wages always tend towards the minimum salary necessary for 'subsistence.' Empirical implications of the Malthusian world: Technological growth increases the population's size. Technological development has 0 effects on long-run per capita income. Population growth decreases short-run per capita income. "from the laws of our nature some check to population must exist , it should be checked from a foresight of the difficulties attending a family and the fear of dependent poverty [= Preventive Check] than that it should be encouraged, only to be repressed afterward by want and sickness." Malthus believed that the government shouldn’t get involved in poverty policies because it has no point in the long run simply delaying the inevitable. Households should have preventive checks, intended by Malthus as abstinence, where families decide not to have children due to their lack of finance or a poor state of the food supply chain. Our model so far produces an implausible state of stability. Actors in our model are entirely rational with perfect foresight and with no shocks. However, raising a child is primarily a matter of emotion or randomness, and households may not have complete information (or really care) about the current state of the food supply chain. Malthus argued that population growth continuously outpaces technological progress. The result is the worst kind of Positive Check : the Malthusian Catastrophe. An external shock such as a famine or a war that brings the population back to the point of equilibrium with resources and technology (Positive in the sense that it brings back the system to equilibrium)
Population Growth and Economic Development, POVs
Pessimists : Population growth harms economic development, and a higher population leads to a lower income per capita. Two theories: I. (Neo)-Malthusianism: Population growth exceeds technological progress. Ultimately, humans will reach some constraints (food supply and climate change/space limitations). II. Diverted Resources: Rapid population growth induces people to invest in social capital assets (education, health) that are good long-term but not short-term output. Optimists: Population growth positively affects economic development (only in countries with good governance): A more significant population stock increases human ingenuity if governance allows. If people are free, they will invent, spurring technological progress. Two theories: I. Simon Kuznets : Larger societies = economies of scale, better able to develop, exploit and disseminate increasing flows of knowledge II. Julian Simon / Ester Boserup : Population growth pressures humans to innovate. The boserupian model shows that the population grows exponentially, leading to innovations. Such innovations allow technology to grow hand-in-hand with the people and never reach the moment when the population is higher than resources, leading to the Malthusian catastrophe.
Neutralists: Population growth does not affect economic development (or at least it receives disproportionate attention in the policy debate). Three key results: I. Natural Resources: Population growth does not have a solid empirical negative effect on natural resource depletion. II. Savings: No empirical negative effect of population growth on savings III. Diversification of Resources: Population growth only slightly redirected investments for physical capital into social capital (health & education), the returns to which take much longer to materialize
Unified Growth Theory
Oded Galore’s Unified Growth Theory captures i. Modern growth dynamics ii. Malthusian era. First, the Malthusian trap persists as population growth outpaces technological progress: As the population grows, technological progress speeds up due to scale economies (similar to Kuznets). Then, there is the escape from the trap: technological progress grows faster than population size. Human production has become increasingly complex. We require human capital , which kickstarts a substantial increase in technological progress: the main reason for sudden significant increases in growth. Decreased mortality and increased returns to human capital reduce fertility and speed up technological progress This leads to a fertility transition ( Demographic Window of Opportunity ) and ultimately the sustained per-capita growth path that we experience now.
The Demographic Window of Opportunity
The demographic structure of a developing country is characterized by a high quantity of young people. However, as the country becomes more developed, the “Demographic Pyramid” becomes thinner and thinner at the base and becomes almost “bell” shape. The Demographic Window of Opportunity Stage 1: Traditional phase - both birth and death rates are high, the population is stagnant. Stage 2: Due to the rise in income and technological progress, the death rate begins to decline, birth rate remains high. Stage 3: due to human capital, birth rates decline substantially. In contrast, the decline in the death rate slows down (since all technologies that can prevent avoidable deaths are being implemented already). The decline in birth rates, however, is not enough, and the population keeps growing Stage 4: Ultimately, the population stabilizes at a higher level, where birth rates stay a little below death rates. Crombach & Smits (2021) introduced a categorization of the demographic window like the following: Phase Popo U15 (in%) Popo over 64 (In%) traditional >40 - Pre-window 30-40 - Early-window 25-30 - Mid-window 20-25 - Late-window <20 < Post-window - >
The lower the dependency ratio, the higher the economic growth. However, the effect is more negligible if it happens in an urban area, where the demographic dividend is almost close to zero. Economic growth (measured through the IWI) is also significantly higher in the pre, early, and mid phases of the demographic transition. In terms of other variables, the demographic dividend increases if any of these 3 variables increases: Male education Initial development Country-level governance The zones that enjoy the most demographic dividend are rural areas with an initial level of development, resources, and male education.
Today’s Recap
We discussed how the world transformed from a harmonized and stagnant low-income state to a diverse and growing high-income state. The Malthusian Theory of Development explains the static low-income state by the fact that population growth will always prevent increased income per capita due to it exceeding technological progress. We also learned about alternative mechanisms through which population growth affects economic development offered by the population negativists, optimists, and neutralists. We discussed Oded Galore’s Unified Growth Theory, which allows countries to escape the Malthusian Trap in one overarching model and identifying a Demographic Window of Opportunity through which societies can temporarily obtain a Demographic Dividend due to a temporary favorable age structure. We identified the factors that allow policymakers to increase the Demographic Dividend.
