Disease and Economic Growth

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Disease and Economic Growth

By: Alexander Cameron (B00491129) & David Richards
(B00470768)

For: Marina Adshade ECON 3310 April 13th, 2010

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ifferences in rates of economic growth have been the major reason why there exists cross-country and cross-regional differences in income and well being.

Disease plays a role in the complex web of factors that determines the wellbeing of nations. This paper investigates how disease affects economic growth through both direct and indirect causes. The net effects of disease mitigation can be ambiguous, but by isolating individual mechanisms that play a role in this relationship we can uncover it‟s relation to growth. Throughout this investigation we will discuss a variety of economic relationships related to disease and health. A population‟s health directly affects the productivity of individual workers in that healthy workers are more able to attend work and have a higher mental and physical capacity. Disease has indirect effects on growth through increased incentives for human and physical capital accumulation. Disease prevalence also has an effect on population, which in turn can affect incomes and the rate of economic growth. Institutions are greatly influenced by the disease environment of a geographical area and have long-term effects on a nations‟ development. By analyzing the role of these factors, conclusions can be drawn as toabout the net effect of a population‟s health on its rate of economic growth. A nations‟ current state of public health and disease vulnerability are often a result of geographic factors (Auer, 2008; Bolt and Bezemer, 2009). Tropical regions have been plagued by diseases throughout history (Bleakley, 2003) and as a result, have experienced lower rates of economic growth. With higher rates of disease, the population is generally less productive while working and attends work less frequently than nations with lower disease rates (Weil, 2007). In addition to this relationship, individuals make choices about human capital investment and their savings rate based upon the expected payoff. When life expectancies are lower, the payoffs of both savings and human capital investment are reduced resulting in lower human and physical capital accumulation (Weil, 2007). Bolt and Bezemer (2009) also argues that human capital, in the form of education is a prevalent factor of a nations current economic condition – the development of educational and legal systems are affected by the institutions introduced by early colonizers. Disease prevalence also plays an indirect role in determining rates of economic growth through decisions with respect to the institutions that are adopted by the nation or region, especially when assessing colonized regions. Acemoglu, Johnson and

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Robinson (2001) introduce the terminology of extractive and constructive institutions. In locations where disease rates are high and life expectancy is low, colonizers set up extractive institutions that had weak property rights and an unequal distribution of resources. Alternatively, constructive institutions included implementing trade, education and legal systems leading to more productive people and higher rates of growth. O over time, resulted in a growing income gap between nations with good and bad institutions. Bhattacharyya (2009) and Auer (2008) both provide an overview of how disease and institutions can both affect rates of growth. Bhattacharyya (2009) states that solving disease epidemics is most important in the beginning stages of development of a nation. The disease climate and geographic endowments play a role in the institutions that are adopted by the nation, which in turn determines rates of growth when moving through later stages of growth (Auer, 2008; Bhattacharyya, 2009). This series of eight literature reviews and corresponding analysis provides evidence with respect to the role disease plays in economic growth, and together, tells the story of how disease influences economic growth rates.

Since the 1940s tThere have been many technological improvements and public measures taken to improve health care since the 1940s. The period from 1940 to the present is referred to as the international epidemiological transition and is characterized by increases in life expectancy by many nations. These increases can be related to international health interventions, public health measures and the introduction of new drugs and chemicals (Acemoglu and Johnson, 2007). The exogenous shock to health conditions allowed Acemoglu and Johnson (2007) to investigate how health conditions can affect economic growth. Acemoglu and Johnson (2007) use life expectancy as a proxy for health conditions and look for a possible correlation to economic growth rates. They use data from the years in which major medical improvements were made and compare the results to samples from many years prior to determine if there was significant effect on the growth rate. Acemoglu and Johnson (2007) first outlines various exogenous historical events that impacted population and economic growth. The invention of penicillin, in the 1940s, lead to drastic declines in mortality rates as a result of bacterial infection. Other anti-

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biotics soon followed (eg. Streptomycin which is used to treat tuberculosis) which lead to a reduction in deaths caused directly by bacterial infection as well as indirect bacterial infections caused because of weakened immune systems as a result of viral infection. Chemical pesticides, such as dichlorodiphenyl tri-chloroethylene (DDT), were used to control the spread of malaria through mosquitoes. DDT use resulted in eradication of malaria in Taiwan, the Caribbean and Northern Africa, etc. Another source of health improvements comes from the establishment of the World Health Organization (WHO) and the United Nations International Children‟s Emergency Fund (UNICEF). These organizations are active in the advancement and spread of medical technology and organize anti-malaria campaigns and immunization drives. The paper quotes Preston (1975): “Universal values assured that health breakthroughs in any country would spread rapidly to all other where the means for implementation existed.” Using these exogenous factors as a guide, the authors create various economic variables to describe changes in life expectancy and mortality rates specific to particular diseases and countries. These factors are proven to have an effect on both the life expectancy and populations of the countries they examined. A strong negative relationship is found between change in population and predicted mortality. This relationship held for all countries (of various levels of development) that are examined. They also find that an increase in life expectancy is associated with an increase in the fraction of the population under the age of 20, suggesting that it will lead to a trend of population growth. When assessing the impact of mortality and life expectancy of GDP, Acemoglu and Johnson (2007) finds that there is only a slight (and not statistically significant) negative relation between both mortality and GDP and life expectancy and GDP. Acemoglu and Johnson (2007) was unique study in that it exploits many exogenous events that had a distinct impact on economic indicators of health (ie. life expectancy and mortality). The paper finds that an increased life expectancy positively affects population. A higher population reduces the ratio of capital to labour and land to labour, which in turn decreases output per person. As more people enter the labour force, output increases and capital accumulation increases. This increase in labour can counteract the income decreases resulting from an increased population, however if

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factors of production are fixed and fully exploited, the increases of output as a result of a larger labour force may not fully offset the losses. This leads to a degree of ambiguity with respect to the net effect of health improvements on growth. Acemoglu and Johnson (2007) provides historical evidence to suggest that the net change in GDP as a result of health improvements is negative. Though this result is consistent with changes related to the international epidemiological transition, the net effects may tell a different story when assessing other periods of history. Bloom, Canning and Fink (2009) tells a different story of the overall change in well being during this epidemiological transition period.

It is a certainty that widespread disease, especially among third world countries, increases mortality rates throughout the world. Acemoglu and Johnson (2007) concludes that an increase in life expectancy, mostly in underdeveloped or developing countries, due in part to a reduction in disease, has a negative effect on economic growth in the countries. This result appears to be in direct contradiction of many previously published papers that overall health improves economic growth. Bloom, Canning and Fink (2009) demonstrates that there is in fact a positive correlation between life expectancy and economic growth. Bloom, Canning and Fink (2009) analyzes the reasons Acemoglu and Johnson (2007) used to arrive at their conclusion. The first being that poorer countries may have other factors associated with low life expectancy and growth than countries which are better off that are left out of the model. Secondly, less well off countries are obviously less able to attain required disease treatment and medical supplies. The third being the results of mortality and large populations are not correctly measured throughout their studies. Bloom, Canning and Fink (2009) revisit the approach of Acemoglu and Johnson (2007), and attempt to uncover the causes that created results which oppose previous economic works such as Weil (2007) which finds that an increase in health positively affects growth. Bloom, Canning and Fink (2009) first revise what variables are exogenous to the system and why they have been deemed such. The paper finds that a problem may lay in the fact that the Acemoglu and Johnson (2007) model adjusts income simultaneously to any adjustment in health. Through the logic that this is not a simultaneous relationship the paper finds that there is a delay between the increases in

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income and the improvements in health conditions and decline in mortality rates. Bloom, Canning and Fink (2009) supports this theory with several convincing supporting papers arguing that the income delay is caused by a very gradual increase to accommodate the rise in life expectancy. This can be seen in Weil (2007), Bleakley (2003) and Crimmins and Finch (2006) which argue that health leads to an increase in income and growth. These conclude that when income levels increase future generations will be the beneficiaries of medical and technological breakthroughs which increase early childhood health and development. Kremer and Miguel (2004) also finds children subjected to diseases at an early age are more likely to have their educations affected, which adversely affects their adult lives in a negative economic fashion. Bloom, Canning and Fink (2009) finds that the reason the Acemoglu and Johnson (2007) hypothesis contradicts much of the other work is simply because they fail to control for initial conditions. This means that developed countries, or those who were better off in 1940 will receive fewer benefit from breakthroughs because their rate of disease is already significantly lower than that of under developed countries. Since they receive less benefit from said breakthroughs, Acemoglu and Johnson (2007) neglects the fact that the levels of disease in each country were affected by income in 1940. The fact that all countries did not start on a level playing field, and the neglect to take it into account skewed the results to make it appear as though nations with greater incomes were simply not as in need from the benefits of widely available antibiotics and other medical treatment. The lag between economic growth in these countries and the availability of these drugs (or the ability to lower the mortality rate) further strengthens the case that economic growth is not instantaneous. Bloom, Canning and Fink (2009) identifies that there is a positive effect on income in relation to a decrease in mortality and an increased life expectancy. There are several factors that must be addressed in order to fully understand these results and be able to prove that a countries initial health is a cause of the following economic growth. Bloom, Canning and Fink (2009) finds that there are three important issues that must be dissected. They are as follows: a model must be created in order to allow causal inference in order to prove it isn‟t a bias of the model describing their results, the model must always take into account a small converging rate of economic growth towards the

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growing health expectancy rate, and the third is how this affects the scarcity of resources in larger populations. In order to fully understand how technological advances impact growth these questions must be answered. The discrepancy in results between Acemoglu and Johnson (2007) and Bloom, Canning and Fink (2009) suggests that there is a web of factors underlying the net effects of health on economic growth. Assessing these mechanisms separately will provide insight as to the differing results of research in this area and the situations and contexts in which health improvements are beneficial. Weil (2007) assesses the direct impacts of health improvements on worker productivity.
Comment [CLC1]: Already used web of factors. Can change the wording maybe? She probably won‟ t notice either way

From a humanitarian standpoint, there is considerable incentive to aid developing countries in improving health conditions. Various governments, international organizations and charities have made headway in this area (Weil, 2007). Many of these groups claim their reasons for doing so are moral in nature. There is a secondary goal for undertaking these objectives and it is the potential for economic growth as a result of having a healthier population. Whether or not there exists such a relationship between the overall health of a nation and its GDP is a difficult question to answer due to the vast number of contribution factors to both health and GDP. Weil (2007) draws quantitative conclusions about the effect of health improvements on average income. The paper also attempts to determine the mechanisms by which these improvements can act on GDP. The paper cites various mechanisms by which the overall health of a nation affects output. Firstly, the health of a worker directly affects their productivity. Improvements in health lead to an increase in life expectancy (Acemoglu and Johnson, 2007), which in turn raises incentive to invest in human capital, as the expected future payoff is higher when number of working years increases. This relationship also has the implication that lower morality leads to an increase in saving for retirement, thus increasing the level of physical capital per worker. This paper examines specifically the effect of better health on workers ability to work harder and more productively while holding level of physical capital, education and the quality of institution constant (Weil, 2007). Casselli (2005) looks at the determining factors of a nation‟s income level. It divides contributing factors into three categories: accumulation of physical capital,

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human capital and differences in productivity. The paper finds that productivity is the greatest source of income differentials between countries. Weil (2007) attempts to explains how productivity increases can be attributed to health and thus how health affects income level. Economic analyses have generally used two types of measures to link health to the economy. Inputs into health are physical factors that contribute to health (ie. nutrition, exposure to pathogens and the availability of health care). Weil (2007) finds that health outcomes, which include life expectancy, height, ability to work and cognitive capabilities, are affected by health inputs. An indicator of interest in Weil (2007) is human capital in the form of health. In other words, this means the portion of labour productivity that can be attributed to being a healthy and well nourished. Though this is an immeasurable variable, the paper uses other health outcomes and economic models to approximate its value (ie. adult survival rates, height and age at menarche). Weil (2007) concludes that health has an effect on incomes. As health in a particular group or nation improves, the income levels of this group also increase. Using the preferred measure of human capital in the form of health, adult survival rate, and eliminating the gap between nations, there is a reduction of 9.9 percent in the variance log GDP per worker between nations and a decrease in the ratio of income within country between those in the 90th and the 10th income percentile (Weil, 2007). There are some problems however with the conclusions that are drawn. The paper is limited in that the model used can only examine the direct effect of health (ie. people working harder, longer or more intelligently) on GDP per worker. This means that the indirect effects of health improvements are not taken into account, which could result in a change of the overall relationship between health and GDP. These indirect effects include health leading to an increase in the accumulation of both human and physical capital as well as health improvements leading to population growth. Accumulation of human or physical capital has a positive effect on GDP per capita while increases in population leads to a negative effect. This ambiguity in overall effects makes analyzing net effects a difficult process. With so many variables and factors at work, understanding exactly how health
Comment [CLC2]: She told me to take out attempts to. Makes the arguments seem stronger

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improvement can affect GDP is still unclear. In Bleakley (2003) assesses the effect of disease mitigation is assessed in the context of changes in human capital accumulation.

In Bleakley (2003) the eradication of two major parasites, hookworm and malaria, are discussed and conclusions are drawn about the effect of eradication these diseases have on economic growth and, more specifically, the accumulation of human capital in the American south. The paper discusses how exogenous changes in health affect economic growth in the region. The paper finds that the eradication of hookworm in the Southern United States increased school enrollment rates, which lead to increases in human capital. The example of the American South that is used in Bleakley (2003) is unique and useful for economic analysis for a variety of reasons. First of all, the major innovations that reduced disease prevalence rates came from outside the region and thus we can consider them to be exogenous shocks to the local economy. Second, these innovations were available in regions that were both affected by these diseases and those that were not. The areas with high disease prevalence experienced larger gains as a result of eradication, thus there is a treatment/control relationship that can be exploited in a statistical model. The coastal plains of the south have geography that is more susceptible to infection from these parasites while mountainous regions are less vulnerable. Lastly, eradication occurred far enough in the past that long run economic trends can be assessed. Bleakley (2003) uses school attendance and literacy as proxies for human capital increase and assesses these variables before and after eradication. The paper finds that regions with high rates of infection before eradication experienced large increases in school attendance after the intervention. These results were controlled for trends across regions, crop prices and educational policy changes. The incomes of adults who were exposed to the parasites as children also provide quantitative evidence with regards to the effect of eradication. Bleakley (2003) finds that in the long run, regions of the American South experienced large income gains after eradication. This significant evidence explains how it is possible for a nation or region to benefit from improving public health. As discussed in Weil (2007) there is evidence to suggest there is a direct effect of health on productivity. Bleakley (2003) provides even further evidence of this trend. In

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addition, the paper also provides some evidence of the long-term effect of improving health. This is especially important to regions, like the Southern United States, where a tropical climate lends itself to proliferation of diseases such as hookworm and malaria. The American South also has a history of “bad” institutions that were adopted to promote the extractive, plantation-based economy prevalent in the early twentieth century. These institutions did not provide solutions to the problems of tropical diseases. This problem exists in other regions that adopted similar extractive institutions (Acemoglu, Johnson and Robinson, 2001). Without the exogenous advancements in medical technology, it can be argued that the American South would not have pulled itself out of its static state of public health as quickly. This would have lead to lower rates of human capital accumulation, as low life expectancy and mortality rates lead people to invest less in human capital. This trend can still be seen in many African nations today (Bolt and Bezemer, 2009). Bleakley (2003) shows how health improvements can result in economic growth through an increase in human capital accumulation. In the case of the American South, solving health issues lead to a decrease in the income gap between the Northern and Southern states. Applying this trend to developing African nations that are currently experiencing debilitating epidemics could provide some insight into the initial steps that must be taken in order to promote growth. Addressing health alone will not necessarily lead to continued growth, however it is plays a major role in “kick starting” growth. Bleakley (2003) looked primarily at the effect of human capital changes as an indirect source of economic growth. The following paper by Voigtländer and Voth (2007) evaluates how disease affects population and the implications this relationship has on economic growth. This relationship is discussed in the context of thirteenth to nineteenth century Europe and provides evidence that population has an indirect effect on economic growth.
Comment [CLC3]: Should we use “kick starting” in a formal paper?

In the thirteenth century, China was a nation that was innovative, technologically advanced and was under unified political rule. China appeared to have all the tools necessary to advance, grow and flourish. Europe on the other hand was a collection of fragmented nations under the constant threat of war and political instability. By the dawn

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of the industrial revolution however, Europe had managed to surpass the wealth of China and the rest of the world. Voigtländer and Voth (2009) presents three factors, “The Three Horsemen”, which are responsible for the per capita increase in GDPGPD increase in Europe and why it had not occurred simultaneously in China between the 14th and 19th centuries. The three horsemen which lead to the beginning of Europe‟s eventual rise to dominance over the rest of world are pPlague, wWar and uUrbanization. Voigtländer and Voth (2009) finds that these three factors play a major role in what separated the development of technologically advanced China from the lagging, fragmented European nations and how it was possible even within a Malthus ian model. The Malthusian model predicts that if there are any changes in technology, the short term rise in GDP will be offset by a population increase which will return per capita GDP to its‟ former subsistence level, thus preventing per capita growth. Voigtländer and Voth (2009) shows that the plague, Black Death, which wiped out between one third and one half of the European population was such a substantial shock that it would take several generations for the population size to catch up to the gains seen in the wages of the survivors. It is from the plague onward that disease, war and urbanization helped fuel growth in Europe while in China that absence of these factors contributed to the stagnation of the once great Asian nation. Each of the three horsemen work together to ensure that population growth could not grow at a rate sufficiently high to offset the initial increases in output per capital due to the plague. Disease was the agent which initialized the shock in growth of income per capita and what subsequently continued to help war and urbanization play their part in allowing Europe to begin its‟ advance on world dominance. Voigtländer and Voth (2009) finds disease affected the rate of population growth in Europe through three distinct channels after the plague. High mortality rates and very short life spans in cities due to their lack of hygiene curtailed population growth. Disease also spread very efficiently over trade routes allowing any outbreaks and pandemics to move quickly from location to location. Third, disease was highly prevalent among war, the armies and their poor housing conditions. War in Europe raged constantly, “Between 1500 and 1800, the continent‟s great powers were fighting each other on average for nine years out of every ten” (Tilly, 1992).
For matted: Indent: F irst line: 0.5"

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This fostered the spread of disease and produced high numbers of casualties which again maintained low population growth. War created a market for the manufacturing of goods that equipped soldiers to continuing fighting. The political instability of the fractionalized geography allowed for populations to remain in check. War however, also provided short term negative income shocks by destroying property and preventing people from continuing to work. Meanwhile, in China, warfare was not nearly as prevalent due to the unity of the country and its‟ relative political stability. Though there was not a complete lack of war, it simply did not match the magnitude at which Europe continued battling over the period. Early urbanization was driven by this initial shock in income growth that allowed Engel‟s Law to come in to effect. The initial rise in wages allowed people to spend a greater percentage of their income on manufactured goods. This, along with the onset of continued manufacturing of war related goods created a higher drive for people to move to urban areas. The manufacturing increase created a rise in demand for trade. Trade allowed for diseases that were common in urban centres to move along trade routes, thereby further culling population growth. Chinese cities were much cleaner and mortality rates were lower allowing the Malthusian model to take place as exactly as it was predicted to do and thus created a higher population growth rate moving continually toward subsistence. Voigtländer and Voth (2009) provides a framework that allowed Europe to enter the industrial revolution. Peculiarly enough, the same high mortality rate in Europe that allowed income per capita to remain elevated in Europe prior to the end of the Malthusian era prevented colonized nations from experiencing positive growth over time (Acemoglu, Johnson and Robinson, 2001). It is also interesting to note that disease environments prior to the 19th century were able to maintain the initial growth in Europe under poor conditions while positive disease environments in China hindered them. The European model contradicts research done on nations during and after the 19th century. Auer (2008) finds that low disease environmentspositive disease environments, like such as pre-19th century China promote growth, while poor disease environments seriously hinder it. Voigtländer and Voth (2009) allows us to see how differences between disease and health, war and relative peace, and the effects of urbanization create a situation that

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allowed European nations to gain power, overcome the Malthusian model, and begin the creation of the modern world through colonization and technological innovation. It also shows China‟s relative lack of strife and turmoil actually hindered progress and prevented it from remaining a worldly power during the modern growth period. This studyied provided evidence with respect to the role disease environments play on economic growth through population controls. These disease environments also determine the types of institutions that are adopted by nations and colonies. In Moving from Voigtländer and Voth (2009) to Auer (2008) we will see how the role that disease and geography plays in the development is appraised through the of political and economic institutions of a region. This relationship is supported by Acemoglu, Johnson and Robinson (2001), but is put into a context specific to disease. A theory can be defined as “a belief that can guide behavior”. A theory, however, is not proof. Auer (2008) creates a more complete explanation of what effects geography, colonization and institutions have on growth by expanding on previous works. Auer (2008) uses two important, albeit divided schools of thought to identify a common and more conclusive answer to what past factors drove growth or a lack thereof to where economies are today. These two important schools of thought are a nations endowments and the impact of institutions. Auer (2008) places heavy emphasis on the importance of using both of these agents to determine how much weight and validity each has on growth. With Bythe removing theal of bias of initially using only institutions or endowments from the beginning it Auer (2008) shows that a variation in geography will lead to variation in institutions themselves. The first school of thought is that of the importance of endowments. Works such as Diamond (2007) and Bloom and Sachs (1998) argue that a nation‟s natural endowments are the greatest importance to its‟ economic prosperity and growth. These endowments can include soil quality, climate, amount of rainfall, and geographical location such as proximity to the equator. A very important factor attributed to endowments is disease prevalence. Auer (2008) measures geographic potential for disease, referred to as Early Disease Environment (EDE). Using EDE Auer (2008) deducts that based on mortality rates of settlers in colonized nations from Acemoglu et al.

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(2001)Acemoglu, Johnson and Robinson (2001) and geographic variables that the prevalence of disease is a direct result of the climates in which they were settled. Auer (2008) finds that disease effects growth and prosperity both directly and indirectly. Disease affects all nations in some manner whether they are former colonies or not. These effects have significantly different ranges throughout different geographical zones such as the sub-Saharan, temperate and tropical regions ofin the world. It also finds that non-colonies (minus the four rich colonies Canada, USA, Australia and New Zealand) are not indirectly affected by the prevalence of disease. The colonies are indirectly affected such that the colonization of these countries created a tendency to enact institutions, which weare undesirable for prosperity. Institutions are argued to be a strong motivator for growth. Acemoglu et al. (2001)Acemoglu, Johnson and Robinson (2001) presents that settler mortality rates affects the institutions that are implemented in colonized nations. These institutions are divided into two sections. They are those which promote positive growth and those which hinder growthit. Positive institutions included high settler rates, entrepreneurship, legal systems and trade. Negative institutions that were applied by colonizers are described as extractive. Colonies that had these extractive institutions were set up only to exhaust and export their resources. Auer (2008) shows that initial early disease environments play a crucial role in the establishment of positive or negative (extracting) institutions in colonized countries. High prevalence of diseases, especially malaria, lead to extractive institutions which result in poor economic conditions today. Disease prevalence; however, plays a larger initial role, as opposed to a sustained role in the further development of these colonies. Early disease environments appear to have been stepping stones for the further growth of colonized nations. Auer (2008) finds that there is a significant difference in the effect that EDE and institutional outcomes has on former colonies and those that are not former colonies. This serves to show that colonial origins and the established institutions within the colonies are directly affected by the initial EDE. The strength of Auer (2008) is reliant on the effects that endowments and institutions have on each other rather than one alone being the driving factor. By using hypotheses from different pools of thought and information, Auer (2008) provides a very

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convincing argument that it is neither geography nor institutions alone that can explain all of the reasons behind a flourishing economy or one that is hindered by history, preventing growth and prosperity. It finds that using the two schools of thought a more accurate picture is developed about what effects geography, disease and the institutions of colonized nations have on economic growth. By building on previous works and combining the strengths of other arguments Auer (2008) develops a sound hypothesis while proving there are many variables that all play crucial roles in the development of economic systems in the world. Bolt and Bezemer (2009) use many of the ideas presented by Auer (2008) with an emphasis on the educational institutions which have been implemented. The effect of geography and institutions are evaluated in the context of African development.

There are a plethora of factors that affect economic growth among all regions of the world. These factors can react with each other in either a negative or positive fashion. These reactions can prove to be highly beneficial for a country‟s long-term economic success or contribute to its‟ failure. Sub-Saharan Africa proves to be an excellent model to observe due to the fact that there is a vast array of various degrees of successes and failures between nations. These nations have imposed different institutions, have various levels of investment in human capital, and have a range of geographic distributions. Bolt and Bezemer (2009) examines the factors that determined the level of growth preceding modern economic times. Though the paper discusses many variables, the focus of this paper is how disease and geographical endowments affect growth. Bolt and Bezemer (2009) finds that investment in human capital, geographic location and the institutions implemented by colonizers all affect the level of growth of these colonized nations have experienced and are currently experiencing. Geography is a factor found to affect long-term economic growth. It is a component implicated in the availability of resources, prevalence of disease and access to waterways. Geography is an important aspect of both creating growth, and its sustainability. Geographic location affects the abundance of resources that are able to provide an environment that promotes growth. Bolt and Bezemer (2009) divides resources into two categories: point resources and non-point resources. Point resources

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are natural resources such as diamonds, oil, precious metals and crop exports. When successfully utilized they can increase income sustainability; however, they can also be a direct cause of both political and economic instability known as the „resource curse‟ (Isham, Woolkock, Pritchett, Busby, 2005). Non-point resources are described as resources such as sunshine, rainfall and soil fertility. These are the bases for sustainable growth but due to Sub-Saharan Africa‟s fluctuating weather patterns, which include long dry spells; this can make non-point resources a difficult agent to rely on. Disease, which is another important variable reliant on geography affects more than just citizens of countries. Disease, such as malaria can have various negative effects on humans such as a decline in both productivity and life expectancy, but it can also affect crops and livestock through plagues and pests. A restriction to rivers and various waterways also increases the costs of transportation and trade creating difficulties in fostering growth. Acemoglu, Johnson and Robinson (2001) find that institutions also play a role in the growth of former European colonies. It describes two institutions implemented by colonizers: constructive and extractive. Constructive institutions are characterized by a higher European settler rate due to a disease environment that was more favourable. Areas not favourable to European settlement, those with higher settler mortality rates, would rather be met with extractive institutions. Extractive institutions also did not promote further growth but rather repressed it. Bolt and Bezemer (2009) acknowledges this; however, questions whether this explains the African situation completely due to the fact Acemoglu, Johnson and Robinson (2001) does not investigate only African colonies. Bolt and Bezemer (2009) did not find that high or low settler mortality rates lead to the different institutions among nations. It simply found that nations which had implemented good institutions resulted in a much higher level of human capital investment which in turn leads to higher levels of growth today. Legal origins are also fundamental institutions in the development of former European colonies. Glaeser and Shleifer (2002) finds that current growth of former colonies which implemented various legal systems has a role in determining the quality of the current situations in these nations. Along with legal institutions, educational institutions implemented play a large role in economic growth in colonial nations. Bolt and Bezemer (2009) observes that colonial education provided long-term growth through

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two channels: affecting present education levels, and through its effect on political institutions by fostering stability. By using only African nations in Bolt and Bezemer (2009), the Acemoglu, Johnson and Robinson (2001) model no longer finds that a higher mortality rate and lower settler population create institutions harmful for economic growth. It finds that institutions including education and the origins of the legal system correlate with geographical factors promoting growth. Bolt and Bezemer (2009) provides strong evidence that a nation‟s colonization can have a positive or negative effect on nations by the institutions instilled by the colonizers. Bolt and Bezemer (2009) provide insight into the effect geographic location can have on a nations‟ potential for economic growth (resource rich, fertile soil, etc.) and how disease can pose great problems for economic development. Their research doesn‟t take into account the net effects of these relationships. Integrating the direct effect of disease on growth as well as the many indirect effects, including institutions, is the purpose of the paper by Bhattacharyya (2009). The unified framework presented allows one to see how depending on the stage of development a nation is in, the effects of disease directly on growth may be the primary mechanism or may take a back seat role to institutional sources of growth.

Disease and institutions have both been claimed as a root cause of economic growth. Weil (2007) discusses the effect of health improvements on worker productivity and Bleakley (2003) discusses the indirect effects of human capital accumulation as a result of disease eradication. Both of these papers cite disease as a root cause of growth. Acemoglu, Johnson and Robinson (2004) cites institutions as the fundamental determinant of long run growth. Bhattacharyya (2009) takes both institutions and health into account in a unified way. The paper finds that health and disease mitigation are important in the early stages of development and can have effects on incomes, whereas the adoption of good institutions are the cause of continued development later on. Bhattacharyya (2009) uses historical examples to provide evidence for how institutions and disease differ in their affect on GDP and also how the two are interrelated. The paper uses the example of development in Western Europe to explain how both of these hypothesized root causes can have an effect on growth. Bhattacharyya

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(2009) He breaks development down into four stages. The first stage is characterized by a Malthusian cycle that is affected by disease and geography. In this stage of development, the only factors that lead to changes in food production are climate and disease. Climate directly affects yields, and thus total food production. Disease affects the productivity and supply of labour as concluded by Weil (2007). In this period, land and technology are relatively stable. An increase in food production will lead to increases in population. Because the other factors of food production are stable, population will out grow the supply of food and thus will experience food shortages. Constant incidences of disease, often brought on by food shortages, keep the population from reaching high levels. Malnourished people are more vulnerable to disease and, as seen in Western Europe throughout the fourteenth century, epidemics often coincided with food shortages. This disease bottleneck is the major factor preventing growth at this stage in development. The second stage of development comes when it is realized by national leaders that in order to increase food production to support an increasingly dense population, more land is needed. This results in armed conflict between nations and colonial conquest. For Europe, this stage of development also included an increase in tax revenue as territory and agricultural yield grew. This revenue was used to adopt new technology (for war and food production) and to maintain a healthy army and population. Once war within Europe became too costly, exploration by sea became a more common source of revenue. Colonial trading and the mercantile system brought about further specialization and productivity increases. By this stage, some nations adopted institutions that distributed wealth and promoted private investment. These nations experienced rapid technological advancements and continued to grow. In the later stages, disease had a lesser effect on growth, while institutions were the main root cause. Europe is not the only area in which stage of development determined growth. In Africa, disease has been common throughout history. Epidemics and climate variation play a large role in growth for African nations. Food production is constrained due to drought and unpredictable weather. This leads to malnutrition and a greater vulnerability of the population to disease. Such a struggle to produce a subsistence level of food prevented Africa from reaching the later stages in development where institutions play a role. This is reflected in the data. In assessing China, India and the Americas, the paper

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finds that these nations were able to escape the Malthusian poverty trap, however each had their own institutional factors that lead them on different paths of growth. For these nations, disease had little effect on growth rates because they were able to move past the early stages of development to stages where institutions were the primary driving force of further development. The impact of disease on economic growth has always been dealt with in isolated situations that assess individual mechanisms such as the direct effects of health on productivity and income increases as a result of increase human capital (Weil, 2007 and Bleakley, 2003). Bhattacharyya (2009) is unique in that it uses historical narratives to outline how different theories of development can be used together to explain how and why particular counties developed when they did. This way of examining the problem, though it provides little scientific evidence, produces strong and tailored arguments as well as explains how the literature can provide conflicting evidence. Bhattacharyya (2009) provides a framework by which both disease and institutions can be used to explain growth rates of nations. He finds disease mitigation is an important factor in early stages of development, when nations are in a Malthusian cycle and have not fully utilized available land for production. Once a nation moves beyond this stage of development, disease mitigation will not result in net gains in economic growth. Institutions take over as the primary cause to income growth, and as a result, gains to health improvements depend on the stage of development a nation or region is currently in. The connection between disease and development may not be straightforward throughout development, however given particular circumstances it can be the primary root cause.

Throughout our paper we have examined the effect disease has played and continues to play on various stages of economic growth in a variety of time periods and environments. In each of the literary works we have encountered, there is consistent evidence stating that disease does in fact play a role in growth though that role may vary due to several factors and circumstances. Disease affects the economic growth patterns of nations both directly and indirectly. Geography is a driving factor for disease rates and nations in areas with higher disease prevalence, or regions that are unable to eradicate disease, continue to

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have lower growth rates today than nations that have a more opportune geographic location with lower prevalence rates. By looking at isolated examples of changes in health states we can see how disease leads to changes in wellbeing. We see how improvements in GDP and human capital development in the American southwest resulted from the eradication of major diseases and also how poor economic conditions can persist in former European colonies in Africa which have failed to eradicate many of the diseases that plague their population. By determining the mechanisms that link disease to economic growth, one can assess the benefits of disease mitigation as well as how developing nations can use health measures in to increase GDP, long term economic growth and the overall wellbeing of the population.

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References Acemoglu, D., & Johnson, S. (2007). Disease and Development: The Effect of Life Expectancy on Economic Growth. Journal of Political Economy, 115(6), 925-985. Retrieved from http://www.journals.uchicago.edu/JPE/ Acemoglu, D, Johnson, S., & Robinson, J. A. (2001). The Colonial Origins of Comparative Development: An Empirical Investigation. The American Economic Review, 91(5), 1369-1401. Retrieved from http://www.jstor.org/stable/2677930 Auer, Raphael. (2009). The Colonial and Geographic Origins of Comparative Development. Working Papers 09.03, Swiss National Bank, Study Center Gerzensee. Retrieved from http://www.snb.ch/n/mmr/reference/working_paper_2008_08/source/working_pa per_2008_08.n.pdf Bhattacharyya, S. (2009). Institutions, Diseases, and Economic Progress: A Unified Framework. Journal of Institutional Economics, 5(1), 65. Retrieved from http://journals.cambridge.org/action/displayFulltext?type=6&fid=4288720&jid=J OI&volumeId=5&issueId=01&aid=4288716&fulltextType=RA&fileId=S174413 7408001227 Bleakley, H. (2003). Disease and Development: Evidence from the American South. Journal of the European Economic Association, 1(2-3), 376-386. Retrieved from http://www.mitpressjournals.org/loi/jeea Bloom, D. E., Canning, D., & Fink, G. (2009). Disease and Development Revisited. Retrieved from http://www.nber.org/papers/w15137.pdf Bloom, D. E., Sachs, J. D., Collier, P., & Udry, C. (1998). Geography, Demography, and Economic Growth In Africa. Brookings Papers on Economic Activity, 1998(2), 207-295. Retrieved from http://www.jstor.org /stable/2534695 Bolt, J. & Bezemer, D. (2009). Understanding Long-Run African Growth: Colonial Institutions or Colonial Education? The Journal of Development Studies, 45(1), 24. doi: 10.1080/00220380802468603 Crimmins, Eileen M. and Caleb E. Finch. (2006). Infection, Inflammation, Height, and Longevity. Proceedings of the National Academy of Sciences 103(2): 498-503. Retrieved from http://www.jstor.org/stable/30048331 Diamond, J. M. Guns, Germs And Steel: The Fate Of Human Societies. New York: W.W.Norton & Co., 1997. Glaeser, E. L., & Shleifer, A. (2002). Legal Origins. Quarterly Journal of Economics, 117(4), 1193-1229. Retrieved from http://www.mitpressjournals.org/loi/qjec

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Heckman, J. J. (2007). The Economics, Technology and Neuroscience of Human Capability Formation. Retrieved from http://www.nber.org/papers/w13195.pdf Isham, J., Woolkock, M., Pritchett, L. and Busby, G. (2005). The Varieties of Resource Experience: Natural Resource Export Structures and the Political Economy of Economic Growth. The World Bank Economic Review, 19(2), 141. doi:10.1093/wber/lhi010 Miguel, E., & Kremer, M. (2004). Worms: Identifying Impacts on Education and Health in the Presence of Treatment Externalities. Econometrica, 72(1), 159-217. Retrieved from http://www.jstor.org/stable/3598853 Preston, S. H. (1975). The Changing Relation Between Mortality and Level of Economic Development. Population Studies, 29(2), 231-248. Retrieved from http://www.tandf.co.uk/journals/titles/00324728.asp Voigtlander, N., & Voth, J. (2008). The three horsemen of growth: Plague, war and urbanization in early modern Europe. Retrieved from http://www.econ.upf.edu/docs/papers/downloads/1115.pdf Weil, D. N. (2007). Accounting for the Effect of Health on Economic Growth. Quarterly Journal of Economics, 122(3), 1265-1306. Retrieved from http://www.mitpressjournals.org/loi/qjec

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