Econ Dev Notes PDF

Population Pyramids visually show the age and gender structure of a country's population: 1.​ Developed Countries: ○​ Shape: Narrow base, broader top. ○​ Meaning: Low birth/death rates, aging population. 2.​ Developing Countries: ○​ Shape: Wide base, narrow...

Population Pyramids visually show the age and gender structure of a country's population: 1.​ Developed Countries: ○​ Shape: Narrow base, broader top. ○​ Meaning: Low birth/death rates, aging population. 2.​ Developing Countries: ○​ Shape: Wide base, narrow top. ○​ Meaning: High birth rates, younger population. 3.​ Ethiopia: ○​ Shape: Classic pyramid (very wide base). ○​ Meaning: High fertility, short life expectancy, and young population. Stage 1: Pre-Industrial ​ High Birth and Death Rates: Rates are roughly equal, leading to little or no population growth. ​ Causes: Poor sanitation, diseases, and lack of medical care. Stage 2: Early Industrial ​ High Birth Rates, Declining Death Rates: Population grows rapidly as healthcare and sanitation improve. ​ Causes: Better food supply, clean water, and vaccines. Stage 3: Mature Industrial ​ Declining Birth Rates, Low Death Rates: Population growth slows down. ​ Causes: Urbanization, access to contraception, and improved education. Stage 4: Post-Industrial ​ Low Birth and Death Rates: Stable or declining population. ​ Causes: High living standards, women in the workforce, and family planning. Case A ​ Birth Rates (Case A): Represents a scenario where birth rates start high but gradually decrease over time due to factors such as increased access to contraception, education, and changes in societal values. ​ Death Rates (Case A): Represents a scenario where death rates decline significantly due to improvements in healthcare, sanitation, and overall living conditions. Case B ​ Birth Rates (Case B): Represents a different scenario where birth rates might decrease more slowly or at a different rate compared to Case A, potentially due to varying socio-economic factors, cultural influences, or slower adoption of family planning methods. ​ Death Rates (Case B): Represents a scenario where death rates might not decline as rapidly as in Case A, possibly due to less effective healthcare improvements or other socio-economic challenges. The Malthusian Population Trap is a theory proposed by Thomas Malthus in the 18th century, explaining how population growth can lead to poverty and lower living standards. Key Points: 1.​ Rising Population: As the population grows, resources (especially land) become scarcer. 2.​ Diminishing Returns: With more people but the same amount of land, each person gets less land to work, reducing productivity. 3.​ Low Living Standards: This leads to lower wages, food scarcity, and generally poor living conditions for the population. Malthus's Influence on Birth Control: ​ Malthus believed that controlling population growth (through birth control or delaying marriage) was crucial to prevent societies from falling into the population trap. This theory influenced modern birth control movements by emphasizing the need to manage population growth to ensure economic stability. At income per capita (Yo), a stable population exists because birth and death rates are equal. In Stage 1 of the demographic transition: ​ High Birth and Death Rates: Population stays roughly the same due to these rates balancing each other out. ​ Low Income: Basic living standards, with limited access to healthcare, education, and technology. In Stage 2 of the demographic transition: ​ As income per capita increases beyond Yo, death rates fall due to improvements in healthcare, sanitation, and food supply. ​ Population Size Increases: Since birth rates remain high but fewer people die, the population grows rapidly. When per capita income reaches Y2, population growth is at its maximum (around 3.3%). ​ This happens because birth rates are still high, and death rates are low. ​ Population continues to grow at this high rate until much higher income levels are reached, after which birth rates start to decline. In Stage 3 of the demographic transition: ​ Once per capita income surpasses Y5, birth rates begin to decline. ​ As a result, the population growth rate slows down and starts to decrease, creating a negatively sloped curve. ​ This happens because people have fewer children due to better access to education, family planning, and economic factors like urbanization. The relationship between income growth rate and income per capita (from Yo up to before Y3) is that as per capita income increases, the income growth rate also rises. Economic Reason: ​ Higher Per Capita Income → Higher Savings Rates: People earn more and can save more. ​ More Investments: Savings are channeled into investments like infrastructure, businesses, and technology. ​ Higher Rates of Aggregate Income Growth: Increased investments lead to higher productivity, creating more wealth and driving economic growth. At Y3, growth in total income starts to decline because: ​ New investments lead to more production, but eventually, more workers are needed to work with fixed resources (like land and capital). ​ This results in diminishing returns—the additional income growth slows down as the resources become stretched, and more people compete for the same amount of resources. At Y3, total income growth begins to decline because: ​ New investments lead to more workers being needed to work with fixed resources (land, capital). ​ Diminishing returns occur: As more people work with the same resources, the added output from each additional worker decreases. ​ This follows the basic theory of production, where increasing input (labor) with fixed output (resources) leads to lower productivity gains. ​ The absence of technological progress can worsen this, as improvements in technology are needed to increase efficiency and keep growth rates up. At Point A, the Malthusian population trap level of per capita income, Y1, is reached. ​ If per capita income rises above Y1 (moving to the right), population growth increases due to higher birth rates, which leads to a return to Y1 as resources become scarce. ​ If per capita income falls below Y1 (moving to the left), population decreases due to higher death rates, and income will also return to Y1 as the population stabilizes. This cycle happens because resources are limited, and any change in income leads to population adjustments that bring income back to the Malthusian equilibrium at Y1. At Point A, poor nations are stuck near their subsistence levels of per capita income (Y1) unless they implement "Preventive Checks" (like birth control). ​ Preventive Checks: These are actions that reduce birth rates, such as family planning and delayed marriages, which can help stabilize the population and allow for higher income growth. ​ Without these measures, the population will keep increasing, leading to Positive Checks like starvation, disease, and wars, which reduce the population and bring income back to the subsistence level. Thus, nations must control population growth to break free from the Malthusian trap and raise living standards.  At Point B, the economy is in an unstable equilibrium. ​ If the economy moves to the left (lower income), population decreases, but income will continue to fall until it reaches Point A, the subsistence level. ​ If the economy moves to the right (higher income), population grows, leading to more competition for resources and causing income to fall back to Point A as well. This instability means that Point B is not a stable position; the economy will either move toward Point A (low income) or Point C (higher income) if there is significant progress like technological growth or better resource management. Criticisms of the Mathusian Model 1.​ Malthusian model ignores technological progress: ​ The model assumes that resources are fixed, and population growth will lead to poverty because there won't be enough food or land. ​ But in reality, technology has helped increase food production and improve resource use, allowing populations to grow without falling into poverty. ​ So, Malthus didn't consider how innovation can solve problems of limited resources. 2.​ Malthusian model is is currently no clear connection between population growth and per capita income. The model suggests that as the population grows, income should decrease due to limited resources, but in reality, many countries with high population growth have experienced economic growth, while others with lower population growth still face economic challenges. This shows that population growth doesn't always lead to the negative outcomes predicted by Malthus. 3.​ Malthus focused on aggregate population growth and its impact on resources, but microeconomics looks at individual or household decisions about family size. The theory suggests that families make decisions based on factors like income, education, and access to birth control, which can affect population growth more directly than Malthus's broader focus on just birth and death rates. In short, the Malthusian model doesn't account for the fact that families may choose smaller sizes when they have more resources and better options, which challenges the idea of inevitable population pressure. Interpretation: 1.​ Initial Increase: Both the total income growth rate and population growth rate initially increase as income per capita rises. 2.​ Peak and Decline: ○​ The total income growth rate peaks and then gradually declines. ○​ The population growth rate also peaks but begins to decline after reaching a certain level of income per capita. Conclusion: This graph shows that as nations experience technological and social progress, leading to higher income per capita, they can avoid the population trap. Initially, both income and population grow, but with further progress, the population growth rate decreases, leading to sustainable development. The Microeconomic Household Theory of Fertility explains family size decisions based on economic factors: ​ In developing countries, the first two or three children are often seen as "consumer goods"—providing direct enjoyment and support for the family. ​ Additional children are viewed as "investment goods"—they can contribute to the family farm, microenterprise, or provide old age security by caring for parents in their later years. This theory highlights how families weigh the benefits and costs of having children based on economic needs and resources.  Interpretation: 1.​ Higher Levels of Living: As households achieve higher standards of living (moving to higher indifference curves like I_3 and I_4), they face a relative increase in the cost of raising children. 2.​ Motivation to Have Fewer Children: The higher the cost of children in terms of goods foregone, the more likely households are to desire fewer children. This is illustrated by the shifts from points like e and f to points like g and h on higher indifference curves. 3.​ Economic Decision-Making: The graph shows how economic factors, such as income and the cost of goods, influence family planning decisions. Higher income leads to a preference for fewer children, as parents allocate more resources to goods and services rather than having more children. Main Conclusion: ​ Economic Trade-Off: Higher levels of living with a relative increase in the price of children motivate households to have fewer children. Parents balance their desire for children with the need to consume other goods, leading to a decision-making process influenced by economic factors. Causes and Policy Responses to High Fertility in Developing Countries: 1.​ Improved Women’s Education, Role, and Status: ○​ Enhancing women’s education and their social status can lead to lower fertility rates. 2.​ Increase in Female Nonagricultural Wage Employment: ○​ Encouraging women to participate in nonagricultural wage employment can reduce fertility as women gain economic independence and career aspirations. 3.​ Rise in Family Income Levels through Shared Growth: ○​ Increasing family incomes through equitable economic growth can help lower fertility rates as families may choose to have fewer children. 4.​ Reduction in Infant Mortality, Better Health Care: ○​ Improving health care and reducing infant mortality can lead to lower fertility as parents feel more assured about the survival of their children. 5.​ Development of Old-age and Social Security Plans: ○​ Establishing social security and old-age plans can reduce the need for large families as a form of support in old age. 6.​ Expanded Schooling Opportunities, Lowered Real Costs: ○​ Increasing access to education and reducing the costs associated with schooling can contribute to lower fertility rates. 7.​ Lowered Prices and Better Information on Contraceptives: ○​ Making contraceptives more affordable and providing better information can help families plan their sizes more effectively. 8.​ Direct Incentives such as Subsidy Benefits: ○​ Offering direct incentives like subsidies can encourage families to have fewer children. 9.​ Policies that Have the Effect of Reducing Boy Preference: ○​ Implementing policies to reduce gender preference, particularly the preference for boys, can help balance family planning decisions. These strategies aim to provide a comprehensive framework for policy-making to address high fertility rates in developing countries, leveraging education, economic growth, health care improvements, and social policies. The implications for lower fertility rates are: ​ Raising women’s education, role, and status: When women have access to education and greater societal roles, they tend to have fewer children. ​ More female nonagricultural wage employment: Increased participation of women in the workforce, especially in non-agricultural sectors, often leads to delayed marriage and childbearing. ​ Rise in family income levels: Higher income can make it easier for families to support fewer children and prioritize quality of life. ​ Reduction in infant mortality: As healthcare improves, fewer children die in infancy, leading families to have fewer children to ensure survival. ​ Development of old-age and social security: With better security for the elderly, families may feel less need to have many children for old-age support. ​ Expanded schooling opportunities: Access to education encourages families to invest in fewer children, focusing on their education and future. These factors contribute to a shift toward lower fertility rates as families prioritize quality of life, education, and economic stability. The Consequences of High Fertility: Some Conflicting Perspectives "Population growth is not a real problem" argues that the actual issues lie elsewhere: ​ Underdevelopment: Poverty and lack of resources in certain regions. ​ Resource depletion and environmental destruction: Overuse of natural resources and environmental damage. ​ Population distribution: Uneven population growth in different areas, leading to overcrowding or underpopulation in some regions. ​ Subordination of women: Gender inequality, which impacts family planning and economic growth. "Population Growth is a Real Problem" includes both extremist and empirical perspectives: ​ Extremist arguments: These often highlight the potential for disaster if population growth continues unchecked. ​ Empirical arguments point to real-world consequences: ○​ Lower economic growth: Overpopulation can strain resources and hinder economic progress. ○​ Poverty: More people can lead to greater competition for limited resources, increasing poverty levels. ○​ Adverse impact on education: Overcrowding can reduce the quality of education due to limited facilities and resources. ○​ Adverse impact on health: Overpopulation can overwhelm healthcare systems, leading to poorer health outcomes. ○​ Food constraints: Increased demand for food can outpace agricultural production, leading to shortages. ○​ Impact on the environment: More people lead to greater environmental degradation, including deforestation and pollution. ○​ Frictions over international migration: High population growth can lead to migration pressures, causing tensions between countries. Goals and Objectives: Toward a Consensus Despite differing opinions on population growth, there is common ground on several points: ​ Population is not the primary cause of lower living standards but may be a contributing factor. ​ Population growth is often a consequence rather than a cause of underdevelopment. ​ Quality of life is more important than sheer population numbers. ​ Market failures and negative social externalities may arise from unchecked population growth. ​ Voluntary fertility reduction is generally desirable in developing countries with expanding populations. Policy Approaches What Developing Countries Can Do: ​ Persuasion through education: Encourage informed decisions about family size. ​ Family planning programs: Provide access to education and technology to regulate fertility. ​ Address incentives and disincentives: Modify factors influencing the demand for children. ​ Raise women’s socioeconomic status: Increase opportunities for women to work and contribute to the economy. ​ Facilitate faster development: Promote economic growth in countries with high fertility rates. What Developed Countries Can Do: ​ Address resource use inequities: Ensure fairer distribution of global resources. ​ More open migration policies: Allow easier migration to reduce demographic pressures in overpopulated regions. ​ Assist with research and financial support: Help developing countries with fertility control technologies and fund family planning programs. These approaches aim to balance population growth with sustainable development, focusing on improving the quality of life and addressing socioeconomic factors. Migration Urbanization: Trends and Projections ​ Pattern of Development: As economies develop, urbanization typically increases. ​ Challenge in Developing Countries: Rapid and excessive urbanization often outpaces infrastructure, services, and job availability. ​ Migration-Urbanization Dilemma: High rural-to-urban migration can lead to overcrowded cities, unemployment, and inadequate public services. Projection: Urbanization will continue to grow globally, with the majority of the population in developing countries expected to reside in urban areas in the future. This figure illustrates the relationship between urbanization rates and log per capita GDP in 2010, with a comparison to 1960 trends. Here’s a breakdown of its key insights: 1.​ Urbanization and Economic Growth:​ The solid line represents the linear fit for 2010, showing that higher urbanization correlates with higher per capita GDP. The dashed line for 1960 reflects a similar but less pronounced trend. 2.​ Shifts Over Time: ○​ In 2010, many countries reached higher urbanization levels at lower GDPs compared to 1960. ○​ Rapid urbanization is evident in developing nations, not always accompanied by proportional economic gains. 3.​ Key Implication:​ While urbanization has grown worldwide, its economic benefits depend on adequate infrastructure, industrialization, and governance to support urban populations. Developing countries often face challenges due to premature or excessive urbanization without matching economic advancements. Urban Population Trends ​ Less Developed Regions: ○​ Urban population has shown consistent growth since 1950 and is projected to continue increasing sharply, surpassing 4 billion by 2050. ○​ The rise reflects rapid urbanization in regions like Asia, Africa, and Latin America. ​ More Developed Regions: ○​ Urban population growth has been more gradual and is projected to stabilize at around 1 billion after 2020. Rural Population Trends ​ Less Developed Regions: ○​ Rural populations have been increasing until around 2020 but are expected to decline thereafter as urban migration accelerates. ○​ The decline aligns with industrialization and the reduced reliance on agrarian economies. ​ More Developed Regions: ○​ Rural populations have been declining steadily since 1950 and are expected to plateau at very low levels by 2050. Key Implications ​ The urbanization of less developed regions will place significant pressure on infrastructure, resources, and services, requiring sustainable urban planning and development policies. ​ The decline in rural populations highlights the need for balanced development strategies to prevent economic disparities and ensure that rural areas are not neglected. ​ Global efforts will need to address urban poverty, environmental challenges, and the equitable distribution of resources.  This chart depicts the number of people living in urban and rural areas globally from 1960 to 2021, based on data from "Our World in Data." Here's a summary of the insights: Key Observations 1.​ Urban Population Growth: ○​ The urban population (red line) has been rising steadily since 1960. ○​ Around 2007, the urban population surpassed the rural population, marking a significant global demographic shift. ○​ By 2021, the urban population exceeded 4 billion, reflecting the global trend of urbanization. 2.​ Rural Population Plateau and Decline: ○​ The rural population (green line) grew slightly from 1960 to around 2000, reaching a peak of approximately 3.4 billion. ○​ After 2000, the rural population began to plateau and has shown signs of a gradual decline in recent years, reflecting urban migration and reduced growth rates in rural areas. 3.​ Crossing Point: ○​ The crossover point where the urban population exceeded the rural population occurred around 2007, highlighting the shift to a predominantly urban world. Implications ​ Urbanization brings opportunities for economic development and access to services but also poses challenges such as infrastructure strain, housing shortages, and environmental concerns. ​ Rural areas may face depopulation and aging populations, which could impact agricultural production and the sustainability of rural economies. The graph illustrates the share of people living in urban areas in 1990. It shows that in the Philippines, 46.99% of the population lived in urban areas during that year. The map uses different colors to represent various percentages of the urban population across different countries. This interactive map allows viewers to see data from different years, ranging from 1960 to 2021, and offers options to view the data in table or chart form. Agglomeration Economies Summary 1. Urbanization Economies (General) ​ Benefits from diverse industries clustering in urban areas. ​ Shared infrastructure, large labor pool, and knowledge spillovers. ​ Example: New York, Tokyo. 2. Localization Economies (Industry-Specific) ​ Industry clusters create specialized suppliers, labor, and faster innovation. ​ Example: Silicon Valley for tech, Hollywood for entertainment. Key Benefits: ​ Reduced transportation costs: Firms and consumers benefit from proximity. ​ Labor market pooling: Firms access skilled workers; workers find nearby jobs. ​ Infrastructure sharing: Urban areas provide essential and specialized infrastructure. ​ Knowledge spillovers: Ideas and innovation spread among firms and industries. Consumer Benefits: Access to urban amenities and a variety of goods/services. Challenges: Overcrowding, high costs, and environmental strain. Quality of Clusters and Industrial Districts ​ Strong clusters drive sectoral efficiency and competitiveness. ​ Developing countries often face challenges in building effective clusters, limiting their progress.  Challenges of Urbanization ​ Cities face "congestion costs" that can offset benefits. ​ Optimal urban size varies by industry, based on lowest average production costs. ​ Capital-intensive industries need larger cities, while labor-intensive economies often sustain smaller cities. ​ Urban areas require significant investment in capital and infrastructure. Urbanization and Bias in Developing Countries ​ Urban areas are capital-intensive, leading to large cities in developed countries. ​ However, urbanization in developing countries has accelerated faster than expected. ​ Informal sectors, such as shantytowns and favelas, dominate much of urban growth. ​ A significant portion of workers remain outside the formal sector. ​ While growth is seen in mid-size cities, urban bias continues to be a major challenge. The urban informal sector refers to unregulated economic activities, typically small-scale and labor-intensive, that operate outside formal government oversight. It includes businesses like street vending, home-based work, and self-employment, which often require minimal capital and lack formal contracts or social protections. Despite its informality, this sector plays a crucial role in job creation, particularly in rapidly urbanizing areas, offering employment opportunities to marginalized groups, including women and migrants. It fosters economic surplus, provides informal training, utilizes local resources and technologies, and contributes to recycling efforts. In many developing countries, the informal sector helps alleviate poverty by offering economic opportunities to those excluded from the formal labor market. Why Promote the Urban Informal Sector? ​ Surplus Generation: It creates economic surplus despite challenging conditions. ​ Job Creation: Provides employment opportunities with low capital investment. ​ Training Opportunities: Offers informal training and apprenticeships for skill development. ​ Demand for Labor: Creates jobs for low- or unskilled workers. ​ Local Resource Use: Utilizes appropriate technologies and local resources. ​ Waste Recycling: Promotes recycling of materials. ​ Empowerment for the Poor: Particularly benefits women, who are highly represented in the informal sector.  Rural-to-urban migration was once seen as positive, offering better job opportunities and improved living standards. However, recent views recognize that the rapid pace of migration often outpaces cities' ability to accommodate newcomers. Urban areas struggle to create enough jobs and provide essential services like healthcare, education, and housing. As a result, many migrants end up in overcrowded informal settlements with limited access to basic services, creating challenges like unemployment, inequality, and poor living conditions. Proper urban planning and investment are needed to manage this growth effectively. The Harris-Todaro Migration Model explains the economic forces driving migration from rural to urban areas, highlighting how wage differentials influence labor allocation and migration decisions. Let's break down the key elements of the diagram: Curves and Lines: ​ Curve A: Downward-sloping curve representing the agricultural wage rate. ​ Curve M: Upward-sloping curve representing the manufacturing wage rate. ​ Line q: Intersects both curves at key points. Points: ​ Point Z: Intersection of line q with the agricultural wage rate curve. ​ Point E: Intersection of line q with the manufacturing wage rate curve. Wage Rates: WA: Initial agricultural wage rate. WA*: Adjusted agricultural wage rate. ​ WA:**: Further adjusted agricultural wage rate. ​ WM*: Adjusted manufacturing wage rate. ​ WsubM: Average manufacturing wage rate. Key Concepts: 1.​ Initial Wage Rates: The agricultural wage rate (WA) starts at a certain level, and the manufacturing wage rate (WM) is higher. 2.​ Labor Allocation: Workers migrate from rural (agriculture) to urban (manufacturing) areas in search of higher wages. 3.​ Equilibrium: Migration continues until the expected wage in the urban area (considering the probability of finding a job) equals the agricultural wage. This is where the curves intersect at points like Z and E, showing the balance between rural and urban labor forces. Conclusion: The model demonstrates that migration is driven by the difference in expected earnings between rural and urban areas. As more workers migrate to cities, the urban job market becomes saturated, and the probability of finding a job decreases. This process continues until the expected urban wage adjusts to match the rural wage, leading to an equilibrium where migration stabilizes. This model helps policymakers understand the impact of wage differentials on migration patterns and the importance of creating balanced economic opportunities across regions to manage urbanization effectively. Explanation: The equation shows that agricultural income (WsubA) is influenced by the ratio of employment in manufacturing (LsubM) to the total urban labor pool (LsubUS), multiplied by the urban minimum wage (WsubM}). Key Points: 1.​ Higher Urban Employment: If more people are employed in manufacturing (LML_M), this increases the agricultural income. 2.​ Larger Urban Labor Pool: A larger total urban labor pool (LUSL_{US}) can decrease agricultural income, as it suggests more competition for jobs. 3.​ Urban Minimum Wage: The urban minimum wage (Wbarsubm) directly affects agricultural income, indicating that higher urban wages can boost incomes in rural areas as well. Conclusion: This relationship highlights how economic factors in urban areas (like employment and wages) impact rural incomes, influencing migration decisions. If urban jobs and wages are attractive, people are more likely to migrate from rural areas to cities. The Todaro migration model has four main points: 1.​ Migration is driven by economic factors, with people weighing the financial and psychological benefits and costs of moving. 2.​ The decision to migrate is based on expected, not actual, wage differences between urban and rural areas. 3.​ The likelihood of finding an urban job depends on the urban employment rate, which is inversely related to the unemployment rate. 4.​ High urban unemployment rates are a result of the imbalance in economic opportunities between urban and rural areas in developing countries. The five policy implications are: 1.​ Reduction of urban bias: Address the uneven focus on urban areas, ensuring balanced development. 2.​ Imbalances in expected income: Focus on correcting income opportunity gaps between rural and urban areas. 3.​ Educational expansion: Avoid indiscriminate educational growth that can lead to more migration and higher unemployment. 4.​ Integrated rural development: Promote rural development programs that link economic and social improvements. 5.​ Encouraging rural growth: Support rural initiatives to reduce the pressure on urban areas and improve living standards. Integration into Expected Urban Income: This component is added to the expected urban income calculation. It reflects that if a person doesn't secure a formal urban job, they still have an alternative source of income from the informal sector. Further Elaboration: ​ Additional Wages: Different activities in the informal sector and their respective wages can be considered. ​ Probabilities Over Time: Probabilities of receiving these wages can be factored in over current and future periods, providing a dynamic view of expected income. Conclusion: This approach adds depth to the expected urban income calculation by including informal-sector wages, making it more realistic and reflective of actual urban income opportunities.  The Harris-Todaro Migration Model Example The example uses specific wage values to determine if a person will migrate from a rural area to an urban area based on expected income calculations. Given Values: 1.​ Rural Wage: $1.50 per day 2.​ Urban Modern Wage: $3.00 per day 3.​ Urban Traditional Income: $0.25 per day 4.​ Probability of Getting a Modern Job: 0.5 (50%) Expected Urban Income Calculation: ○​ The expected urban income is calculated considering the probability of obtaining a modern job and the alternative income in the urban traditional sector if the modern job is not secured. ○​ Formula: E(Y^URB) = (Probability of modern job×Urban Modern Wage) + (Probability of not getting modern job × Urban Traditional Income) 2.​ Applying the Given Values: ○​ The probability of getting a modern job = 0.5 ○​ Urban Modern Wage = $3.00 per day ○​ Probability of not getting a modern job = 1 - 0.5 = 0.5 ○​ Urban Traditional Income = $0.25 per day Therefore, E(Y^URB) = (0.5x3) + (0.5x0.25) E(Y^URB)=1.50 + 0.125 E(Y^URB)= 1.625 3.​ Comparison with Rural Income: ○​ The expected urban income ($1.625) is compared with the rural wage ($1.50). (Giunsa pagkuha si $1.50) ○​ Since $1.625 (Expected Urban Income) > $1.50 (Rural Wage), the individual would choose to migrate to the urban area. Conclusion: ​ The individual decides to migrate because the expected urban income is higher than the rural income. ​ This decision is made despite the fact that there's a 50% chance of receiving a much lower income ($0.25) in the urban traditional sector, demonstrating how expected income calculations influence migration decisions. This example illustrates the Harris-Todaro model in action, showing how individuals weigh their potential earnings in urban areas against their current earnings in rural areas when deciding whether to migrate. Environment and Development Environmental Impact: Economic growth often causes pollution and resource depletion, affecting the environment. Market Failures: Overuse of resources happens because markets don't account for environmental harm, leading to degradation. Poverty and Education: In developing countries, poverty and lack of education lead to unsustainable resource use for survival. Global Warming: Developing countries are vulnerable to climate change, which threatens their agriculture, health, and infrastructure. Sustainable Development and Environmental Accounting: Balancing economic growth with environmental preservation by tracking resource use and its impact on the environment. Population, Resources, and the Environment: Growing populations increase demand for resources, putting strain on the environment and leading to depletion. Poverty and the Environment: Poor communities often exploit natural resources unsustainably due to lack of alternatives, exacerbating environmental degradation. Growth vs. the Environment: Economic growth can conflict with environmental protection, as industrialization and consumption lead to pollution and resource depletion. Rural Development and the Environment: Rural areas face environmental challenges from agriculture and deforestation; sustainable rural development is key to balancing growth and environmental health.  Sustainable Development- means meeting the needs of the present generation without compromising the ability of future generations to meet their own needs. Capital Stock and Sustainability: Capital Stock: The total resources available, including manufactured capital, human capital, and environmental capital. Sustainability: Running down the capital stock (using it up without replenishment) is not consistent with sustainability because it would compromise future generations' well-being. Environmental Capital in Developing Countries: ​ Larger Fraction: In developing countries, environmental capital (natural resources like forests, soil, and water) constitutes a larger portion of total capital compared to developed countries. ​ Importance of Environmental Accounting: To determine whether environmental capital is increasing or decreasing, environmental accounting is needed. This process tracks the use and status of natural resources to ensure they are managed sustainably. Types of Capital: 1.​ Manufactured Capital: ○​ Examples: Machines, factories, roads. ○​ Role: Physical assets that contribute to production and economic activity. 2.​ Human Capital: ○​ Examples: Knowledge, experience, skills. ○​ Role: The capabilities and expertise of individuals that contribute to economic productivity and innovation. 3.​ Environmental Capital: ○​ Examples: Forests, soil quality, groundwater. ○​ Role: Natural resources that support life, provide ecosystem services, and contribute to economic activities like agriculture and forestry. Conclusion: To achieve sustainable development, it is crucial to balance the use of all forms of capital. This means not depleting natural resources (environmental capital) and ensuring that manufactured and human capital are maintained and developed. Environmental accounting helps monitor and manage these resources to maintain their availability for future generations. The poor are both victims and agents of environmental degradation: Victims: ​ Living in Degraded Areas: The poor often live in areas that are environmentally degraded (e.g., polluted lands or areas with poor soil quality) because these lands are cheaper, and wealthier people avoid them. ​ Lack of Political Power: People living in poverty usually have less political influence, making it harder for them to advocate for improvements in environmental conditions, such as reducing pollution. ​ Limited Economic Opportunities: The poor often face poor living conditions that hinder their ability to earn a living, making it more difficult to escape poverty. The polluted or degraded environments in which they live restrict access to productive land or resources. Agents: ​ High Fertility Rates: Poor communities tend to have higher fertility rates, which can lead to increased pressure on already limited resources and environmental degradation. ​ Short Time Horizon: Because of their immediate survival needs, the poor may focus more on short-term solutions, neglecting long-term environmental sustainability. This can lead to practices that degrade the environment, like over-exploitation of resources. ​ Insecure Land Tenure: People in poverty often lack secure ownership or rights to the land they occupy, leading to unsustainable land-use practices, as they have no long-term stake in maintaining its fertility or health. ​ Incentives for Rainforest Resettlement: In some cases, the poor may be incentivized to resettle in sensitive areas like rainforests. This leads to deforestation and environmental degradation, as they clear land for agriculture or habitation. In summary, the poor both suffer from and contribute to environmental degradation, often due to economic pressures and lack of access to resources or political power. Environmental problems impact health and productivity through: 1.​ Loss of Agricultural Productivity: ○​ Reduced crop yields due to soil degradation and climate change. 2.​ Unsanitary Conditions: ○​ Waterborne diseases from lack of clean water and sanitation. 3.​ Airborne Pollutants: ○​ Respiratory and cardiovascular issues from air pollution. 4.​ Old Environmental Kuznets Curve (EKC): This curve shows that pollution increases with rising income up to a certain point (peak), and then starts to decline. The peak pollution level occurs at a higher income level (y^O). 5.​ New Environmental Kuznets Curve (EKC): This curve also shows the same trend but peaks at a lower pollution level and at a lower income level (y^N). This suggests improvements over time due to advancements in technology, policies, and awareness.  1.​ Environmental Kuznets Curves: ○​ Old Environmental Kuznets Curve (EKC): This curve shows that pollution increases with rising income up to a certain point (peak), and then starts to decline. The peak pollution level occurs at a higher income level (y^O). ○​ New Environmental Kuznets Curve (EKC): This curve also shows the same trend but peaks at a lower pollution level and at a lower income level (y^N). This suggests improvements over time due to advancements in technology, policies, and awareness. Interpretation: The Environmental Kuznets Curve (EKC) hypothesizes a relationship between income levels and environmental degradation, typically represented as an inverted U-shaped curve. Here's a summary of this relationship in hypothetical terms: 1.​ Low-Income Stage (Rising Pollution): ○​ At low income levels, economic activity focuses on basic needs and industrialization. ○​ Environmental degradation increases as industries expand, and there is little investment in clean technologies or environmental protections. ○​ Example: Increased air and water pollution from factories in developing economies. 2.​ Middle-Income Stage (Peak Pollution): ○​ As income grows, industrialization intensifies, leading to a peak in environmental degradation. ○​ Environmental awareness remains limited, and policies to regulate pollution are often weak or nonexistent. ○​ Example: Urban smog and high levels of waste generation in emerging economies. 3.​ High-Income Stage (Declining Pollution): ○​ Beyond a certain income threshold, societies demand better environmental quality. ○​ Investments in clean technologies, stricter regulations, and a shift towards service-based economies reduce pollution levels. ○​ Example: Reduced emissions and cleaner air in developed economies through green policies and renewable energy adoption. The EKC suggests that while economic growth initially worsens environmental outcomes, it eventually leads to improvements as societies become wealthier and prioritize sustainability. However, this relationship is not guaranteed and depends on effective policies, technology, and public awareness.