Development Economics

  1. The concept of development is ___________
  2. The MDG goals:
    • Eradicate extreme poverty and hunger
    • Achieve universal primary education
    • Promote gender equality
    • Reduce child mortality
    • Improve maternal health
    • Combat HIV/AIDS
    • Ensure environmental sustainability
    • Develop a global partnership for development
  3. The seven dimensions of developmet
    • 1. Income and income growth
    • 2. Poverty and hunger
    • 3. Inequality
    • 4. Vulnerability
    • 5. Basic needs in education, health, sanitation and housing
    • 6. Environmental sustainability
    • 7. Quality of life
  4. Measuring Income and Income Growth:
    • Compare over time: adjust for inflation
    • Compare accross countries: bring income figures into a single currency
  5. Measuring Poverty:
    • Poverty Gap Index: uses indicator of wellbeing (income or consumption) and poverty line
    • Head Count poverty index: % of population living in households with income per capita ¡ poverty line
  6. Measuring Inequality:
    Gini Coefficient: describe chart
  7. Measuring Basic Needs:
    • Measure by achievements or access to basic needs
    • Basic Needs include: Health, education, nutrition
    • Human Development Index
  8. Measuring Quality of Life:
    Gross National Happiness Index: uses good health, psychological wellbeing, education, diversity, ect..
  9. "Convergence Club"
    East Asia and Pacific, South Asia
  10. Most of poverty and hunger is located:
    South Asi and Sub-Saharan Africa, and poverty is increasing in these regions
  11. China's recent poverty reduction:
    Only China has been successful in sharply reducing the number of poor, taking more than 600 million people out of poverty in the last 25 years.
  12. China has reduced poverty, however inequality has increased:
    Pure growth is inequalizing, especially when growth is rapid.
  13. Explain Brazil's reduction in inequality:
    Social programs can be used to counteract this effect and achieve greater equality with growth (e.g., Brazil).
  14. Explain rise of a world middle-class phenomena:
    Because convergence benefited some very large, initially poorest, countries (particularly China and India) international inequality with countries weighted by population size has declined steadily.
  15. What happens to Human Development Index as income increases:
    As income increases, countries converge to fairly uniform levels of HDI
  16. Threats to sustainability growth:
    • Climate Change
    • Energy Demand: Energy consumption tracks closely rising per capita income
    • Deforestation: Higher prices for resources in the future
  17. Effect of income to Gross National Income Index:
    • Income is important for happiness at low levels of income
    • For high levels of income additional income is not as important as freedom of choice, quality of work, ect..
  18. Why is geography important to economic development:
    • Agricultural productivity: climate, land, water, ecology, etc.
    • Transportation cost: trade, coastal lines, ports, roads, other logistics and
    • infrastructure
    • Others: population density, disease burdens
  19. Geography hypothesis: Diamond (1997), Sachs (2001):
    Explains economic prosperity by geographic, climatic, or ecological differences across countries
  20. Institution hypothesis: Olson (2000), Acemoglu et al (2001)
    Explains differences in economic prosperity by the organization of society (Focuses on enforcement property rights, contraints on powerful groups, equal oportunity)
  21. Geography vs institution hypothesis:
    • Both hypotheses predicts persistent economic performance
    • Difficult to distinguish by looking at correlations
    • Natural experiments: one factor changes while other potential determinants for the outcomes of interest remain constant
  22. Natural Experiment example:
    • global colonization by Europeans starting in
    • the 15th century
  23. Geography vs Institution: Conclusions
    • Institutions have a large and quantitatively important effect on economic prosperity today.
    • Geography seems to play a relatively small role in the large cross-country differences in prosperity. It cannot be the case that climate, ecology, or disease environments of the tropical areas induced poverty today
  24. In order to better understand contemporary growth prospects, it is useful to examine _______________
    • historical growth patterns
    • Ex: Growth in Europe and North America (1580/.2% Netherland, 1820/1.2% UK, 1890/2.2% USA) --> Leaders change, growth rate accelerates
  25. Kuznet;s 6 characteristics of modern growth:
    • High rates of per capita income and population growth
    • High rates of Total Factor Productivity (TFP) increase
    • High rates of economic structural transformation
    • High rates of social, political, and ideological transformation
    • International economic outreach
    • Limited international spread of economic growth
  26. T/F: The historical growth of current industrial countries directly applies to modern developing countries
  27. Why cant we apply Historical Growth Experience:
    Population size has changed, international migration, international trade, stability and flexibility of political and social institutions.
  28. Impact Evaluations:
    • Ex-Ante: measures expected costs and benefits
    • Programmatic: tracks progess
    • Comprehensive Expenditure: tracks use of financial resources
    • Impact Analysis: assigned causality between specific interventions and observed changes in outcomes.
  29. Objectives of Impact Evaluations:
    • Accountability
    • Result-based management
    • Generic Lessons
  30. Regression Analysis:
    • Try to see if x depends on y, calculate errors in case of any outliers.
    • B1 = slope
  31. Challenge of Impact Evaluation:
    • Determine the causality between X (intervention) and Y(outcome)
    • Causality: X causes Y
    • Reverse causality: Y causes X
    • Simultaneity: X causes Y and Y causes X
    • Omitted variable bias: There exists a third variable Z such that Z causes X and Z causes Y
  32. Techniques for impact evaluation:
    • Randomized control trials (RCT)
    • Instrumental variable (IV)
    • Propensity score matching (PSM)
    • Difference-in-Difference (DID)
    • Regression Discontinuity (RD)

    • Randomized control trials (RCT): (Experimental)
    • Randomization over a sufficiently large number of units creates statistically identical treatment and control groups. Impact can then be measured by simple difference in the outcome
    • variable between treatment and control groups
    • Examples: Progresa in mexico, immigration policy in new zealand
  33. Problems of RCT evaluation:
    • 1. Hawthorne effects: A randomization bias caused by subjects’ knowledge of study which causes change in natural behavior.
    • 2. Contamination or spillover effects: subjects excluded do receive treatment, subjects selected do not receive treatment
    • 3. Can we apply RCT to large populations?
  34. Instrumental Variable:
    Uses relevance, exogeneity and exclusion restriction in order to evaluate program outcome. (How Z, the causual variable, influences program)
  35. Problems of IV:
    • It is very difficult to find an instrument that meets the three conditions
    • The instrumented causal variable only explains the outcome in terms of its variation due to the instrument
  36. Propensity score matching:
    Select a control group that are comparable to participants on a large number of observable essential characteristics. (unobserved characteristics are similiar accross treated and control groups)
  37. Problems of PSM:
    • PSM can be misused because the underlying assumptions are strong:
    • Self-selection: Technology adoption, microfinance program participation
    • Placement bias
  38. Difference in Difference Method:
    • Measure changes over time
    • However, many other things have changed during the same period that may have affected the outcome: subtract the change observed over time among
    • non-beneficiaries
    • Ex: Duflo Indonesia
  39. the ”parallel trend” assumption
    In the absence of the program, the change in the outcome variable among beneficiaries would have been identical to that among non-beneficiaries
  40. Problems with DID:
    • Main issue: Omitted variable bias
    • Reforms are not introduced randomly, independently of contextual changes
  41. Regression Discontinuity Design
    • Eligibility to a treatment is determined by meeting a threshold value, people just below and above the threshold are identical
    • Ex: Li and Meng
  42. Problem of RDD
    The impact is strictly measured only around the threshold
  43. Internal Validity:
    • showing that the control group has been properly
    • chosen against the treatment group
  44. External Validity:
    apply results to a broader population
  45. Characteristics of poverty groups:
    • Rural poverty
    • Bigger fimaly size
    • Less educated
    • Work disproportionately more in the informal sector
    • More engaged in agriculture and more self-employed
    • Ethnic minorties, indigenous groups
  46. Types of poverty:
    • Never poor: 41%
    • Transitory poor/Temporarily poor: 36%
    • Chronic poor: 18%
    • Persistent poor: 5%
  47. Interventions to reduce poverty:
    • Pro-poor income growth with emphasis on increased access, opportunities and productivity for the poor
    • Social safety nets and social assistance programs for the poor
  48. Indicators of Inequality
    • Gini coefficient
    • Theil Entropy Index
    • Kuznets Ratio
  49. Gini coefficient:
    • Most popular
    • cannot measure contribution of each population group to total inequality
  50. Theil Entropy Index:
    • Additively decomposable accoss population groups
    • cannot be used if there are negative incomes in population
  51. Kuznets ratio:
    • The ratio of the percentage of total income by the richest 20% to the percentage of total income by the poorest 20%
    • It is good to characterize what happens at the extremes in the distribution of income
  52. Decomposition of Inequality
    • By population
    • By sources of income
  53. Kuznet Hypothesis:
    higher level of GDP will itself subsequently take care of inequality. Not true
  54. Does the ”Kuznets hypothesis” imply the causal relationship between growth and inequality? Explain.
  55. No. Simultaneity - GDPpc and inequality influence each other at the same time; Omitted variable bias both are jointly
  56. Relationship between growth and inequality:
    • Growth has on average no impact on inequality
    • A higher inital inequality implies that subsequent growth has less capacity to reduce poverty
    • Hence, the quality of growth for poverty reduction depends on the initial level of inequality.
  57. inequality bad or good for growth
    • If it is bad, then reducing it would help accelerate growth, with the associated benefits for poverty reduction
    • If it is good, then we have to deal with a difficult policy trade-off Empirical results are mixed
  58. Why rising income inequality may hurt economic growth?
    Social and political instability; reduce investment in human capital; reduce overall investment; reduce work incentives; decrease growth of domestic consumption.
  59. Channels through which inequality may affect growth:
    • 1. Aggregate rate of savings and growth
    • 2. Social and political stability
    • 3. Access to financial capital
    • 4. Aggregate investment in human capital
    • 5. Inequality and incentives
    • 6. Inequality and domestic market size
  60. Indicators of Education:
    • Gross Enrollment rate
    • Out of scool Children
    • Grade completion rate
    • Grade retention rate
    • The educational attainment
    • Test Scores
  61. Why is education important for development?
    High correlation between education and level of income across countries
  62. Relationship: Education and Health
    • High correlation between education and level of income across countries
    • Education lead to higher income and to less risky choices of occupation
    • Education increases people’s understanding of sanitation and hygiene, encourages their use of health care systems
  63. Explain the reverse causality challenge in the relationship between eduaction and health:
    • Healthier people may be better able to succeed in the
    • classroom, not education leads to good health
  64. Relationship: Education and fertility
    • Woman’s education reduces her desired family size
    • Education increases the opportunity cost of women’s time
    • Better educated women may have higher aspirations for their children
  65. Social return of education:
    • Strong positive social externalities associated with individual education
    • Your education helps create more jobs
    • Improves the human capital of your children
  66. What determines the levels of schooling?
    • Supply side
    • Demand Side
  67. Supply Side determinants:
    • Quantity: distance to school, hours of instruction
    • Quality: teacher attendance, teachers level of training, school resources
  68. Supply side Problems:
    • Under-investment
    • Poor incentives for teachers
  69. Supply Side Examples:
    • Incentives for teachers: Dufflo (incentive for teachers increase there pressence which increases learning?)
    • Class siz: Angrist and Lavy (Effect of class size on learning outcomes?)
  70. Demand Side Determinants:
    • 1. Intrinsic value of schooling: i
    • 2. Expected return from schooling: W1 − W0
    • 3. Direct cost of schooling: c
    • 4. Opportunity cost of schooling: W0
    • 5. Discount factor: r
  71. Key factor influencing return to education:
    • Opportunities pro schooling: use education for income generation. Education has little value in traditional agriculture; it does have value when there are opportunities to adopt new agricultural technologies that require skills
    • Opporunities against schooling: Cost of schooling, child labor is valuable to the household
Card Set
Development Economics
midterm 1