Resume
Summary - Development Economics
- Cours
- Development Economics
- Établissement
- Vrije Universiteit Brussel (VUB)
Summary of the papers that are required to read for the exam
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CHAPTER 2: POVERTYThe paper by Ruggeri Laderchi et al. (2003) compares four approaches to defining and measuring poverty: the monetary
approach, the capabilities approach, social exclusion and the participatory approach. The key points applied to the topic of
poverty are as follows:
Four Approaches to Understanding Poverty
- Monetary approach
o Definition: Poverty is viewed as a shortfall in income or consumption relative to a poverty line.
o Advantages: Easy to measure and widespread in use, with strong economic rationale.
o Disadvantages: Neglects other dimensions of well-being, such as access to social goods, and is often imposed
without input from the poor themselves
- Capabilities approach
o Definition: Inspired by Amartya Sen, focuses on what people are capable of doing and being, such as health,
education and social participation.
o Benefits: Emphasizes people's actual freedom to live a life of dignity.
o Disadvantages: Difficult to operationalize; requires choices about which capabilities are essential and how to
measure them
- Social exclusion
o Definition: Poverty is seen as a process by which individuals or groups are excluded from participation in
normal social activities.
o Benefits: Focuses on structural and relational aspects of poverty, such as discrimination and marginalization.
o Disadvantages: Difficult to define and measure, especially in developing countries, due to differences in norms
and structures
- Participatory approach
o Definition: Poverty is defined based on what people themselves say is important.
o Advantages: Gives space to the voices of the poor, making the definition more context-specific.
o Disadvantages: Costly, and participants' inputs can be influenced by social expectations or conditioning
Empirical Comparisons
- Data from Peru and India: There is little overlap between the people identified as poor by the four methods.
o Almost half of the population was considered poor by the monetary approach but not by the capability
approach, and vice versa.
- Importance of Definitions: Different approaches emphasise different dimensions of poverty, which has policy
implications.
Implications for Policy
- Monetary Approach: Focuses on income generation.
- Capacity Approach: Emphasises education, health and social goods.
- Social Exclusion: Requires structural reforms, such as combating discrimination.
- Participatory Methods: Suitable for local policies and context-specific interventions.
Conclusion
Ruggeri Laderchi et al stress that the lack of consensus on poverty definitions has implications for who is helped and how.
Poverty is a multidimensional phenomenon that requires different policy approaches. Transparency and context-specific choices
are crucial to combat poverty effectively.
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, CHAPTER 2: POVERTY (PRESENTATION)
Easterlin et al (2010) revise and extend the analysis of the Happiness-Income Paradox. They show that although there is a
positive correlation between income and happiness within and across countries at one point in time, this relationship is absent in
the long run. The paradox applies not only to developed countries, but also to emerging economies and countries in transition
from socialism to capitalism.
Key Findings
- No long-term relationship between happiness and income:
o In both developed and developing countries, average life satisfaction remains constant even when per capita
income grows significantly.
o Examples include countries such as China and Chile, where GDP per capita doubled in less than 20 years
without a significant increase in life satisfaction.
- Short-term relationship is positive:
o In the short term, there is a positive correlation between changes in income and happiness, especially during
economic recessions or growth.
o However, this relationship disappears on longer time horizons (at least 10 years).
- Social comparisons and hedonic adaptation:
o The paradox can be explained by social comparisons: people assess their wealth relatively to others.
o Hedonic adaptation ensures that individuals quickly get used to higher incomes, so the impact on happiness is
temporary.
- Differences between countries:
o In Latin American countries such as Brazil and Mexico, no correlation has been found between economic
growth and financial satisfaction.
o In transition countries (e.g. Russia and Estonia), the data showed a V-shaped pattern during economic
transitions, with short-term fluctuations but no long-term trend.
Methodology
- Datasets and populations:
o Data from the Latinobarometer, World Values Survey and Eurobarometer cover 17 developed, 11 transition
and 9 developing countries.
o Happiness measures include life satisfaction (10-point scale) and financial satisfaction (5-point scale).
- Statistical analysis:
o Long-term trends were analysed with regressions of change in life satisfaction on growth in real GDP per
capita.
o For short-term fluctuations, deviations from trends in income and happiness were studied.
Implications for Poverty
- Income is not the only measure of well-being:
o Happiness and well-being are not entirely determined by income; health care, family relationships and social
cohesion play a larger role.
o This suggests that poverty measures aimed only at increasing income do not necessarily lead to improved well-
being.
- Redefining poverty reduction:
o Policies should focus on multidimensional poverty indicators, such as health, education and social inclusion.
o Improving subjective well-being requires interventions that go beyond pure economic growth.
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,Criticism of the Paradox
- The Happiness-Income Paradox is often criticised for methodological limitations. Criticisms include:
o Cross-section versus time series: Some studies confuse the positive short-term relationship with the long-term
absence of a correlation.
o Data artifacts: Fluctuations in questionnaire design and interpretation of results affect conclusions about
happiness and income.
Conclusion
Easterlin et al. emphasise that economic growth does not guarantee a long-term increase in happiness. This finding highlights
the need for policies that look beyond GDP growth and focus on improving quality of life and social cohesion. The paradox
remains a powerful tool to illustrate the limitations of income-focused poverty measures.
CHAPTER 4: INEQUALITY
Trapeznikova (2019) offers a detailed overview of the methods and challenges in measuring income inequality. The paper
highlights that different measurements can yield different results depending on the measure chosen and the purpose of the
analysis. The paper argues that a good understanding of inequality is essential for designing effective policies.
Dimensions of inequality:
- Income inequality:
o Refers to the distribution of labour income, capital income (such as dividends and interest) and government
benefits.
o Differences between individuals or households in pre- and post-tax income.
- Inequality in assets:
o Refers to the distribution of assets such as property, savings and shares.
o Wealth inequality is often higher than income inequality and is influenced by taxation, inheritance and
ownership structures.
- Consumption inequality:
o Consumption is seen as a better measure of sustainable inequality because it can smooth out temporary
shocks to income through saving and borrowing.
o More relevant for developing countries, where income data are often unreliable.
- Unit level of measurement:
o Individual versus household: Household income data correct for shared consumption and insurance
mechanisms within households.
o Equivalence scales, such as the root scale, are used to account for economies of scale in households.
Measurement tools:
- Lorenz curve: Visual representation of income distribution.
- Gini coefficient: Measures inequality across the income distribution; ranging from 0 (complete equality) to 1 (complete
inequality).
- Percentile ratios: For example, the 90/10 ratio that measures the ratio of highest to lowest incomes.
- Palma ratio: Compares the incomes of the richest 10% to the poorest 40%.
- Theil index: Can distinguish inequality within and between groups, but is less intuitive
Evolution of inequality over time.
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, - Differences between countries:
o Countries such as Norway have low Gini coefficients (<0.3), while South Africa and Brazil show high values
(>0.5).
o Historical and institutional factors, such as tax structures and social benefits, influence inequality.
- Temporal trends:
o In developed economies, income inequality has increased since the 1980s, partly due to globalisation and
technological progress.
o Government benefits reduce inequality, especially at the bottom of the income distribution.
Policy implications
- Choice of metric:
o The choice between metrics such as the Gini coefficient and Palma ratio depends on policy goals, e.g.
redistribution or poverty reduction.
- Fiscal and social reforms:
o Taxes and transfers can reduce inequality but require fine-grained monitoring of effects on income
distribution.
- Improve data quality:
o Reliable administrative data and long-term analysis are essential to adequately measure and address
inequality.
Conclusion
Trapeznikova stresses that measuring inequality is complex but essential for effective policy. Using multiple measures, tailored
to specific contexts and policy goals, provides the most complete insights into economic inequality. This is especially important in
addressing poverty and promoting inclusive growth.
CHAPTER 4: INEQUALITY
The paper by Cerra et al. examines the complex relationships between economic growth, inequality and poverty. The central
theme is how these variables mutually influence each other, with a specific focus on the role of policy in shaping inclusive
growth. The paper highlights that growth can be effective in reducing poverty, but the impact on inequality depends on the
nature and sources of growth.
Evolution of Inequality and Poverty
- Inequality trends:
o Income inequality has increased in advanced economies since the 1980s, while it has remained relatively stable
in emerging markets and developing countries.
o Largest increases in market insecurity were measured in countries such as the US, while redistribution through
taxes is less effective in developing countries.
- Poverty reduction:
o Globally, poverty rates fell, especially in emerging markets such as China and India.
o The decline is mainly attributed to economic growth, although changes in income distribution also play a role.
How does Growth Affect Inequality and Poverty?
- Classical Theories:
o According to neoclassical growth models, technological progress leads to higher productivity, which can affect
both poverty and income inequality.
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