Inequality Flashcards
(9 cards)
Why is inequality important over and above
poverty?
- Economic Efficiency – Inequality can distort economic incentives, limit access
to education and healthcare, and reduce overall productivity. - Fairness – Measuring inequality, rather than just poverty, reveals whether
economic mobility and opportunities are widely shared. Even in societies with
low poverty, extreme inequality can indicate systemic barriers that prevent
people from reaching their potential. - Well-being – Inequality matters for psychological and social well-being. People
compare themselves to others, and large income gaps can lead to
dissatisfaction, stress, and reduced happiness, even among those who are not in
absolute poverty. - Social Cohesion and Political Stability – Inequality affects social cohesion,
trust, and political stability. High levels of inequality can lead to polarization,
social unrest, and reduced cooperation within societies, even if absolute poverty
is low.
Is global inequality rising or falling?
Both claims are widespread
* Not mutually exclusive
Important considerations:
* Measurement
* Within or between countries?
* How much weight is put on extremes
* Relative or absolute?
* Trade-off between poverty and inequality?
What are the different measures of inequality?
- Lorenz curve
- Population ranked by income vs cumulative share of income
- Gini index
- The area between Lorenz curve and 45-degree line divided by
total area under 45-degree line - Mean Log Deviation (Theil(0) or Theil’s L):
- Within + between components add up to total – not always the
case for Gini index - Absolute Gini: average absolute distance between all income pairs
- Standard deviation
Inequality within or between countries?
- Inequality between countries
has fallen sharply since 2000 - Inequality within countries
has risen slightly
- What can explain that?
- Inequality between countries
has fallen sharply since 2000 - Inequality within countries
has risen slightly
Countries that have been poor have progressed faster than older countries.
The older countries see a higher level of inequality within the country because ressources and money is more and more collected at the 1% of the society.
What could cause the observed rise in between-developing-country inequality?
- Uneven Economic Growth
Some developing countries grow rapidly (e.g., Vietnam, Bangladesh), while others stagnate or regress (e.g., some Sub-Saharan African nations). Reasons include:
Better governance and institutions
Political stability
Strategic integration into global trade
Investment in education and infrastructure
Data concerns – potential sources of bias?
- Is income/consumption a good proxy for welfare? Partially — but with caveats. Consumption is generally considered a better proxy for welfare in developing countries than income because it’s more stable over time and reflects actual living standards (especially among the poor).
Income can be more volatile, misreported, or seasonal (especially in informal/agricultural economies).
However, both miss aspects of welfare such as:
Health, education, security, leisure
Quality of public services
Environmental factors
Sampling errors
* Selective compliance
* Sampling frame and population movements
- Underreporting in sample
- Within-household inequality
- Price measurement errors:
- If only one price index per country is used, we neglect urban/rural differences, leading to bias in within-country inequality.
How do sampling error and underreporting affect within-country
inequality?
a. Sampling Errors
These arise when survey data do not accurately reflect the true population distribution.
Selective compliance: If rich or poor households are less likely to respond, the inequality estimate gets biased.
Example: If the wealthy under-participate, inequality will appear artificially low.
Sampling frame problems & population movements:
If surveys miss certain groups (e.g., migrants, homeless, urban slum dwellers), you’re excluding groups likely at the bottom or top of the distribution.
Rapid urbanization or displacement can cause mismatches between the frame and real population → biases inequality measures.
Effect: Sampling errors can understate or overstate inequality depending on who is missed.
b. Underreporting in Sample
This refers to respondents inaccurately reporting income or consumption.
Underreporting by the rich: High-income households may hide or downplay their earnings, especially if income is from informal or untaxed sources. This leads to an underestimation of top-end inequality.
Underreporting by the poor: Often due to recall errors or fear of losing social benefits. This could distort the lower tail of the distribution.
Consumption smoothing: The poor might borrow or rely on social networks, making their consumption seem more stable than their income actually is.
Effect: Underreporting often leads to systematic underestimation of inequality, especially at the top end of the distribution.
Has the globalization elephant left the room? Figure 5
Yes it seems like it, due to the slowdown of western countries after 2008. At the same time most of Asia has increased its growthrates, that means that people has not got porrer but just relative less richer in western countries compared to Asia, especially China and India. The bottom third of some European countries and the US, has now fallen down to the middle of the percentile richests, around the 50 percentile. More and more Asian people enter the top 10-percentile.
The most notable change is that the median income has increased in size, due to faster growth of asien countries.
The future would see even more people in the median income group, due to fast growth in the lowest percentile in great contrast to the elephant curve. We would especially look towards india and population dense countries in Africa, e.g. Nigeria, Congo, etc.
