Topic 1 Inequality Flashcards
Why do we care about inequality (5)
1.Welfare consideration (perceived status of indictable and happiness
2.Trust and social capital- cooperation- link between inequality and violent crimes, however direction of causality controversial
3.Socio-political instability. I.e if lots of inequality, people get the perception of a lack of social justice.
- Economic growth- inequality can facilitate and also reduce growth
- Other e.g industrialisation, health education, political reforms etc which impact inequality.
Inequality association to long run economic growth (2 points)
Research finds inequality is either irrelevant or bad for LR growth
Extreme inequality is associated with financial crises
Why do we not mind inequality? (3)
Excessive equality can be bad for economic efficiency e.g no punishment for being inefficient or not contributing
Inequality produces incentives
Inequality may be result of choice e.g
Leisure v income
Risk adversity
Short/long term income
Forms of inequality
Personal income distribution
Factor/functional distribution
Global income distribution
Personal income distribution: graphical tools, measure, data and data sources (2)
Graphical tools: Lorenz curve
Measure: Gini coefficient
Data: individual/household data
Data sources:
income tax data i.e HMRC
Family expenditure/income survey i.e BHPS
Lorenz curve diagram
Closer to perfect line of equality=more equal
Note: when Lorenz curves intersect, we need more information to determine which is more unequal.
Gini coefficient scale
(The area underneath the diagonal)
0-perfect equality
1-perfect inequality
How to calculate Gini coefficient
Divide area under Lorenz curve into trapeziums: A1, A2 etc (depending on amount of income groups)
Calculate area of each trapezium, and add together. (A)
Gini coefficient formula is
1-2A
A=area of each trapeziums added together
Area of trapezium formula
A=
(a+b) x H
/
2
Pros of Gini coefficient (3)
Straightforward to calculate
Takes into entire income distribution into account
Can be calculated even if data is not divided into percentiles etc.
Disadvantages of Gini coefficient (3)
Not additive across groups
The top or the bottom of distribution are equally weighted. (Bottom is usually more important in terms of how income is distributed for poor rather than rich)
Different Lorenz curves can indicate same Gini coefficient (same final numeric figure but different line of distribution)
Applied: most equal (3) and least equal (3)
Most equal: Sweden Norway Finland
Least: Comoros Namibia South Africa
Inequality is increasing… why? (5)
Change in industrial structure
Higher returns to education or skill premium because of technology progress
Urban/rural and regional divergences
Demographic changes e.g older people less money
Factor/functional income distribution
Factors of production-
Labour income share vs capital income share
Labour income share is 60% of total income currently
