Empirical Project 5 Solutions

These are not model answers. They are provided to help students, including those doing the project outside a formal class, to check their progress while working through the questions using the Excel or R walk-throughs. There are also brief notes for the more interpretive questions. Students taking courses using Doing Economics should follow the guidance of their instructors.

Part 5.1 Measuring income inequality

  1. China and the US are used as examples.

China, 1980
Cumulative share of the population (%) Cumulative share of income (%)
0 0.00
10 3.14
20 7.63
30 13.43
40 20.47
50 28.82
60 38.55
70 49.92
80 63.28
90 79.33
100 100.00

Table showing cumulative income shares for China (1980).

Solution figure 5.1 Table showing cumulative income shares for China (1980).

China, 2014
Cumulative share of the population (%) Cumulative share of income (%)
0 0.00
10 0.92
20 2.84
30 5.81
40 9.95
50 15.44
60 22.55
70 31.75
80 43.95
90 61.43
100 100.00

Table showing cumulative income shares for China (2014).

Solution figure 5.2 Table showing cumulative income shares for China (2014).

United States, 1980
Cumulative share of the population (%) Cumulative share of income (%)
0 0.00
10 2.29
20 6.22
30 11.52
40 18.08
50 25.89
60 35.04
70 45.73
80 58.44
90 74.39
100 100.00

Table showing cumulative income shares for the US (1980).

Solution figure 5.3 Table showing cumulative income shares for the US (1980).

United States, 2014
Cumulative share of the population (%) Cumulative share of income (%)
0 0.00
10 1.88
20 5.14
30 9.66
40 15.41
50 22.45
60 30.92
70 41.09
80 53.58
90 69.90
100 100.00

Table showing cumulative income shares for the US (2014).

Solution figure 5.4 Table showing cumulative income shares for the US (2014).

Lorenz curves for China.

Solution figure 5.5 Lorenz curves for China.

Lorenz curves for the US.

Solution figure 5.6 Lorenz curves for the US.

  1. Solution figures 5.7 and 5.8 show the Lorenz curves for China and the US with Gini coefficients labelled.

Lorenz curves for China, with labelled Gini coefficients.

Solution figure 5.7 Lorenz curves for China, with labelled Gini coefficients.

Lorenz curves for the US, with labelled Gini coefficients.

Solution figure 5.8 Lorenz curves for the US, with labelled Gini coefficients.

  1. Measures chosen here are the share of income going to the top 1%, and the share of children living in relative poverty.

    • Share of income going to the top 1%: This measure looks at the high end of the income distribution (the right tail). Larger values indicate that the very rich have a larger share of the income, and that there is therefore more inequality between the very rich and the rest of society. However, this is a narrower measure of inequality than the Gini coefficient because it only tells us about how the very rich are doing.

    • Share of children living in relative poverty: This measure is defined as the share of children living in a household with half of the disposable income of the median household. A larger value indicates that a larger proportion of children are living in relative poverty.

Part 5.2 Measuring other kinds of inequality

Mortality inequality Gini coefficients (1952–2002).

Solution figure 5.9 Mortality inequality Gini coefficients (1952–2002).

Countries ranked according to mortality inequality Gini coefficients in 1952.

Solution figure 5.10 Countries ranked according to mortality inequality Gini coefficients in 1952.

Countries ranked according to mortality inequality Gini coefficients in 2002.

Solution figure 5.11 Countries ranked according to mortality inequality Gini coefficients in 2002.

  1. This example looks at access to essential medicines.

Median availability of selected generic medicines in the private sector.

Solution figure 5.12 Median availability of selected generic medicines in the private sector.

Median availability of selected generic medicines in the public sector.

Solution figure 5.13 Median availability of selected generic medicines in the public sector.

  1. This example looks at the gender gap in primary education.

Female pupils as a percentage of total enrolment in primary education.

Solution figure 5.14 Female pupils as a percentage of total enrolment in primary education.

Change (%) in female pupils’ share of total enrolment in primary education.

Solution figure 5.15 Change (%) in female pupils’ share of total enrolment in primary education.