Lorenz Curve and Gini Coefficient

Using data from this spreadsheet cPreview the documenthoose two countries that you would like to compare and filter the data so only the values for 1980 and 2014 are visible. You will be using this data as the basis for your Lorenz curves.

Use the tables you have made to draw Lorenz curves for each country in order to visually compare the income distributions over time.

Using your Lorenz curves:

Compare the distribution of income across time for each country.
Compare the distribution of income across countries for each year (1980 and 2014). Of course you will recognize that it will be helpful to have a Gini coefficient to do this, You might want to use this calculator (Links to an external site.) to come up with one. You should have four coefficients in total. Label each Lorenz curve with its corresponding Gini coefficient, and check that the coefficients are consistent with what you see in your charts.
Now, calculate some ratios:

90/10 ratio = the ratio of Decile 10 income to Decile 1 income

90/50 ratio = the ratio of Decile 10 income to Decile 5 income (the median)

50/10 ratio = the ratio of Decile 5 income (the median) to Decile 1 income.

For each of these ratios, explain why policymakers might want to compare the two deciles in the income distribution.
What kinds of policies or events could affect these ratios?
We will now compare these summary measures (ratios and the Gini coefficient) for a larger group of countries, using OECD data. The OECD has annual data for different ratio measures of income inequality for 42 countries around the world, and has an interactive chart function that plots them for you.

Go to the OECD website (Links to an external site.) to access the data. You will see a chart similar to Figure 5.4, showing data for 2015. The countries are ranked from smallest to largest Gini coefficient on the horizontal axis, and the vertical axis gives the Gini coefficient.

Compare summary measures of inequality for all available countries on the OECD website:
Plot the data for the ratio measures by changing the variable selected in the drop-down menu ‘Gini coefficient’. The three ratio measures we looked at previously are called ‘Interdecile P90/P10’, ‘Interdecile P90/P50’, and ‘Interdecile P50/P10’, respectively. (If you click the ‘Compare variables’ option, you can plot more than one variable (except the Gini coefficient) on the same chart.)
For each measure, give an intuitive explanation of how it is measured and what it tells us about income inequality. (For example: What do the larger and smaller values of this measure mean? Which parts of the income distribution does this measure use?)
Do countries that rank highly on the Gini coefficient also rank highly on the ratio measures, or do the rankings change depending on the measure used? Based on your answers, explain why it is important to look at more than one summary measure of a distribution.

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