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Development Economics

Problem Set 2

As I mentioned in the class, in this assignment you would use the real world data to explore the relationship between poverty, inequality, and income. I have downloaded the attached data from World Development Indicators for some of the key variables related to our measures. You will see that I have included more than one measure for the same variable. For example, to measure income inequality I have included  the gini coefficient, as well  as the income  shares  of the  top  and bottom 20%  of population. Similarly, I have included different series for income. You can choose to create your own measures from the included variables if you want (for instance, different methods of creating growth rate). The income is from 2016. I have included both 2016 and 2015 data for other variables. You should 2016 data where available and use 2015 data only when 2016 isn’t available.

For the key variables of interest – poverty, income, and inequality.

1)   Report a table of summary statistics – Mean, Median, Min, Max, Std. Dev., 25th percentile and coefficient of variation.

Based on the summary stats, answer the following questions.

a.    What is the average income, inequality?

b.    Create a dummy variable to divide countries into three different income groups (hint: you don’t have to use the very strict definition of the GNI per capita (PPP) that the World Bank uses). What proportion of the sample is rich/poor?

c.    What is the average inequality for the rich countries?

d.   Find a cross tabulation of inequality and poverty by income group?

2)   What is the correlation between inequality, poverty, and income?

3)   What is the interquartile range for inequality? What is the variance in inequality? Do inequality and other variables co-vary?

4)   Provide the five-number summary for inequality, poverty, and income, for the middle income countries only.

5)   Plot a scatterplot of poverty and inequality. Include a line offit.

6)   Now you are ready to run the regressions - Regress and interpret the effect of (a) income on poverty; (b) income on inequality; and (c) inequality on poverty.

7)   Instead of using income, use the dummy variables for whether the country is rich vs poor in your regression of income on poverty. Interpret the coefficients carefully.

You can choose any of the three relationships above to explore it further.

8)   Do you expect any non-linearity in your regression, in which variable? Why? Test your hypothesis.

9)   Run diagnostic tests i.e. Are the error terms normal? Are they homoscedastic? Is there any evidence of autocorrelation, outliers, etc.?

10) Bonus: Anything else you like to do. (Don’tgo overboard).

PS: Please submit both your wordfile as well as the final data file and codeso I can replicateyour results.