Quantitative Project: World Income and Health Inequality
Based on what we have discussed so far, it seems that there is a lot of variation around the world in terms of income, wealth, education, health status, and many other characteristics.
And these characteristics seem to be related with one another. For example, people from wealthier countries tend to live longer.
In this project, you are asked to use international data to empirically investigate the relationship between income and health status. The following sections provide a general description of this project and raise questions that you need to answer.
Objectives:
A. Substantive: Students will be able to
1. investigate world inequality in income.
2. investigate world inequality in health status.
3. investigate the relationship between income and health status.
B. Quantitative Skills: Students will be able to
1. sort a single variable and examine its distribution
2. calculate within-group adjusted-means weighted by populations
3. produce a scatter plot to investigate the relationship between two variables
Data and Variables
The data are from "2008 World Population Data Sheet" published by the Population Reference Bureau.
Three variables are used for this project:
Gross National Income (GNI) PPP per capita
Life expectancy
Population (in millions)
These three variables for more than 100 countries are already compiled in an Excel file.
Validity of the Measurement
Income level
Q_1: Why can't Gross National Income be directly used as a measure of income level? What does the PPP adjustment take into account? Why has it to be per capita?
Health Status
Q_2: How is life expectancy defined? Why not to use Crude Death Rate (CDR)? What is the advantage of using life expectancy?
Data Analysis
Corresponding to the three objectives stated above, the analysis section is composed of the following three parts:
1. Investigation of income inequality between rich and poor countries
Q_3: Find out the top five countries with the highest GNI PPP per capita and the bottom five countries with the lowest values. List these
countries' names and their income.
Q_4: How much is the difference between the highest and lowest country?
Q_5: If we want to find out the overall difference between these two groups, can we simply take an average of the five values of GNI PPP
per capita within each group and compare the two means? Why or why not?
A better way is to compare the population-weighted means. We first need to calculate the total income for each country by multiplying GNI PPP per capita by its population.
Then, add all five total income within each group. Finally, divide the sum within each group by the corresponding sum of population.
Q_6: What is the average income for either group? How much is the difference and how to interpret it?
2. Investigation of inequality in life expectancy
Q_7: Find out the top five countries with the highest life expectancy and the bottom five countries with the lowest values. List these countries' names and their life expectancy.
Use the same method for Q_3 to answer this question.
Q_8: How much is the difference between the highest and lowest country?
Q_9: If we want to find out the overall difference between these two groups, can we simply take an average the five values of life expectancy within each group and compare the two means? Why or why not?
Similarly, a better way is to compare the population-weighted means. We first need to calculate the total expected life-years for each country by multiplying life expectancy by its population. Then, add all five total expected life-years within each group. Finally, divide the sum within each group by the corresponding sum of population.
Q_10: What is the average life expectancy for either group? How much is the difference and how to interpret it?
3. Investigation of the relationship between GNI PPP per capita and life expectancy
One intuitive way to assess such a relationship is to put these two variables in a two-dimension chart, where GNI PPP per capita takes the horizontal axis and life expectancy the vertical axis. Each country is represented by a single dot, whose position on this chart is determined by the values of these two variables.
This can be done in Excel:
Highlight all the numbers of the two columns of "GNI PPP per
Capita" and "life expectancy;"
Click "Insert" on the command bar, and select "Chart";
Select the "XY (scatter)" chart type;
Q_11: Produce a scatter plot chart for these two variables by using Excel.
What kind of general trend does it show? Some dots seem to be distant from the bulk of the dots. They are called outliers. Find three of them. Which countries do these dots represent? Why are they outliers? What are the possible explanations for them?
Conclusion and Discussion
Q_12: Based on the findings above, what conclusions can be drawn about income and health inequality between countries in the world?
What is the general relationship between income and health status? Why do you think there is such a relationship? What does the existence of the outliers tell us regarding the impact of income on health? Does higher national income always lead to better health of the citizens?
Overall, what can be learned from this study regarding how to maintain or improve people's health?
Type your answers to all the questions above on separate paper.
Attachment:- Simplified Project Data.rar