Empirical Project 4 Measuring wellbeing

Learning objectives

In this project you will:

Key concepts

  • Concepts needed for this project: mean.
  • Concepts introduced in this project: index, time series data, cross-sectional data, geometric mean, and the natural log transformation.


CORE projects

This empirical project is related to material in:

  • Unit 4 of Economy, Society, and Public Policy
  • Unit 3 of The Economy.

GDP per capita is a widely used summary measure of incomes in a country. It is calculated by dividing Gross Domestic Product (GDP)—the total value of all the goods and services produced in a country in a given period, such as a year—by the population of the country. GDP per capita is therefore a measure of average annual income in a country.

GDP per capita is commonly used in economics to compare living standards across countries or measure progress in living standards over time. The rationale is that higher income and expenditure means a greater ability to spend on goods and services, which in turn increases material wellbeing. Since material wellbeing can contribute to non-material wellbeing, we might also expect countries with higher GDPs per capita to have higher non-material wellbeing. But how do we measure non-material wellbeing? And does a higher GDP per capita necessarily mean a higher non-material wellbeing?

An index is formed by aggregating the values of multiple items into a single value, and is used as a summary measure of an item of interest. Example: The HDI is a summary measure of wellbeing, and is calculated by aggregating the values for life expectancy, expected years of schooling, mean years of schooling, and gross national income per capita.

To answer these questions, we will first learn how different variables can be summarized in an index by looking at GDP and its components. We will then learn how indices of non-material wellbeing are constructed, and compare an index of material wellbeing (GDP per capita) with an index of non-material wellbeing (the Human Development Index).

Working in Excel

Working in R