Contents

  1. Preface
  2. A note to instructors
  3. Producing Doing Economics
  4. List of resources
  5. 1 Measuring climate change
    1. Learning objectives
    2. Introduction
    3. Working in Excel
      1. Part 1.1 The behaviour of average surface temperature over time
      2. Part 1.2 Variation in temperature over time
      3. Part 1.3 Carbon emissions and the environment
    4. Working in R
      1. Getting started in R
      2. Part 1.1 The behaviour of average surface temperature over time
      3. Part 1.2 Variation in temperature over time
      4. Part 1.3 Carbon emissions and the environment
    5. Working in Google Sheets
      1. Part 1.1 The behaviour of average surface temperature over time
      2. Part 1.2 Variation in temperature over time
      3. Part 1.3 Carbon emissions and the environment
    6. Working in Python
      1. Getting started in Python
      2. Part 1.1 The behaviour of average surface temperature over time
      3. Part 1.2 Variation in temperature over time
      4. Part 1.3 Carbon emissions and the environment
    7. Solutions
      1. Part 1.1 The behaviour of average surface temperature over time
      2. Part 1.2 Variation in temperature over time
      3. Part 1.3 Carbon emissions and the environment
  6. 2 Collecting and analysing data from experiments
    1. Learning objectives
    2. Introduction
    3. Working in Excel
      1. Part 2.1 Collecting data by playing a public goods game
      2. Part 2.2 Describing the data
      3. Part 2.3 How did changing the rules of the game affect behaviour?
    4. Working in R
      1. Getting started in R
      2. Part 2.1 Collecting data by playing a public goods game
      3. Part 2.2 Describing the data
      4. Part 2.3 How did changing the rules of the game affect behaviour?
    5. Working in Google Sheets
      1. Part 2.1 Collecting data by playing a public goods game
      2. Part 2.2 Describing the data
      3. Part 2.3 How did changing the rules of the game affect behaviour?
    6. Working in Python
      1. Getting started in Python
      2. Part 2.1 Collecting data by playing a public goods game
      3. Part 2.2 Describing the data
      4. Part 2.3 How did changing the rules of the game affect behaviour?
    7. Solutions
      1. Part 2.1 Collecting data by playing a public goods game
      2. Part 2.2 Describing the data
      3. Part 2.3 How did changing the rules of the game affect behaviour?
  7. 3 Measuring the effect of a sugar tax
    1. Learning objectives
    2. Introduction
    3. Working in Excel
      1. Excel-specific learning objectives
      2. Part 3.1 Before-and-after comparisons of retail prices
      3. Part 3.2 Before-and-after comparisons with prices in other areas
    4. Working in R
      1. Getting started in R
      2. Part 3.1 Before-and-after comparisons of retail prices
      3. Part 3.2 Before-and-after comparisons with prices in other areas
    5. Working in Google Sheets
      1. Google Sheets-specific learning objectives
      2. Part 3.1 Before-and-after comparisons of retail prices
      3. Part 3.2 Before-and-after comparisons with prices in other areas
    6. Working in Python
      1. Getting started in Python
      2. Part 3.1 Before-and-after comparisons of retail prices
      3. Part 3.2 Before-and-after comparisons with prices in other areas
    7. Solutions
      1. Part 3.1 Before-and-after comparisons of retail prices
      2. Part 3.2 Before-and-after comparisons with prices in other areas
  8. 4 Measuring wellbeing
    1. Learning objectives
    2. Introduction
    3. Working in Excel
      1. Excel-specific learning objectives
      2. Part 4.1 GDP and its components as a measure of material wellbeing
      3. Part 4.2 The HDI as a measure of wellbeing
    4. Working in R
      1. R-specific learning objectives
      2. Getting started in R
      3. Part 4.1 GDP and its components as a measure of material wellbeing
      4. Part 4.2 The HDI as a measure of wellbeing
    5. Working in Google Sheets
      1. Google Sheets-specific learning objectives
      2. Part 4.1 GDP and its components as a measure of material wellbeing
      3. Part 4.2 The HDI as a measure of wellbeing
    6. Working in Python
      1. Python-specific learning objectives
      2. Getting started in Python
      3. Part 4.1 GDP and its components as a measure of material wellbeing
      4. Part 4.2 The HDI as a measure of wellbeing
    7. Solutions
      1. Part 4.1 GDP and its components as a measure of material wellbeing
      2. Part 4.2 The HDI as a measure of wellbeing
  9. 5 Measuring inequality: Lorenz curves and Gini coefficients
    1. Learning objectives
    2. Introduction
    3. Working in Excel
      1. Part 5.1 Measuring income inequality
      2. Part 5.2 Measuring other kinds of inequality
    4. Working in R
      1. R-specific learning objectives
      2. Getting started in R
      3. Part 5.1 Measuring income inequality
      4. Part 5.2 Measuring other kinds of inequality
    5. Working in Google Sheets
      1. Part 5.1 Measuring income inequality
      2. Part 5.2 Measuring other kinds of inequality
    6. Working in Python
      1. Python-specific learning objectives
      2. Getting started in Python
      3. Part 5.1 Measuring income inequality
      4. Part 5.2 Measuring other kinds of inequality
    7. Solutions
      1. Part 5.1 Measuring income inequality
      2. Part 5.2 Measuring other kinds of inequality
  10. 6 Measuring management practices
    1. Learning objectives
    2. Introduction
    3. Working in Excel
      1. Part 6.1 Looking for patterns in the survey data
      2. Part 6.2 Do management practices differ between countries?
      3. Part 6.3 What factors affect the quality of management?
    4. Working in R
      1. Getting started in R
      2. Part 6.1 Looking for patterns in the survey data
      3. Part 6.2 Do management practices differ between countries?
      4. Part 6.3 What factors affect the quality of management?
    5. Working in Google Sheets
      1. Part 6.1 Looking for patterns in the survey data
      2. Part 6.2 Do management practices differ between countries?
      3. Part 6.3 What factors affect the quality of management?
    6. Working in Python
      1. Getting started in Python
      2. Part 6.1 Looking for patterns in the survey data
      3. Part 6.2 Do management practices differ between countries?
      4. Part 6.3 What factors affect the quality of management?
    7. Solutions
      1. Part 6.1 Looking for patterns in the survey data
      2. Part 6.2 Do management practices differ between countries?
      3. Part 6.3 What factors affect the quality of management?
  11. 7 Supply and demand
    1. Learning objectives
    2. Introduction
    3. Working in Excel
      1. Part 7.1 Drawing supply and demand diagrams
      2. Part 7.2 Interpreting supply and demand curves
    4. Working in R
      1. Getting started in R
      2. Part 7.1 Drawing supply and demand diagrams
      3. Part 7.2 Interpreting supply and demand curves
    5. Working in Google Sheets
      1. Part 7.1 Drawing supply and demand diagrams
      2. Part 7.2 Interpreting supply and demand curves
    6. Working in Python
      1. Getting started in Python
      2. Part 7.1 Drawing supply and demand diagrams
      3. Part 7.2 Interpreting supply and demand curves
    7. Solutions
      1. Part 7.1 Drawing supply and demand diagrams
      2. Part 7.2 Interpreting supply and demand curves
  12. 8 Measuring the non-monetary cost of unemployment
    1. Learning objectives
    2. Introduction
    3. Working in Excel
      1. Part 8.1 Cleaning and summarizing the data
      2. Part 8.2 Visualizing the data
      3. Part 8.3 Confidence intervals for difference in the mean
    4. Working in R
      1. Getting started in R
      2. Part 8.1 Cleaning and summarizing the data
      3. Part 8.2 Visualizing the data
      4. Part 8.3 Confidence intervals for difference in the mean
    5. Working in Google Sheets
      1. Part 8.1 Cleaning and summarizing the data
      2. Part 8.2 Visualizing the data
      3. Part 8.3 Confidence intervals for difference in the mean
    6. Working in Python
      1. Getting started in Python
      2. Part 8.1 Cleaning and summarizing the data
      3. Part 8.2 Visualizing the data
      4. Part 8.3 Confidence intervals for difference in the mean
    7. Solutions
      1. Part 8.1 Cleaning and summarizing the data
      2. Part 8.2 Visualizing the data
      3. Part 8.3 Confidence intervals for difference in the mean
  13. 9 Credit-excluded households in a developing country
    1. Learning objectives
    2. Introduction
    3. Working in Excel
      1. Excel-specific learning objectives
      2. Part 9.1 Households that did not get a loan
      3. Part 9.2 Households that got a loan
    4. Working in R
      1. Getting started in R
      2. Part 9.1 Households that did not get a loan
      3. Part 9.2 Households that got a loan
    5. Working in Google Sheets
      1. Google Sheets-specific learning objectives
      2. Part 9.1 Households that did not get a loan
      3. Part 9.2 Households that got a loan
    6. Working in Python
      1. Getting started in Python
      2. Part 9.1 Households that did not get a loan
      3. Part 9.2 Households that got a loan
    7. Solutions
      1. Part 9.1 Households that did not get a loan
      2. Part 9.2 Households that got a loan
  14. 10 Characteristics of banking systems around the world
    1. Learning objectives
    2. Introduction
    3. Working in Excel
      1. Part 10.1 Summarizing the data
      2. Part 10.2 Comparing financial stability before and after the 2008 global financial crisis
    4. Working in R
      1. Getting started in R
      2. Part 10.1 Summarizing the data
      3. Part 10.2 Comparing financial stability before and after the 2008 global financial crisis
    5. Working in Google Sheets
      1. Part 10.1 Summarizing the data
      2. Part 10.2 Comparing financial stability before and after the 2008 global financial crisis
    6. Working in Python
      1. Getting started in Python
      2. Part 10.1 Summarizing the data
      3. Part 10.2 Comparing financial stability before and after the 2008 global financial crisis
    7. Solutions
      1. Part 10.1 Summarizing the data
      2. Part 10.2 Comparing financial stability before and after the 2008 global financial crisis
  15. 11 Measuring willingness to pay for climate change mitigation
    1. Learning objectives
    2. Introduction
    3. Working in Excel
      1. Part 11.1 Summarizing the data
      2. Part 11.2 Comparing willingness to pay across methods and individual characteristics
    4. Working in R
      1. Getting started in R
      2. Part 11.1 Summarizing the data
      3. Part 11.2 Comparing willingness to pay across methods and individual characteristics
    5. Working in Google Sheets
      1. Part 11.1 Summarizing the data
      2. Part 11.2 Comparing willingness to pay across methods and individual characteristics
    6. Working in Python
      1. Getting started in Python
      2. Part 11.1 Summarizing the data
      3. Part 11.2 Comparing willingness to pay across methods and individual characteristics
    7. Solutions
      1. Part 11.1 Summarizing the data
      2. Part 11.2 Comparing willingness to pay across methods and individual characteristics
  16. 12 Government policies and popularity: Hong Kong cash handout
    1. Learning objectives
    2. Introduction
    3. Working in Excel
      1. Part 12.1 Inequality
      2. Part 12.2 Government popularity
    4. Working in R
      1. Getting started in R
      2. Part 12.1 Inequality
      3. Part 12.2 Government popularity
    5. Working in Google Sheets
      1. Part 12.1 Inequality
      2. Part 12.2 Government popularity
    6. Working in Python
      1. Getting started in Python
      2. Part 12.1 Inequality
      3. Part 12.2 Government popularity
    7. Solutions
      1. Part 12.1 Inequality
      2. Part 12.2 Government popularity
  17. Extra: Female labour supply and the macroeconomy
    1. Learning objectives
    2. Introduction
    3. Acknowledgements
    4. Working in Excel
      1. Part 1: Collecting and preparing the data
      2. Part 2: Links between female labour supply and the macroeconomy
    5. Working in R
      1. Getting started in R
      2. Part 1: Collecting and preparing the data
      3. Part 2: Links between female labour supply and the macroeconomy
    6. Working in Google Sheets
      1. Part 1: Collecting and preparing the data
      2. Part 2: Links between female labour supply and the macroeconomy
    7. Solutions
      1. Part 1: Collecting and preparing the data
      2. Part 2: Links between female labour supply and the macroeconomy
  18. Technical Reference
  19. Glossary
  20. Bibliography
  21. Copyright acknowledgements