Note to instructors
Our target audience includes:
- students at undergraduate and postgraduate level who are not taking economics as a major subject
- anyone who wants to learn how to use economics to understand and articulate reasoned views on some of the most pressing policy problems facing our societies: inequality, financial instability, the future of work, environmental degradation, wealth creation, and innovation
- anyone who wants practical training in understanding and using data to measure the economy and policy effectiveness
- anyone interested in social and economic policy, who is taking a degree related to policy, or is hoping to have a policy-related job in the future.
- no prior courses in economics or statistics are required
- no knowledge of statistical programs (such as R or Excel) required, except a familiarity with the interface and how to enter and clear data
- familiarity with basic mathematical operations, percentages, decimals, bar charts, 2-D graphs
The purpose of the empirical projects
- Provide hands-on experience, using real-world data, to investigate important policy problems.
- Strengthen the link between real-world phenomena and economic concepts and models.
- Help students to develop skills that are transferable to other courses and to the workplace.
The structure of the empirical projects
Empirical projects are designed to be completed in Excel. We are developing step-by-step instructions for the projects using R for the full beta release, later in 2018.
Each project contains:
- Clearly defined learning objectives related to statistical/economic concepts and data presentation.
- An introduction to the project and the economic topics it addresses.
- Two to three parts, each containing multiple questions on a specific subtopic. Unless indicated otherwise, these can be done independently, or at the same time.
- Step-by-step walkthroughs for conceptually difficult or challenging tasks in Excel and R. These are annotated screenshots (Excel) and code with explanations (R). The walk-throughs are designed so that beginners in Excel or R will be able to learn the skills required to complete the project.
Solutions for all empirical projects will be made available, and the walk-throughs will also help students confirm that they have got the correct output.
How to use the empirical projects
- Each empirical project in Doing Economics is divided into two or three parts. Each part can be completed independently, or together (unless specified otherwise). The time needed to complete one part will depend on the structure and pace of the course, though as a rough guide, one project can be a term-long assignment. In each part, students will be guided through the steps to produce the charts or tables that can form the basis of a report.
- The projects can be done independently, since the same key concepts are repeated in a number of projects. Each project has an introduction with information about the concepts that are prerequisites, for that project, as well as those that will be introduced in the project.
- The empirical projects can be used to supplement units in Economy, Society, and Public Policy and The Economy, although this is not essential. Each project contains information about the unit to which the material is related, and has links to sections in the ebooks that may help students to understand the project.
ESPP and Doing Economics as part of a connected curriculum
If you are teaching a social science, engineering, business studies, or public policy program in which students have to take an economics course and a quantitative methods course, you can use ESPP and Doing Economics empirical projects to connect these parts of the curriculum.
|ESPP Unit||Title||Doing Economics|
|1||Capitalism: Affluence, inequality, and the environment.||Empirical Project 1: Measuring climate change (datasets: Goddard Institute for Space Studies temperature data; US National Oceanic and Atmospheric Administration CO2 data)|
|2||Social interactions and economic outcomes||Empirical Project 2: Collecting and analysing data from experiments (datasets: student-generated experimental data; Hermann et al 2008)|
|3||Public policy for fairness and efficiency.||Empirical Project 3: Assessing the effect of a sugar tax (datasets: Global Food Research Program’s Berkeley Store Price Survey; Silver et al 2017)|
|4||Work, wellbeing, and scarcity.||Empirical Project 4: Measuring wellbeing (datasets: UN GDP data; Human Development Index)|
|5||Institutions, power, and inequality||Empirical Project 5: Measuring economic inequality: Lorenz curves and Gini Ratios (dataset: Our world in data)|
|6||The firm: Employees, managers, and owners||Empirical Project 6: Measuring management practices (dataset: World Management Survey)|
|7||Firms and markets for goods and services||Empirical Project 7: Supply and demand (dataset: US market for watermelons (1930–1951); taken from Stewart (2018))|
|8||The labour market: Wages, profits, and unemployment||Empirical Project 8: Measuring the non-monetary cost of unemployment (dataset: European Values Study)|
|9||The credit market: Borrowers, lenders, and the rate of interest||Empirical Project 9: Credit-excluded households in a developing country (dataset: Ethiopian Socioeconomic Survey)|
|10||Banks, money, housing, and financial assets||Empirical Project 10: Characteristics of banking systems around the world (dataset: World Bank Global Financial Development Database)|
|11||Market failures and government policy||Empirical Project 11: Measuring the willingness to pay for climate change abatement (dataset: German survey data, taken from Uehleke (2016))|
|12||Governments and Markets in a democratic society||Empirical Project 12: Government policies and popularity: Hong Kong cash handout (dataset: data from Hong Kong)|