I teach a number of courses in the (rather non-specific area) of applied economics, which basically consists of applying economic models and theories to real-world data, using the tools and techniques learned in econometrics. This is a particularly challenging area for students (and instructors, to be honest) because it is interdisciplinary – combining ideas, methods, and skills from several different fields. In particular, while students often have strong theoretical skills in both micro/macoreconomics and econometrics, they often have problems applying those skills to the real world.
This page collects a number of different resources I’ve developed over the years for teaching and learning in this area. These include guides and notes for specific technical subjects which I think are valuable, as well as learning modules and interactives that instructors may find interesting.
Guide to Variables and Marginal Effects in STATA
This resource (which you can find at this link) provide a very hands-on and practical guide to using both marginal effects and factor variables in STATA. These are technical skills which are usually taught, but prove invaluable (and very convenient!) when carrying out applied research projects. Topics covered include:
- A review of qualitative and dummy variables
- STATA’s factor variable notation and options
- Marginal effects, including predictive margins and their implementation in STATA
- Over 15 worked examples, which can be carried out using a supplied dataset in STATA
Canvas Learning Modules for Applied Economics
This resource, which is accessible via Canvas Commons (at this link) contains five learning modules which walk students through a simple applied economic research project from start to finish using STATA and Statistics Canada microdata. Each module includes:
- A set of pre-readings or videos to cover necessary background or introduce concepts
- A detailed, step-by-step walkthrough and discussion of the research task and its implementation in STATA
- A quiz to test student understanding of the material covered
- Topics include: importing and managing data, descriptive statistics and hypothesis testing, factor variables, variable creation and adjustment, missing data, regression analysis, outputting and formatting data
I am actively working on an R version of this project; if you’re interested, let me know. I also welcome suggestion for other modules (yes, graphing is on the list!) to include.
Cool Data Resources for Applied Economics Projects
One of the biggest challenges students often face is finding data for their project. My students and I have been slowly collecting and curating an ever expanding list of the best resources online for different kinds of data.
You can find the most recent publication of this list (and associated links) on Canvas Commons (located here) and online here on my Github
Let me know if you have any suggestions or additions!
(Last updated: 11-05-2020)