Ten Things for Applied Econometricians to Keep in Mind, by Dave Giles: No "must do" list is ever going to be complete, let alone perfect. This is certainly true when it comes to itemizing essential ground-rules for all of us when we embark on applying our knowledge of econometrics.
That said, here's a list of ten things that I like my students to keep in mind:
- Always, but always, plot your data.
- Remember that data quality is at least as important as data quantity.
- Always ask yourself, "Do these results make economic/common sense"?
- Check whether your "statistically significant" results are also "numerically/economically significant".
- Be sure that you know exactly what assumptions are used/needed to obtain the results relating to the properties of any estimator or test that you use.
- Just because someone else has used a particular approach to analyse a problem that looks like, that doesn't mean they were right!
- "Test, test, test"! (David Hendry). But don't forget that "pre-testing" raises some important issues of its own.
- Don't assume that the computer code that someone gives to you is relevant for your application, or that it even produces correct results.
- Keep in mind that published results will represent only a fraction of the results that the author obtained, but is not publishing.
- Don't forget that "peer-reviewed" does NOT mean "correct results", or even "best practices were followed".
I'm sure you can suggest how this list can be extended!
I'll add two that I heard often in grad school:
Don't take econometric techniques in search of questions. Instead, start with the important questions and then develop the econometrics needed to answer them.
Model the process that generates the data.
Any further suggestions?