Hit and Run Econometrics

Here’s a set of twenty videos I did for my econometrics students. I hope you’ll find them useful or even enjoy them.

Confession: I am an econometric impostor. I have published papers with econometric findings for more than 40 years now. Some of them have attracted tens, if not dozens, of readers. But I never have been an econometrics hawk. All along, I just kept trying things and looking up references until I figured things out. As a result, about a fourth of what I’m about to show you is wrong — I just don’t know which fourth.

And yet, it’s useful, because as an econometric impostor I developed a lot of intuition.

This is “hit and run” by analogy to baseball — on that play, the batter swings at everything and the runner gets a fast start. (Ask a baseball fan if you’re interested.) I modestly think you can get a lot of econometric intuition by watching these videos. Email me when you find mistakes and I’ll start a list.

I especially recommend these if your significant other is an economist and you just don’t understand that person! Watch these and you’ll have everything you need to keep the conversation going.

If you find these unhelpful, you get all of your money back!

1. Excel regression and a trap. Yes, you can do regression analysis in lowly Excel! . . . but here’s a trap that one beginning student fell into.

2. Deviation notation is not a big deal, but the Fisher Equation is a great thing to know about and it provides a nice illustration.

3. What’s more accurate, a watch that’s always a minute off or a watch that’s stopped? Here’s a new take on that old folk riddle.

4. There are many choices out there for statistical packages, but here are a few that stand out. Find out why there’s a big buzz about R.

5. If you drive a new car off the lot, you lose a lot of value — you’ve heard that, right? See what the t-test can tell us about new and used cars.

6. The Gauss-Markov Theorem is important in econometrics. See why in this video.

7. Where does R-squared come from? Here’s an answer that helps point out why this statistic is so often consulted.

8. Why did the invention of cable TV and the videocassette recorder come to be known as “the video revolution”? These inventions foreshadowed our media landscape today, and media historians can learn from the econometrics of the revolution.

9. Can you interpret β in a regression equation? Can you paint by numbers? What do these questions have to do with each other?

10. Multicollinearity can mess up your estimates; it can be cured; but sometimes the cure is worse than the illness.

11. How could nonlinearity be “cheap”? The Phillips Curve from macroeconomics provides an example. Hint: This is a trick that’s way easier than true nonlinearity.

12. An interaction term can help you sort out the sources of discrimination in the labor market. Find out how.

13. Testing for structural change can be done a lot of different ways. Find out how, and also find out why “This Time It’s Different” may be the most dangerous words ever for individual investors.

14. The Koyck Lag is a nifty piece of math that, in this video, helps illuminate the effects of threatened price controls on research and development in the pharmaceutical industry.

15. Specification error is a serious problem in econometrics and this is a really compact treatment.

16. Generalized Least Squares can fix the problem of autocorrelated errors, but there’s a big “if.” Find out why fixing it might be worse than leaving it alone.

17. And Generalized Least Squares can also fix problems with heteroskedastic errors but — you guessed it! — it might be better to leave it alone.

18. Did class and gender influence who survived the sinking of the Titanic? A logit model helps us get answers.

19. Simultaneity bias is bad and it’s everywhere! Here are some of the reasons why.

20. OK, time for blind spots — what are the biggest blind spots in the sort of econometrics taught at the undergraduate level? Here are my candidates: the McCloskey reservation and the Taleb reservation. (Hint: Are there any swans that are black?)