When You Have Multiple Measures of the Same Thing...

The usual problem when doing empirical work is that you don't have an important variable in your data. Very, very occasionally, you have the opposite problem: Lots of different highly correlated variables measuring pretty much the same thing. What to do? How to choose?

I would say that if the variable is typically measured in a specific way in the (economics) literature, maybe go with that one for your main specification unless you have reason to believe you have a better one. Either way, include a table in the appendix showing that your results are robust across measures. Don't freak out if you fail to see a star for one or two of them. This will happen if you have enough different measures and not a large enough sample size.

Another good option to choosing just one for your main specification is to include a summary measure of all of the different measures. Of course, many ways to create summary measures. Have a look here for a nice discussion of this.

And Now For Cool Migration Data

Here you go! Enjoy! Policy data for 45 countries, wow!

Gender Related Data

To come up with good implementable ideas, it's useful to know what data exist and how to get them, especially data in easy to use format.  If you're interested in gender issues, have a look here. Really interesting variables by country and year!!! Browse through the data---you just may come up with a brilliant new paper topic.

Some Teaching Advice

I know, I know. This blog is about doing research. But teaching is also a big (and important) part of our jobs. I especially like to hear about tips for improving teaching that do not involve too much time investment. Here are some examples.  Any other ideas and suggestions?

How To Talk About IVs with Non-Economists

Some good points about instrumental variables in the article but what I really appreciated is the talk of IVs in a magazine everyone reads.

Enjoy!