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!

Clustering When Few Clusters

Clustering in STATA when you have many clusters is super easy. Sometimes depressing, but super easy. But what if you have few clusters? Then what? Good news: There's a STATA package for that! Woo hooo!!! Click here.

In other clustering news, it is true that you don't have to cluster when you have a true randomized experiment. Read this lament of clusterjerks and this response to it. Even for those of us not running RCTs, I think reading about this issue helps us understand the importance of clustering.

People Will Forget Your Regression Tables But They'll Remember Your Pictures

Take time to think about how to present your results graphically in a way that best tells your story. Context is important. Whether the y-axis includes zero? Maybe not so much. See this video.

For My Graduate Students...

Commuting Zones, Occupation Codes, Occupational Tasks, and More...Thank You, David Dorn!

MSAs have gone out of fashion. Commuting Zones are all the rage these days! 


David Dorn has graciously provided cross-walks for PUMAs and counties to commuting zones on his webpage. Super useful! On behalf of labor economists everywhere, I thank you! 

Here is a short abstract:Commuting Zones (CZs) provide a local labor market geography that covers the entire land area of the United States. CZs are clusters of U.S. counties that are characterized by strong within-cluster and weak between-cluster commuting ties. The crosswalk files below provide a probabilistic matching of sub-state geographic units in U.S. Census Public Use Files to CZs.

And the webpage is linked here. 

PS

Use this code with the IPUMS data so that you can use the crosswalk: 
g puma2000=real(string(statefip)+string(puma, "%04.0f"))