International migration is the most effective action that people in developing countries can take to increase their incomes and well-being. Yet our ability to learn about the policies that enhance or inhibit the gains to migration is severely restricted due to the poor state of migration data. One element of this is the lack of representative surveys of immigrants.
Women are less likely to occupy the top paying jobs in developed economies, in part because they are less competitive than men. A whole series of laboratory experiments has detailed the gap in competitiveness between the average woman and the average man, even when women are just as good, if not better than men. Is this result due to the fact that women are biologically female, or the fact that they are socialized as female? Although we often alternate between gender and sex in describing males and females, they are not strictly the same.
Last week I posted about a nice experiment that Lori Beaman and Jeremy Magruder had done to understand the role networks play in job-referrals.
I was recently talking with one of my younger colleagues and she was lamenting something that was going wrong in an impact evaluation she was working on. She was thinking of throwing in the towel and shutting down the work. This reminded me of the horrible feeling in the pit of my stomach when I started doing impact evaluation (as well as research more generally) when something went wrong. Now, of course, I am bald…
When done well, randomized experiments at least provide internal validity – they tell us the average impact of a particular intervention in a particular location with a particular sample at a particular point in time. Of course we would then like to use these results to predict how the same intervention would work in other locations or with other groups or in other time periods.
- external validity
To deceive or not to deceive? David’s last post about Beaman and Magruder’s experiment, in which there is a small, and seemingly harmless deception, got me thinking about this continually uncomfortable issue. David claims that this is now an increasingly popular strategy, which gives me some worry about the future of experiments in economics.
One of the frustrations facing job seekers worldwide, but especially in many developing countries, is how much finding a job depends on who you know rather than what you know. For example, in work I’ve done with small enterprises in Sri Lanka, less than 2 percent of employers openly advertised the position they last hired – with the most common ways of finding a worker being to ask friends, neighbors or family members for suggestions. Clearly networks matter for finding jobs.
An interesting, recently revised working paper by Duflo, Dupas and Kremer looks at the effects of providing school uniforms, teacher training on HIV education, and the two combined. This paper is useful in a number of dimensions – it gives us some sense of the longer term effects of these programs, the methodology is interesting (and informative), and finally, of course, the results are pretty intriguing and definitely food for thought.