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Markus Goldstein's blog

Measuring work

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I was in a meeting the other week where we were wrestling with the issue of how to capture better labor supply in agricultural surveys.   This is tough – the farms are often far from the house, tasks are often dispersed across time, with some of them being a small amount of hours – either in total or on a given day.   Families can have more than one farm, weakening what household members know about how the others spend their time.   One of the interesting papers that came up was a study by Elena Bardasi, Kathleen Beegle, Andrew Dllon and Pieter Serneels.  Before turning to their results its worth spending a bit more time discussing what could be going on. 

Two things would seem to matter (among others).  First, who you ask could shape the information you get.    We’ve had multiple posts in the past about imperfections in within household information.   These posts have talked about income and consumption and while labor would arguably be easier to observe, it may suffer from the same strategic motives for concealment and thus be underreported when the enumerator asks someone other than the actual worker to respond on this.   

Further thoughts on sharing results

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I wanted to follow up on David’s post of yesterday on the issue of sharing results with respondents.   My initial reaction was that we kind of owe this to the respondents not least because they spent a lot of time answering our tedious questionnaires. But as David points out, it’s not quite that simple in cases where we expect to have ongoing work.  

The perfectionists versus the reductionists

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coauthored with Jishnu Das

Women perform 66 percent of the world’s work, and produce 50 percent of the food, yet earn only 10 percent of the income…. 

--Former President Bill Clinton addressing the annual meeting of the Clinton Global Initiative (September 2009)

Impressive, heart-wrenching, charity-inducing, get off your sofa and go do something heartbreaking.

But Wrong.

The impact evaluation roller coaster

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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…

Education, fertility and HIV: It’s complicated

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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. 

The effects of land tenure regularization in Rwanda

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So I come back from vacation to find out that I was part of a randomized experiment in my absence.   No, this had nothing to do with the wonders of airline travel in Europe (which don’t add that frisson of excitement through random cancellations like their American brethren), but rather two of our co-bloggers trying to figure out if the blog actually makes people recognize me and Jed more (here are links to parts

Getting serious about learning how to overcome women’s economic barriers

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coauthored with Alaka Holla

 So two weeks ago we talked about how we don’t know enough about economically empowering women and last week we talked about power issues when measuring this in “gender-blind” interventions.   This week we’d like to make some suggestions about how, with small effort, we could make serious progress in learning meaningful things about how to increase the earning capacity of women.   

gender power doesn't come cheap

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coauthored with Alaka Holla

As we argued last week, we need more results that tell us what works and what does not for economically empowering women. And a first step would be for people who are running evaluations out there to run a regression that interacts gender with treatment.   Now some of these will show no significant differences by sex.   Does that mean that the program did not affect men and women differently? No. Alas, all zeroes are not created equal.  

We need to know more about how to economically empower women

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co-authored with Alaka Holla

Everyone always says that great things happen when you give money to women. Children start going to school, everyone gets better health care, and husbands stop drinking as much. And we know from impact evaluations of conditional cash transfers programs that a lot of these things are true (see for example this review of the evidence by colleagues at the World Bank). But, aside from just giving them cash with conditions, how do we get money in the hands of women? Do the programs we use to increase earnings work the same for men and women? And do the same dimensions of well-being respond to these programs for men and women?

The answer is we don’t know much. And we really should know more. If we don’t know what works to address gender inequalities in the economic realm, we can’t do the right intervention (at least on purpose). This makes it impossible to economically empower women in a sustainable, meaningful way. We also don’t know what this earned income means for household welfare. While the evidence from CCTs for example might suggest that women might spend transfers differently, we don’t know whether more farm or firm profits for a woman versus a man means more clothes for the kids and regular doctor visits. We also don’t know much about the spillover effects in non-economic realms generated by interventions in the productive sectors and whether these also differ across men and women. Quasi-experimental evidence from the US for example suggests that decreases in the gender wage-gap reduce violence against women (see this paper by Anna Aizer), but some experimental evidence by Fernald and coauthors  from South Africa suggests that extending credit to poor borrowers decreases depressive symptoms for men but not for women.