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In what looks to be its inaugural issue, Nature Human Behaviour–a new social science journal published by the Nature group–discusses some of the research I and other economists have done on the topic of female genital cutting (FGC).

In short, the article’s angle is that, contra a popular theory that holds that FGC persistence is due to community-level factors, the persistence of FGC seems to come from individual and household-level factors:

Some economists say it’s time for a new approach. Their work, itself controversial, questions long-held views on FGC — that communities either all follow the practice, or all give it up – and thereby challenges the very underpinnings of many interventions.

Interventions should stop trying, as most do, to sway entire villages, these scientists say. They should instead target cracks in support for the practice: the influential community leader who has decided his daughters will not be cut, or the husband and wife who are divided on the fate of their daughters.

The article also talks about some of the research that my PhD student Lindsey Novak* has done on FGC in her job-marker paper:

A few weeks ago, one of my doctoral advisees wrote to me asking me how she could test for a specific mechanism behind the causal effect she is trying to estimate in her job-market paper.

Letting [math]y[/math] be her outcome of interest, [math]D[/math] her treatment of interest, [math]x[/math] be a vector of control variables, and [math]\epsilon[/math] be an error term with mean zero, my student was estimating

(1) [math]y = \alpha_{0} + \beta_{0}{x} + \gamma_{0}{D}+\epsilon[/math],

in which she was interested in [math]\gamma[/math], or the causal impact of [math]D[/math] on [math]y[/math].

But more importantly for the purposes of this post, she was also interested in whether [math]M[/math] is a mechanism through which [math]D[/math] causes [math]y[/math]. I suggested the usual thing I often see done, which is to estimate

(1′) [math]y = \alpha_{1} + \beta_{1}{x} + \phi_{1}{M} + \gamma_{1}{D}+\nu[/math],

in which case if [math]\gamma[/math] dropped out of significance and [math]\phi[/math] was significant (and had the “right”) sign, then she could say that [math]M[/math] was a mechanism through which [math]D[/math] cause [math]y[/math]. I also suggested maybe conducting a Davidson-MacKinnon J-test for non-nested hypotheses to assess the robustness of her mechanism finding.

Come gather ’round people
Wherever you roam
And admit that the waters
Around you have grown
And accept it that soon
You’ll be drenched to the bone
If your time to you is worth savin’
Then you better start swimmin’ or you’ll sink like a stone
For the times they are a-changin’

— Bob Dylan, “The Times They Are A-Changin’.”

On November 8, bucking the vast majority of polls, pundits, and prediction markets, Americans have elected Donald Trump as their president and have given him a majority of seats in both the Senate and the House of Representatives.

Whatever opinion I might have of the result of the election is immaterial, first because I am not a US citizen, and so I cannot vote in this country; and second, because I am not sure what the world needs at this point is more opinion.*

One thing I do have a cogent opinion on, however, is about the serious examination of conscience agricultural and applied economists need to do–especially left-leaning agricultural and applied economists.

First off, by “agricultural and applied economists,” I mean those of us who have any mix of research, teaching, and extension appointments in (what used to be known as) agricultural economics departments at land-grant universities. I know “applied economics” encompasses more than the category just delineated, but for the purposes of this discussion, I am choosing to go with the label the Agricultural and Applied Economics Association–my professional association–uses to designate people like my colleagues and me.