Absolutely agreed that factor 2 that I mentioned might be insubstantial, but I felt the need to mention it just in case it ended up being greater than I expected. My intuition on this issue is somewhat different than yours, and my guess is that the two largest factors (remittances and direct effects on Nigeria through less nurses) are going to roughly balance out, and that it’s going to depend on the other issues which I placed under factor 4.
You mention two of the indirect (factor 4) impacts I was thinking of, but there’s definitely a lot of that kind of impact which is difficult to measure.
On its own terms as you discuss it, I absolutely agree that the original article is flawed. It’s certainly the case that the issue nowhere near as straightforward as the paper’s authors would have you believe. However, the question of the overall cost-benefit is also an important one, and also worth examining. I’m going to start working on a basic model, and I’ll post here (and maybe in a separate post as well) once I’ve completed it to a level I’m content with. The overall issue at work here, of brain drain vs. remittances appears to me to be a very important issue in global development, with this being an example where the costs of brain drain appears higher than usual. If the effect of remittances is powerful enough to outweigh brain drain even in this case, it could have broader impacts in terms of immigration as a net QALY increase.
There already does appear to be some evidence towards an effect of “brain gain” where even medical immigration appears to improve net wellbeing through remittances, as seen in the example of the Philippines here, but it’s a complex issue, and the medical situation in the Philippines is different from the situation in Nigeria.
Love this, and super keen to see your model! Some of these things might be nigh on impossible to quantify, but its more than worth a go. I wonder if anyone has tried already (Openphil / CE / RP?) I think a separate post would be a great idea for that, as this is quite an important issue and if you’ve gone through the effort to make a model like that I think there’s easily enough importance/interest there for a fresh post.
Just adding that I would also be keen to see this model. At AIM, we haven’t done any detailed modeling of skilled migration, but if/when we do look into it, quantifying these sorts of tradeoffs will be one of our key considerations.
Absolutely agreed that factor 2 that I mentioned might be insubstantial, but I felt the need to mention it just in case it ended up being greater than I expected. My intuition on this issue is somewhat different than yours, and my guess is that the two largest factors (remittances and direct effects on Nigeria through less nurses) are going to roughly balance out, and that it’s going to depend on the other issues which I placed under factor 4.
You mention two of the indirect (factor 4) impacts I was thinking of, but there’s definitely a lot of that kind of impact which is difficult to measure.
On its own terms as you discuss it, I absolutely agree that the original article is flawed. It’s certainly the case that the issue nowhere near as straightforward as the paper’s authors would have you believe. However, the question of the overall cost-benefit is also an important one, and also worth examining. I’m going to start working on a basic model, and I’ll post here (and maybe in a separate post as well) once I’ve completed it to a level I’m content with. The overall issue at work here, of brain drain vs. remittances appears to me to be a very important issue in global development, with this being an example where the costs of brain drain appears higher than usual. If the effect of remittances is powerful enough to outweigh brain drain even in this case, it could have broader impacts in terms of immigration as a net QALY increase.
There already does appear to be some evidence towards an effect of “brain gain” where even medical immigration appears to improve net wellbeing through remittances, as seen in the example of the Philippines here, but it’s a complex issue, and the medical situation in the Philippines is different from the situation in Nigeria.
Love this, and super keen to see your model! Some of these things might be nigh on impossible to quantify, but its more than worth a go. I wonder if anyone has tried already (Openphil / CE / RP?) I think a separate post would be a great idea for that, as this is quite an important issue and if you’ve gone through the effort to make a model like that I think there’s easily enough importance/interest there for a fresh post.
Just adding that I would also be keen to see this model. At AIM, we haven’t done any detailed modeling of skilled migration, but if/when we do look into it, quantifying these sorts of tradeoffs will be one of our key considerations.