Francisco Gallego a obtenu un doctorat en économie au MIT. Il est professeur associé à l’Institut d’économie de la Pontificia Universidad Católica du Chili (PUC). Ses domaines d’intérêt sont le développement économique, l’économie politique et l’économie de l’éducation. Il a travaillé sur des évaluations dans l’éducation axées sur l’impact de l’information sur les décisions des parents. Il est directeur scientifique de J-PAL Amérique latine et Caraïbe.
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In a sense, doing development is analogous to an MD working in an ER or in an ICU: you need to master a set of different types of tools in order to “treat” your patients that come with urgent needs.
What got you interested in development economics?
I think two different things. First, I come from Chile, a country with many contrasts. For instance, we have relatively high growth rates but a lot of poverty and inequality, so the typical questions of development economics were in my mind since I started studying economics as an undergrad. Next, when I got to do grad studies what I think really got me interested in development is the challenges you faces in order to answer the relevant questions of the field. In a sense, doing development is analogous to an MD working in an ER or in an ICU: you need to master a set of different types of tools in order to “treat” your patients that come with urgent needs. In a sense, in development economics you need to understand several groups of theories and also do empirics at a highly sophisticated level if you really want to make a contribution to the field. You need to master theory and empirics, macro and micro models, neo-classical and behavioral economics models, just to mention a few “contrasts.” This is intellectually challenging and also a continuous source of fun!
What is one current research project that you're particularly excited about?
I am working in a project (jointly with Ofer Malamud and Kiki Pop-Eleches) on computer and internet use and parental involvement and monitoring in Chile. Several previous papers show that just giving out computers to kids may actually create adverse effects on their learning and other dimensions. What is interesting is that some of these papers show in non-experimental ways that the adverse effects of computers seem to go away when parents are involved and, for instance, there are rules in the families in terms of kids’ behavior. For instance, my coauthors show exactly that in a previous paper published in the Quarterly Journal of Economics.
So we set up an experimental evaluation in the context of a big government program in Chile in which we study whether informing parents on how much the kids use internet and providing monitoring tools affect internet use. This is related to asymmetric information problems between parents and children and can also help us understand also the frictions that are relevant within families. As we have a really big sample, we also tested several ways of delivering the messages to families in order to learn more about behavioral biases. We are starting to get the results and we hope to have soon a version of the paper.
What is your "dream evaluation"? (It doesn't have to be feasible!)
I am working with some colleagues (especially Juan-Pablo Montero from PUC-Chile) on trying to understand the effects of several public policies on car and public transportation use—for instance, the effects of driving restrictions and public transportation policies on car use in several Latin American countries. This is a really relevant issue in many emerging countries: as income increases people want to get a car and most countries/cities do not have policies to make the people internalize the negative externalities associated with using a car (especially during peak hours in congested areas of the cities).
The thing is that we need to understand several mechanisms through which the policies affect several margins both in the short and the medium-run. Also, theoretically, you may get interactions between several policies—say, between driving restrictions and increases in the supply and quality of public transportation. There are partial and general equilibrium effects too. Because of obvious reasons one cannot randomize these things and just try to rely on quasi-experimental estimates in some places and also to get estimates that are really combinations of effects on several margins. Thus, my dream evaluation is to evaluate some set of policies in different cities –which would probably imply several countries actually…--including interactions among them and to follow the cohorts several years after the treatments were implemented.
What is your craziest story from the field?
Well, it is really a sad story. In one of the first RCTs we were implementing in Chile we were using an over-subscription method to allocate scholarships for preparation for the Chilean version of the SAT among poor kids in Chile. Access to higher education is a very relevant issue in a very unequal country and also it is worth mentioning that the value of scholarship was not trivial.
So we started with the obvious: call poor high schools to offer this scholarship, talk to the administrators and/or principals and get a really big sample (we just had 500 scholarships). Nothing happened and actually at one point we started talking to the principals and a couple of them told us that they really did not care about scholarships and things like that; they just cared about having the kids finishing secondary education as soon as possible. This was really sad (to me at least…).
So, we had to change strategy and I had to actually talk a couple of times in the media. And this is the crazy part: in one of the cases I had to go to a talk show on TV to talk about this program and invite people to apply. I did that while the previous guy talking in the program was discussing about some affair between two TV stars and the next person was teaching the audience on how to prepare some food. I felt really weird talking in that context (but I had to say that it was the day when some of my relatives finally understood what my research was about…). Well, the good thing is that in that day we got the highest number of applications from poor students in the whole experiment. It was really a practical lesson on how informational poverty traps work and on how we as researchers have to find create ways to get to the poor.