We’ve had quite a few papers on this site recently by job market candidates, so let’s up the ante with paper written by a PhD student mostly before she even started her doctoral degree yet nonetheless published in Econometrica.
Institutions and their effect on long-run growth have been one of the most productive areas of economic research in the past decade or so. There are a number of results that discuss broad trends – English legal system colonies tend to have done better than Spanish, for instance. The exact mechanisms by which an institution from 200 years previous can still affect economic outcomes is less well understood. Dell discusses Engerman and Sokoloff’s contention than high inequality in Latin America in the colonial era led to bad economic outcomes today. Rather than compare across countries, she examines a particular colonial policy, Peru’s mita system of forced labor, shows large modern differences across the mita region boundary, and traces what historical processes may have led the mita to have effects persisting hundreds of years into the future.
The mita was a colonial system, begun in the 16th century, whereby villages in some areas were required to send a fraction of their working-age men to work in the state’s silver and mercury mines (how the colonial government avoided the agency problem here and wound up with anything but the most feeble workers, I don’t know…). Regions were sometimes included in the mita for geographical regions, but often were included solely because of their proximity to a colonial-era path leading to the mines. There was (and is) no significant difference in language, percentage indigenous, etc. along the mita border. The mita boundary has had no official meaning in 200 years.
Running a regression discontinuity (in two directions, since the boundary is located in geographical space) shows that health outcomes (stunted growh) and consumption are quite a bit lower for villages within the old mita boundary even today. For instance, people are nine percentage points more likely to have stunted growth, a sign of poverty. There are a number of potential explanations, but most come down to the fact that large haciendas did not develop in the colonial period within the mita region, since the state didn’t want competition for labor. Those haciendas later used their political power to ensure road networks and other inputs to production were built in their regions. Further, when the hacienda system was dismantled in the 1960s, the hacienda land was distributed to peasants, given them properly-titled land. That is, a case can be made that, at least in Peru, the particularly unequal regions, with large-scale landowners, were in some sense good for growth; this is the opposite conclusion of Engerman and Sokoloff, and a suggestion that idiosyncratic features can overwhelm more obvious theoretical insights when we talk about processes lasting hundreds of years.
I am confused a bit here, though this may be simply because I’m a terrible econometrician. Doesn’t the use of regression discontinuity require that the effect of the treatment is discontinuous at the boundary? Consider regional roads. A village on one side of the boundary is x kilometers from the nearest road. A village right on the other side is x+1 kilometers away. How is this a discontinuity? This has implications for interpreting the results as well. When the paper says the mita lowers household consumption by 25%, RD implies that household consumption falls by 25% at the boundary of the Mita region. If roads and network infrastructure are the reason, it’s tough to see first why you would have such a large effect at the boundary, and second, why I care particularly about the effect at the boundary vis-a-vis the average effect within the mita region. Perhaps someone can explain to me why RD is appropriate here.
http://econ-www.mit.edu/files/5645 (Final WP – published in Econometrica 2010)
When estimating effect of mita on road density, her unit of observation is district as any meaningful definition of road density requires observation in form of geographical area. She notes somewhere that districts are on average 20 x 20 km. Basically she needs to put her data into reasonable sized grids first. She doesn’t show that villages 1 km apart from each other, that are on the other sides of the border are different, but that the 400 km^2 large districts on the other sides of border are. Underlying assumption is that district is to some extent autonomous regional unit. Of course spillovers across districts at their borders are possible too, but these are average out in the regressions.
The RD is a tool to achieve identification and avoid critique that mita and nonmita regions are different in many other confounding characteristics. She shows that potential candidates for these confounders, such as nature, are smooth at the boundary (which is necessary for RD to be credible). In this sense it is cleaner than comparing average outcomes in mita and non-mita regions as it controls for other factors more precisely.
I don’t know much about RD, but I thinkt that the treatment have to be discontinous, not the effect. That is, the assignment to the treatment is discontinous for reasons not related to covariates.
I am not quite sure why this would get published in Econometrica. It’s not such a new idea, and I don’t see how it throws light on the more important questions of why institutional persistence exists or what one should do about it.
which you would imagine is the sort of paper Econometrica should publish.
[…] I think it’s safe to assume she can have any job she wants, and at a salary she names. I have previously discussed another paper of hers – the Mining Mita paper – which would also have been a […]
[…] the moral or political effects remains misunderstood; Melissa Dell’s wonderful paper on the Peruvian mita is a great example of a terrible social policy which nonetheless had positive long-run economic […]