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Next entry in the NBER growth session recap. Diego Restuccia (Toronto) and Raul Santaeulalia-Llopis (Wash. U.) presented their paper on land misallocation and productivity. Essentially, what Diego and Raul are trying to do is apply the firm-level study of Hsieh and Klenow (2009) methodology to farms (you might be starting to sense a theme to the day by now). Specifically, they have detailed data on farm plots from Malawi, and use this to see how much the marginal product of land varies across farming households.
They then ask the counter-factual question of: how much would agricultural output rise if we re-allocated land across farmers to equalize the marginal product of land? Essentially, if I could make sure that high-productivity farmers were able to receive more land, and low-productivity farmers less, how much could we raise aggregate output? Their finding is that output would go up by a factor of 3! This is way off the charts compared to anything that people have done with firms (where output might rise by a factor 1.5).
Big numbers like that lead to questions. The obvious concern is that they are incorrectly measuring the marginal product of land. Working in their favor is that they have clear measures of actual real output (bushels of maize). This means they do not have to make any assumptions about prices to try and deflate revenues, as we often need to do with firms.
You might also be worried that they are attributing land-quality differnces to households. That is, household A looks really productivity in the data because they have good land, not because they are really good at farming. Diego and Raul have really fine-grained measures of land characteristics. Conceptually they can control for land quality. But how do you construct a single-valued index of land quality from 11 different characteristics (slope, elevation, acidity, etc…). There is conceivably some kind of “true” agronomic function that transforms these into a single measure of quality, but it is almost certainly highly non-linear and involves all sorts of weird covariances between the measures. So if you want to be skeptical about their results, I think this is the primary worry.
Let’s take their results as true for the moment, though. One explanation for the vast degree of misallocation goes back to subsistence constraints, as I discussed in a different context before. If I need to ensure that all farming households can achieve a minimum output (and markets are not developed enough for people to borrow/lend over time if they can’t), then you’re bound to have big misallocations. You’d in fact have to give bad farmers even more land than good farmers. A very low absolute level of productivity is thus a determinant of misallocation.
On the other hand, if all the land is really highly productive, then small plots are sufficient to ensure subsistence. This means that we can give all the bad farmers small plots, and let the good farmers operate the surplus land. So a high level of absolute productivity will ensure a better allocation. Inherent land productivity thus has two separate influences on outcomes: a direct one through increasing output, and an indirect one in ensuring better allocations of land.