Much of my work as an economist is built upon the insight of a book written in 1826 by Johann Heinrich von Thunen, called “Der Isolierte Staat”, which is translated, “The Isolated State”. In it, he presented a model of land use that suggested where various crops would need to be produced, given the cost of transportation of the crop to market.
As I was thinking about von Thunen’s theory, it occurred to me that when used in conjunction with how the wage rate is set in a market economy — equal to the value of the marginal product of labor — it provided insight into how a deteriorating highway infrastructure — as we have in the United States — could explain in part the wage stagnation. My point in what follows is not that it explains all wage stagnation, or even a large part of wage stagnation, but only that it can be seen from a theoretical standpoint to explain some wage stagnation.
Ester Boserup is an economist who wrote two books which influenced me greatly. I read both of these books around 15 years ago while in grad school, and I can’t find my copies at home, so I can’t refer to them more precisely. I bet they are both at work. The first book, published in 1965, is “The Conditions of Agricultural Growth: The Economics of Agrarian Change under Population Pressure”, which I was delighted today to find online for free. This book describes how agricultural intensification results from increased population density. I think the underlying story is one of production technologies changing based on land abundance and scarcity. The second, published in 1981, is “Population and Technological Change: A Study of Long Term Trends”, was broader, looking at specialization throughout the economy. It is the second one that I mostly think about in this post.
What I am trying to get at is what may cause a country to get stuck in a high population, low GDP situation, and what might be done to help it get unstuck. My thoughts, based on Boserup’s books, began in regard to the issues of intensification and specialization. The first thing that came to mind was that once a country was more market-oriented or integrated into the global system, what drives development is investments in improving the productivity of labor and capital, since returns to land (owned by someone) and returns to labor are paid at the rate of the value of the marginal product of labor.
In Doha in December 2012, we presented our findings about the impact of climate change on agriculture in Africa. As part of our presentation, we prepared 2-page summaries for each of the 29 countries that were in our study and would be published in forthcoming monographs. For those interested in reading any of those summaries, you can find them at http://www.ifpri.org/publications/results/taxonomy%3A933.7013
We have been using nested logits and multinomial logits (MNL) to model land use and land use change for modeling greenhouse gas (GHG) emissions from the agriculture, forestry, and land use (AFOLU) sector. The Vietnamese government makes 10-year plans for agriculture, making targets for land dedicated to various crops and other uses. While the targets are included in the plan, the policy instruments used to meet those targets are less clear. Farmers may be pressured to change their own plans to achieve those goals, but the methods used are not very certain.
The underlying household model on which the MNL land use models are based is a random utility model (RUM). A RUM computes utility for various land uses or crop choices. Because these utilities are known with uncertainty (stochastically), the probability of a given piece of land to be put to a given use is computed by comparing the utility of that use to the utility of each of the other choices.
The easiest utility to think about is profit per hectare from cultivating different crops. To effect a reduction in area devoted to one crop, a market-solution would be to raise the cost of cultivating that crop (or equivalently, reduce the profitability of the crop, perhaps by reducing the price). Non-market methods of influencing that decision are difficult or impossible to model directly, but within a model, they might be thought of as a shadow price that could be estimated. If the shadow price is a per unit cost, it can be modeled as a constant. If the shadow price is a per unit of output cost, we can model it as a multiplier on output price.
This is a new blog that I hope to post to at least once per day. I want this to be an outlet for sharing ideas related to my work on climate change and agriculture, GIS, remote sensing, econometrics, and programming. I will try to use categories to help the reader rapidly find the content closest to their interests. Happy reading!