Global economic growth and agricultural land conversion under uncertain productivity improvements in agriculture

Joint Program Report
Global economic growth and agricultural land conversion under uncertain productivity improvements in agriculture
Lanz, B., S. Dietz and T. Swanson (2017)
Joint Program Report Series, June, 23 p.

Report 313 [Download]

Abstract/Summary:

We study how stochasticity in the evolution of agricultural productivity interacts with economic and population growth at the global level. We use a two-sector Schumpeterian model of growth, in which a manufacturing sector produces the traditional consumption good and an agricultural sector produces food to sustain contemporaneous population. Agriculture demands land as an input, itself treated as a scarce form of capital. In our model both population and sectoral technological progress are endogenously determined, and key technological parameters of the model are structurally estimated using 1960–2010 data on world GDP, population, cropland and technological progress. Introducing random shocks to the evolution of total factor productivity in agriculture, we show that uncertainty optimally requires more land to be converted into agricultural use as a hedge against production shortages, and that it significantly affects both optimal consumption and population trajectories.

Citation:

Lanz, B., S. Dietz and T. Swanson (2017): Global economic growth and agricultural land conversion under uncertain productivity improvements in agriculture. Joint Program Report Series Report 313, June, 23 p. (http://globalchange.mit.edu/publication/16721)
  • Joint Program Report
Global economic growth and agricultural land conversion under uncertain productivity improvements in agriculture

Lanz, B., S. Dietz and T. Swanson

Report 

313
June, 23 p.
2017

Abstract/Summary: 

We study how stochasticity in the evolution of agricultural productivity interacts with economic and population growth at the global level. We use a two-sector Schumpeterian model of growth, in which a manufacturing sector produces the traditional consumption good and an agricultural sector produces food to sustain contemporaneous population. Agriculture demands land as an input, itself treated as a scarce form of capital. In our model both population and sectoral technological progress are endogenously determined, and key technological parameters of the model are structurally estimated using 1960–2010 data on world GDP, population, cropland and technological progress. Introducing random shocks to the evolution of total factor productivity in agriculture, we show that uncertainty optimally requires more land to be converted into agricultural use as a hedge against production shortages, and that it significantly affects both optimal consumption and population trajectories.

Posted to public: 

Tuesday, June 27, 2017 - 10:05