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Economic growth and agricultural land conversion under uncertain productivity improvements in agriculture

Bruno Lanz, Simon Dietz and Timothy Swanson

No 240, GRI Working Papers from Grantham Research Institute on Climate Change and the Environment

Abstract: We study how stochasticity in the evolution of agricultural productivity interacts with economic and population growth, and the associated demand for food. 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 contemporary population. In addition, sectors differ in that agriculture also 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 consumption and population trajectories.

Date: 2016-06
New Economics Papers: this item is included in nep-dev
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Related works:
Working Paper: Global economic growth and agricultural land conversion under uncertain productivity improvements in agriculture (2017) Downloads
Working Paper: Economic growth and agricultural land conversion under uncertain productivity improvements in agriculture (2016) Downloads
Working Paper: Economic growth and agricultural land conversion under uncertain productivity improvements in agriculture (2016) Downloads
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