Lanz, Bruno

2018-2, Lanz, Bruno, Dietz, Simon, Swanson, Tim

2017-8-25, Lanz, Bruno, Dietz, Simon, Swanson, Tim

We structurally estimate a two-sector Schumpeterian growth model with endogenous population and finite land reserves to study the long-run evolution of global population, technological progress, and the demand for food. The estimated model closely replicates trajectories for world population, GDP, sectoral productivity growth, and crop land area from 1960 to 2010. Projections from 2010 onward show a slowdown of technological progress, and, because it is a key determinant of fertility costs, significant population growth. By 2100, global population reaches 12.4 billion and agricultural production doubles, but the land constraint does not bind because of capital investment and technological progress.

2017, Lanz, Bruno, Dietz, Simon, Swanson, Tim

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.