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Forecasting technological change in agriculture - An endogenous implementation in a global land use model

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/persons/resource/Jan.Dietrich

Dietrich,  Jan Philipp
Potsdam Institute for Climate Impact Research;

/persons/resource/christoph.schmitz

Schmitz,  Christoph
Potsdam Institute for Climate Impact Research;

/persons/resource/Lotze-Campen

Lotze-Campen,  Hermann
Potsdam Institute for Climate Impact Research;

/persons/resource/Alexander.Popp

Popp,  Alexander
Potsdam Institute for Climate Impact Research;

/persons/resource/Christoph.Mueller

Müller,  Christoph
Potsdam Institute for Climate Impact Research;

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Zitation

Dietrich, J. P., Schmitz, C., Lotze-Campen, H., Popp, A., Müller, C. (2014): Forecasting technological change in agriculture - An endogenous implementation in a global land use model. - Technological Forecasting and Social Change, 81, 236-249.
https://doi.org/10.1016/j.techfore.2013.02.003


Zitierlink: https://publications.pik-potsdam.de/pubman/item/item_18423
Zusammenfassung
Technological change in agriculture plays a decisive role for meeting future demands for agricultural goods. However, up to now, agricultural sector models and models on land use change have used technological change as an exogenous input due to various information and data deficiencies. This paper provides a first attempt towards an endogenous implementation based on a measure of agricultural land use intensity. We relate this measure to empirical data on investments in technological change. Our estimated yield elasticity with respect to research investments is 0.29 and production costs per area increase linearly with an increasing yield level. Implemented in the global land use model MAgPIE (“Model of Agricultural Production and its Impact on the Environment”) this approach provides estimates of future yield growth. Highest future yield increases are required in Sub-Saharan Africa, the Middle East and South Asia. Our validation with FAO data for the period 1995–2005 indicates that the model behavior is in line with observations. By comparing two scenarios on forest conservation we show that protecting sensitive forest areas in the future is possible but requires substantial investments into technological change.