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Biewald, A.; Rolinski, S.; Lotze-Campen, H.; Schmitz, C. |
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Global valuation of agricultural, virtual blue water trade measured on a local scale |
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2012 |
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Conference paper presented at the 10th Annual meeting of the International Water Resource Economics Consortium, Stockholm, Sweden, 2012-08-27 to 2012-08-28 |
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MA @ admin @ |
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2323 |
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Ahammad, H.; Heyhoe, E.; Nelson, G.; Sands, R.; Fujimori, S.; Hasegawa, T.; van der Mensbrugghe, D.; Blanc, E.; Havlik, P.; Valin, H.; Kyle, P.; d’Croz, D.M.; Meijl, H.V.; Schmitz, C.; Lotze-Campen, H.; von Lampe, M.; Tabeau, A. |
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The Role of International Trade under a Changing Climate: Insights from global economic modelling |
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2015 |
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293-312 |
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Elbehri, A. |
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Climate Change and Food Systems |
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5001 |
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Stevanović, M.; Popp, A.; Lotze-Campen, H.; Dietrich, J.P.; Müller, C.; Bonsch, M.; Schmitz, C.; Bodirsky, B.L.; Humpenöder, F.; Weindl, I. |
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The impact of high-end climate change on agricultural welfare |
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2016 |
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Science Advances |
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Sci. Adv. |
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2 |
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8 |
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e1501452 |
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ftnotmacsur |
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Climate change threatens agricultural productivity worldwide, resulting in higher food prices. Associated economic gains and losses differ not only by region but also between producers and consumers and are affected by market dynamics. On the basis of an impact modeling chain, starting with 19 different climate projections that drive plant biophysical process simulations and ending with agro-economic decisions, this analysis focuses on distributional effects of high-end climate change impacts across geographic regions and across economic agents. By estimating the changes in surpluses of consumers and producers, we find that climate change can have detrimental impacts on global agricultural welfare, especially after 2050, because losses in consumer surplus generally outweigh gains in producer surplus. Damage in agriculture may reach the annual loss of 0.3% of future total gross domestic product at the end of the century globally, assuming further opening of trade in agricultural products, which typically leads to interregional production shifts to higher latitudes. Those estimated global losses could increase substantially if international trade is more restricted. If beneficial effects of atmospheric carbon dioxide fertilization can be realized in agricultural production, much of the damage could be avoided. Although trade policy reforms toward further liberalization help alleviate climate change impacts, additional compensation mechanisms for associated environmental and development concerns have to be considered. |
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MA @ admin @ |
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5003 |
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Schmitz, C.; Kreidenweis, U.; Lotze-Campen, H.; Popp, A.; Krause, M.; Dietrich, J.P.; Müller, C. |
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Title |
Agricultural trade and tropical deforestation: interactions and related policy options |
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2014 |
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Regional Environmental Change |
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Reg Environ Change |
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15 |
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8 |
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1757-1772 |
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Land-use change; Trade liberalisation; Tropical deforestation; Forest; protection; Agricultural productivity growth; land-use; brazilian amazon; co2 concentrations; carbon emissions; conservation; climate; mitigation; forests; impact; growth; Environmental Sciences & Ecology |
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The extensive clearing of tropical forests throughout past decades has been partly assigned to increased trade in agricultural goods. Since further trade liberalisation can be expected, remaining rainforests are likely to face additional threats with negative implications for climate mitigation and the local environment. We apply a spatially explicit economic land-use model coupled to a biophysical vegetation model to examine linkages and associated policies between trade and tropical deforestation in the future. Results indicate that further trade liberalisation leads to an expansion of deforestation in Amazonia due to comparative advantages of agriculture in South America. Globally, between 30 and 60 million ha (5-10 %) of tropical rainforests would be cleared additionally, leading to 20-40 Gt additional emissions by 2050. By applying different forest protection policies, those values could be reduced substantially. Most effective would be the inclusion of avoided deforestation into a global emissions trading scheme. Carbon prices corresponding to the concentration target of 550 ppm would prevent deforestation after 2020. Investing in agricultural productivity reduces pressure on tropical forests without the necessity of direct protection. In general, additional trade-induced demand from developed and emerging countries should be compensated by international efforts to protect natural resources in tropical regions. |
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2016-10-31 |
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English |
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1436-3798 1436-378x |
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CropM |
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MA @ admin @ |
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4810 |
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Dietrich, J.P.; Schmitz, C.; Lotze-Campen, H.; Popp, A.; Muller, C. |
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Title |
Forecasting technological change in agriculture-An endogenous implementation in a global, and use model |
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2014 |
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Technological Forecasting and Social Change |
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Technological Forecasting and Social Change |
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81 |
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236-249 |
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Technological change; Land use; Agricultural productivity; Land use; intensity; Research and development; land-use; research expenditures; productivity growth; impact; deforestation; forest; yield; Business & Economics; Public Administration |
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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 029 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. (C) 2013 Elsevier Inc. All rights reserved. |
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2016-10-31 |
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0040-1625 |
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MA @ admin @ |
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4789 |
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