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Nendel, C., Ewert, F., Rötter, R. P., Rosenzweig, C., Jones, J. W., Hatfield, J. L., et al. (2013). Addressing challenges and uncertainties for, the use of agro-ecosystem models to, assess climate change impact and food security across scales..
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Banse, M., Brouwer, F., Palatnik, R. R., & Sinabell, F. (2014). The Economics of European Agriculture under Conditions of Climate Change (Editorial). German Journal of Agricultural Economics, 63(3), 131–132.
Abstract: This Special Issue on “The Economics of European Agriculture under Conditions of Climate Change” brings together a selection of papers that contribute to the understanding of recent developments related to agriculture and climate change in four European coun- tries. The focus of the Special Issue is on quantitative modeling and empirical analyses. The papers presented here not only cover the heterogeneity of agriculture in Europe with case studies from the Mediterranean (Italy), central (Austria) and north-western Europe (Ireland and Scotland) but also give insights into the diversity of quantitative modeling approaches in agriculture.
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Köchy, M., & Banse, M. (2013). Food security — is climate important at all? (pp. 165–172).
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Banse, M. (2015). Climate-change impacts on farming systems in the next decades: Why worry when you have CAP? A FACCE MACSUR workshop for policymakers – Introduction. In FACCE MACSUR Reports (Vol. 6, pp. SP6–1). Brussels.
Abstract: MACSUR’s aims•To analyze the effects of climate change for farming conditions in European regions •To identify risks for farmers, to jointly develop mitigation and adaptation options•To analyze consequences of mitigation and adaptation for farming competitiveness, the environment and rural developmentMACSUR’S mission •improve and integratemodels – crop and livestock production, farms, and national & international agri-food markets•demonstrate integration and links – models for selected farming systems and regions •provide hands-on training- young and experienced researchers in integrative modelingProgramme of the workshop•Presentation of current achievements—Regional Pilots on climate adaptation —EU-level assessments •Intensive discussion with all participants—What are your knowledge needs ?—What can MACSUR-2 contribute ?—How to collaborate ?—Next steps of interaction No Label
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Banse, M. (2015). What drives meat consumption? Combining cross-country analysis with an applied trade model (Vol. 5).
Abstract: In a cross country analysis using national data for both OECD and developing countries, we estimate a regression model with different coefficients for different drivers for per capita meat consumption. The model contains data from approximately 125 countries (depending on the variables included) on meat consumption and production, relative size of agricultural area and pasture and meadows, PPP adjusted consumer prices for meat (and for food as control variable), PPP adjusted GNI per capita, HDI, degree of urbanisation, religion and geographical/cultural belonging.A regression analysis has been conducted, using OLS with data from 2011 and an aggregation of all meat types as the dependent variable. In the results all of the mentioned variables have a significant impact on meat consumption.Based on a first scenario analysis which has been presented on a TradeM Workshop of MACSUR in September 2014, this paper will extend the approach of an estimated cross-country analysis to improve the demand elasticities in the MAGNET model for meat and meat products. Further other demand determining factors of meat consumption, e.g. behavioural change towards less meat consumption (vegetarian or vegan) derived from the regression analysis will be fed into the MAGNET model. This extended approach will help to analyse the resulting market effects of a changing demand pattern for meat. MAGNET will provide insights in consequences on supply and international trade for meat and meat products.The aim of this combined approach is to further explore the relationship between production and consumption, and to what extent the one is driving the other. Based on the application of the panel data method for a detailed demand analysis with the combination of the feedback from the supply and trade side based on the MAGNET model we will be able to provide a tool which is able to address the important questions of demand responses under different adaptation or mitigation strategies towards clime change, such as tax measures like fat taxes. This extended tool also contributes to an improved decision making process of policy makers under different options to respond to climate change issues – not only with regard to the supply side of agricultural production but also to the consumption side. No Label
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