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Banse, M. |
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What drives meat consumption? Combining cross-country analysis with an applied trade model |
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2015 |
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FACCE MACSUR Reports |
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5 |
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Sp5-3 |
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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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MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK |
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2118 |
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Banse, M.; Brouwer, F.; Palatnik, R.R.; Sinabell, F. |
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The Economics of European Agriculture under Conditions of Climate Change (Editorial) |
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2014 |
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German Journal of Agricultural Economics |
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German Journal of Agricultural Economics |
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63 |
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3 |
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131-132 |
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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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TradeM, ft_macsur |
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4763 |
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Banse, M.; Köchy, M. |
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Opportunities for collaboration: MACSUR |
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2013 |
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4th Annual AgMIP Workshop, New York, USA, 2013-10-28 to 2013-10-30 |
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MA @ admin @ |
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2292 |
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Köchy, M.; Banse, M. |
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Modelling Efforts and Integrated Regional Studies in FACCE MACSUR |
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2013 |
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4th Annual AgMIP Workshop, New York, USA, 2013-10-28 to 2013-10-30 |
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MA @ admin @ |
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2555 |
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Salamon, P.; Banse, M.; Köchy, M. |
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MACSUR: Modelling European Agriculture with Climate Change for Food Security |
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2014 |
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23rd World Outlook Conference, Seville, Spain, 2014-05-12 to 2014-05-13 |
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MA @ admin @ |
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2782 |
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