Thünen-Baseline : Agri-economic projections for Germany - PDF

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F. Offermann, C. Deblitz, B. Golla, H. Gömann, H.-D. Haenel, W. Kleinhanß, P. Kreins, O. v. Ledebur, B. Osterburg, J. Pelikan, N. Röder, C. Rösemann, P. Salamon, J. Sanders and T. de Witte Landbauforsch

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F. Offermann, C. Deblitz, B. Golla, H. Gömann, H.-D. Haenel, W. Kleinhanß, P. Kreins, O. v. Ledebur, B. Osterburg, J. Pelikan, N. Röder, C. Rösemann, P. Salamon, J. Sanders and T. de Witte Landbauforsch Appl Agric Forestry Res (64)1-16 DOI:1.322/LBF_214_ Thünen-Baseline : Agri-economic projections for Germany Frank Offermann*, Claus Deblitz*, Burkhard Golla*****, Horst Gömann**, Hans-Dieter Haenel****, Werner Kleinhanß*, Peter Kreins**, Oliver von Ledebur***, Bernhard Osterburg**, Janine Pelikan***, Norbert Röder**, Claus Rösemann****, Petra Salamon***, Jürn Sanders* and Thomas de Witte* Abstract This article presents selected results of the Thünen-Baseline as well as the assumptions upon which these results are based. The Thünen-Baseline is established using and combining several models of the Thünen model network. It provides a reference scenario for the analysis of the impacts of alternative policies and developments. The projections are based on data and information available as of winter 213/14. The baseline assumes a continuation of the current policy framework and the implementation of already decided policy changes. For the Thünen-Baseline 213 to 223, this implies the implementation of the EU-CAP reform decided in 213 and its national implementation according to the decisions made at the German Ministers of Agriculture conference. Overall, the Thünen-Baseline 213 to 223 draws a picture of a competitive agricultural sector in Germany, which adapts well to the changes of the latest policy reform and seizes the opportunities for expanding production, especially in the dairy sector. On the other hand, the projections also highlight that under the assumptions made and with unchanged policy conditions the problems that may accompany intensive livestock production will not simply dissolve. In contrast, in view of the projected high profitability of intensive pig and poultry production the related challenges could increase. Keywords: agricultural policy, impact assessment, modelling, Germany Zusammenfassung Thünen-Baseline : Agrarökonomische Projektionen für Deutschland Die Thünen-Baseline 213 bis 223 ist eine auf den deutschen Agrarsektor fokussierte modellgestützte Projektion der erwarteten Entwicklungen auf der Grundlage der im Winter 213/14 vorliegenden Daten und Informationen. Sie stellt eine Referenzsituation für die Analyse von Auswirkungen alternativer Politiken und Entwicklungen dar. Die Thünen- Baseline geht von einer Beibehaltung der derzeitigen Agrarpolitik bzw. der Umsetzung bereits beschlossener Politikänderungen aus. Für die vorliegende Baseline bedeutet dies im Wesentlichen die Umsetzung der 213 beschlossenen Reform der Europäischen Agrarpolitik und ihrer nationalen Umsetzung entsprechend des Beschlusses der deutschen Agrarministerkonferenz. Insgesamt zeichnet die Thünen-Baseline 213 bis 223 das Bild einer wettbewerbsstarken Landwirtschaft in Deutschland, die sich gut an die Veränderungen der jüngsten Agrarreform anpasst und die Möglichkeiten zur Produktionsausdehnung, insbesondere im Milchbereich, wahrnimmt. Auf der anderen Seite zeigen die Projektionen, dass sich unter den getroffenen Annahmen und unveränderten politischen Rahmenbedingungen die Probleme, die sich aus der intensiven Tierproduktion ergeben können, nicht im Zeitablauf von selbst lösen, sondern im Gegenteil angesichts der projizierten Rentabilität der Veredlungsproduktion weiter an Bedeutung gewinnen könnten. Schlüsselwörter: Agrarpolitik, Politikfolgenabschätzung, Modellierung, Deutschland * Johann Heinrich von Thünen Institute, Institute of Farm Economics, Bundesallee 5, Braunschweig, Germany ** Johann Heinrich von Thünen Institute, Institute of Rural Studies, Bundesallee 5, Braunschweig, Germany *** Johann Heinrich von Thünen Institute, Institute of Market Analysis, Bundesallee 5, Braunschweig, Germany **** Johann Heinrich von Thünen Institute, Institute of Climate-Smart Agriculture, Bundesallee 5, Braunschweig, Germany ***** Julius Kühn Institute, Institute for Strategies and Technology Assessment, Stahnsdorfer Damm 81, Kleinmachnow, Germany Contact: 2 F. Offermann, C. Deblitz, B. Golla, H. Gömann, H.-D. Haenel, W. Kleinhanß, P. Kreins, O. v. Ledebur, B. Osterburg, J. Pelikan, N. Röder, C. Rösemann, P. Salamon, J. Sanders and T. de Witte Landbauforsch Appl Agric Forestry Res (64) Introduction This article presents and discusses selected results of the Thünen-Baseline 213 to 223 as well as the assumptions upon which these results are based. 1 The projections are based on data and information available as of winter 213/14. It is important to stress that the Thünen-Baseline is not a forecast about the future. Rather, the baseline describes expected developments should the current agricultural policy be continued in accordance with specific assumptions about the development of exogenous influences. The Thünen-Baseline thus serves as a reference scenario for analyses of the impacts of alternative policies and developments. It complements the more general and highly aggregated results of the baseline reports of the EU-Comission (213) and the OECD- FAO (213) by offering a detailed picture of the projected situation of German agriculture in 223, taking into account national policies. The assumptions for the development of the exogenous factors and the agricultural policy conditions selected for the baseline were chosen in close consultation with experts from the German Ministry of Food and Agriculture. Preliminary baseline results were discussed with representatives from the federal as well as Länder ministries. This approach enabled the integration of expert knowledge as well as the definition of a scenario that is widely accepted as a relevant basis for further policy impact analyses. 2 Methodology The Thünen-Baseline is established using and combining several models of the Thünen model network. The Thünen model network connects farm, regional and sector partial and general equilibrium models for the joint application for policy impact assessments. With the help of the model network, the impacts of a wide range of trade, agricultural and environmental policies on various facets of the agricultural sector, e.g. markets, production, environment, income, can be analyzed at different levels (Figure 1). In the analysis, a coordinated, parallel and/or iterative implementation of the model takes place. This implementation allows for the alignment of important assumptions, the exchange of model results as a basis for other models of the network, and the reciprocal check of the model results. This approach aims at providing a consistent overall result. The databases and characteristics of models used for the establishment of the Thünen-Baseline 213 to 223 are briefly described below. The MAGNET model (Modular Applied GeNeral Equilibrium Tool) is a multiregional, general equilibrium model covering global economic activity as well as single countries and regions (Woltjer et al., 213). It provides a detailed representation of the interactions between agriculture, the input sector and the food industry as well as commercial economics and the service sector, and accounts for the intra- and interregional 1 The full report with detailed results is published in German as Offermann et al. (214). linkages between markets and actors. MAGNET is based on a simultaneous system of non-linear equations, which ensure an equilibrium in the model and the identity between expenses and income. Behavioural equations describe the economic activities of different actors (for example, consumers and producers). Product demand, product supply and factor demand functions are specified so that consumers and producers maximize their utility or profit. Linking supply and demand, the model endogenously determines prices and quantities that lead to balanced product and factor markets. Trade modelling differentiates products by origin based on the Armington assumption (Armington, 1969) and considers transport requirements, and describes trade structure in the form of a matrix of bilateral trade flows (see Hertel and Tsigas, 1997). The GTAP data base 8.2 used for this study includes 57 sectors and 129 regions for the base year 27 (https://www.gtap. agecon.purdue.edu/databases/v8/v8_doco.asp). AGMEMOD (http://www.agmemod.eu) is a partial, multinational, multiple-product model based on econometrically estimated parameters and a recursive-dynamic approach. It covers production, consumption, trade, inventories and prices for 2 agricultural and 17 processing sectors of the EU member states, accession candidates and other neighbouring countries. The German model provides a detailed representation of grains and oilseed, potatoes, cattle and calves, sheep, pigs, poultry and milk as well as their processed products (Salamon and von Ledebur, 25). Coupled with each other and the appropriate world markets, the models create a combined EU Model for the individual EU Member States (van Leeuwen et al., 211). In the present model, version 7, the world markets are endogenous, but calibrated to fit to the OECD price projections (OECD-FAO, 213). The data base covers the years 1973 to 212. The regionalized agricultural and environmental information system RAUMIS (Henrichsmeyer et al., 1996) is employed to analyze medium and long-term agricultural and environmental policy impacts. The model consolidates various agricultural data sources with the national agricultural accounts as a framework of consistency. It comprises of more than 5 agricultural products, 4 inputs with exogenously determined prices, and reflects the German agricultural sector with its sector linkages. According to data availability, the spatial differentiation is based on administrative bodies, i.e., 326 regions (NUTS III level) treated as single region farms. Production adjustments caused by changes in the general framework conditions such as agricultural policies are determined by using a comparative-static mathematical programming approach that maximizes a non-linear objective function for regional farm income. The model is calibrated to observed production decisions using a positive mathematical programming approach (Howitt, 1995; Cypris, 2). Model base years are available in four-year intervals from 1979 to 21. Farm level aspects are covered by FARMIS, a process-analytical programming model for farm groups (Osterburg et al., 21; Offermann et al., 25; Deppermann et al., 213) based on information from the farm accountancy data network (FADN). Production is differentiated for 27 crop and 15 F. Offermann, C. Deblitz, B. Golla, H. Gömann, H.-D. Haenel, W. Kleinhanß, P. Kreins, O. v. Ledebur, B. Osterburg, J. Pelikan, N. Röder, C. Rösemann, P. Salamon, J. Sanders and T. de Witte Landbauforsch Appl Agric Forestry Res (64) Coverage Model Aggregation level World economy Agric. markets German agricultural sector MAGNET AGMEMOD GAS-EM RAUMIS FARMIS Global economic framework Worldwide agri benchmark World EU - Member states Price changes Germany - Counties Production change County farms Sector constraints Aggregation - Farms Farm adaptions Farm groups Adaptive behaviour Typical farms Main focus for Thünen-baseline Agricultural trade Prices and demand Environment (Gas emissions) Supply Income Adjustment strategies Regional focus of the respective model for the Thünen-Baseline. Figure 1 The use of models of the Thünen model network for the establishment of the Thünen-Baseline livestock activities. The matrix restrictions cover the areas of feeding (energy and nutrient requirements, calibrated feed rations), intermediate use of young livestock, fertilizer use (organic and mineral), labour (seasonally differentiated), crop rotations and political instruments (e.g., set-aside and quotas). The model is calibrated to observed production decisions and elasticities using a positive mathematical programming approach. For this study, the model specification is based on data from the accounting years 29/1, 21/11 and 211/12. The farm sample was stratified by region, type, system and size, resulting in 646 farm group models (of which 9 groups represent organic farming). Results are aggregated to the sector using farm group specific weighting factors. To account for structural change, econometrically estimated farm exit probabilities were applied to the aggregation factors for the projection. Within regions, farms compete for land on rental markets (Bertelsmeier, 25). TIPI-CAL und TYPICROP are accounting models applied within the framework of the global agri benchmark network (www.agribenchmark.org). They represent in detail production technology and physical interrelationships at farm level. As part of the model network, these models are mainly used to analyze the impacts of changes in policy, economic, and regulatory framework on selected farms, and to investigate the financial consequences of different alternative farm adjustments and development strategies. The database comprises typical farms, which are established based on a globally harmonized Standard Operating Procedure together with more than 4 partners in different countries. Data are collected annually, and the validation of results and specification of adjustment strategies is done in cooperation with farmers and advisors. For the projection of greenhouse gas and ammonia emissions from agriculture in the baseline scenario, the Thünen model network is linked to the model GAS-EM. GAS-EM is a modular spreadsheet programme to estimate gaseous and particulate emissions from animal agriculture and crop production including professional horticulture. GAS-EM was first described in Dämmgen et al. (22) and has been developed further continuously since then. The assessment of emissions within GAS-EM uses the definitions of agriculture according to the definitions of IPCC. All calculation procedures involved are based on the rules provided by the respective conventions and the current guidance documents. In addition, the German agricultural inventory uses differing methods in specific circumstances in order to improve the description of national emission conditions (Haenel et al, 214). It is used to generate the official National Emission Inventory Reports for Germany. For this study, the projections of gaseous emissions in 223 are based on the RAUMIS projections for land use and livestock numbers in the baseline scenario. For the analysis of the impact of the new greening requirements (see section 3.2), the extent of existing landscape elements was established based on the ATKIS Basic Landscape Model (ATKIS Basic DLM). The ATKIS describes the topographic features of the landscape in vector format. The features are assigned to a certain feature type and defined on the basis of their spatial position, their geometrical type, descriptive attributes and relations to other objects (relations) (AdV, 28). Spatial analysis of ATKIS adopts a method used to establish the Index of regional proportions of ecotones (Enzian and Gutsche, 24). Since 22 this GIS-based register is established in German pesticide risk management. It adjusts 4 F. Offermann, C. Deblitz, B. Golla, H. Gömann, H.-D. Haenel, W. Kleinhanß, P. Kreins, O. v. Ledebur, B. Osterburg, J. Pelikan, N. Röder, C. Rösemann, P. Salamon, J. Sanders and T. de Witte Landbauforsch Appl Agric Forestry Res (64)1-16 pesticide risk mitigation measures for differences in landscape composition according to the amount of semi-natural habitats. The method involves a topological analysis of the landscape features and the land use/land cover (LULC) types represented by ATKIS. It allows the identification and quantification of transition areas between LULC types and landscape features. Transition areas are grouped into (1) transition areas with direct proximity of two LULC types (e.g. the zone between a crop field and grassland, crop field and settlement, crop field and forest) and (2) indirect proximity of two LULC types interrupted by streams, ditches, hedges, roads etc. 3 Assumptions 3.1 General economic framework The Thünen-Baseline 213 to 223 builds on external projections for macroeconomic developments from 213 to 223, as compiled in secondary sources like the USDA (211, 212). The baseline scenario is characterized by an annual growth of the world economy of 3.3 %, and a more modest growth in Germany (1.75 % p. a.). World population growth is projected to increase by 1 % p. a., while the population in Germany is slightly declining (-.2 % p. a.). The baseline scenario assumes that the Euro continuously gains in value compared to the US-Dollar, resulting in an exchange rate of 1.41 $/ in 223 (EU-Commission, 213). As international trade mostly takes place in US-Dollar, this lowers world market prices from the point of countries of the Eurozone. Inflation in Germany remains low at 1.7 % p. a. Agricultural land in Germany is assumed to continue to be lost at an annual rate of -.1 %, accompanied by structural change at historic rates with a decline of farm numbers by -3.4 % each year. The assumptions for the development of input prices in Germany are generally based on historical trends from 23 to 212. For energy inputs, the oil price projections used in the OECD- FAO-outlook (213) are applied, which imply continuously high price increases (+3.1 % p. a). Due to the high importance of energy costs for the production of nitrogen fertilizers, fertilizer prices were also linked to the price forecasts of oil. World market price projections 2 for agricultural products from the OECD-FAO (213) are used as a calibrated basis in the AGMEMOD model to establish price developments in the EU and Germany. For the projection period international prices for livestock products, expressed in Euro, rise further (+1 % to +3 %) compared to the already high price level in 29 to 211, whereas world market prices for crop products decrease slightly. 3.2 Policy framework The baseline assumes a continuation of the current policy framework and the implementation of already decided policy changes. For the Thünen-Baseline 213 to 223, this implies the implementation of the EU-CAP reform decided in 213 and its national implementation according to the decisions 2 All price developments refer to nominal prices. made at the German Ministers of Agriculture conference. The most important policy assumptions of the baseline can be summarised as follows: Trade policy framework: The baseline accounts for the EU accession of Croatia, and numerous bilateral trade agreements which will be implemented over the following years (e.g. with countries in South America and North Africa and the Balkan states). Price and quota policies: EU regulation No. 138/213 foresees a safety net with public intervention mechanisms for selected products. In addition, the EU commission has at its disposal a reserve fund for crisis prevention and management measures, to be able to react to general market disturbances. The Thünen-Baseline presumes that neither these measures nor export support for milk products are applied during the projection horizon due to the prevailing world market conditions. The baseline scenario takes into consideration the stepwise increase of the milk quota until 213/14 and its abolishment in 215. The sugar market reform is implemented based on the study by Gocht et al. (212), and covers the end of the quota regime in 217 while maintaining border protection. In view of the OECD- FAO projection of world market prices, an EU-internal sugar price of 39 /t in 223 results from these calculations. Direct payments of the first CAP pillar: The redistribution of funds between EU member states, the national redistribution of 4.5 % of the budget to the second pillar, and support for young farmers lead to a base payment of 175 /ha and a greening payment of 85 /ha. To support smaller farms, a top-up is granted of 5 /ha for the first 3 ha and 3 /ha for th
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