Distributional Effects of the CAP on Western German Farm Incomes and Regional Farm Income Disparity

This study is concerned with measuring impacts of the Common Agricultural Policy (CAP) on farm income distribution of western Germany. Not only the sheer contribution of market price support and direct payments as a proportion of income is taken into account, but also the impact of support on production incentives. For this purpose, we apply a modelling system consisting of a partial equilibrium model and a programming model. Based on a comparison of Gini coefficients and a decomposition of overall inequality effects we conclude that liberalization of the agricultural sector leads to a more unequal distribution of family farm income in relative terms, whereas a liberalized market provides a more equal situation in absolute terms. Furthermore, we consider the impacts of liberalizing the agricultural market on regional differences in average agricultural income and conclude that in relative terms liberalization increases regional inequality.Income distribution, CAP, Farm Group Model, Equilibrium Model, Agricultural and Food Policy, Agricultural Finance,

An ex-ante analysis of distributional effects of the CAP on western German farm incomes

This study is concerned with measuring impacts of the Common Agricultural Policy (CAP) on farm income distribution of western Germany. Not only the sheer contribution of market price support and direct payments as a proportion of income is taken into account, but also the impact of support on production incentives. For this purpose, we apply a modelling system consisting of a partial equilibrium model and a programming model. Based on a comparison of Gini coefficients and a decomposition of overall inequality effects we conclude that liberalization of the agricultural sector leads to a more unequal distribution of family farm income in relative terms, whereas a liberalized market provides a more equal situation in absolute terms.Income distribution, CAP, Farm Group Model, Equilibrium Model, Agricultural and Food Policy, Q11, Q12, Q18, C54, C6, D31,

EFFEKTE EINER EU-AGRARMARKTLIBERALISIERUNG AUF BETRIEBSEBENE: SIMULATIONEN ANHAND EINES EUROPÄISCHEN AGRARSEKTORMODELLS UND EINES ANGEBOTSMODELLS FÜR DEN DEUTSCHEN AGRARSEKTOR

Verlinkung von Modellen, Politikfolgenabschätzung, Einkommenswirkung, Agricultural Finance, Research Methods/ Statistical Methods,

Ex-ante measurement of redistributive effects of agricultural policy in western Germany

In recent decades, agricultural support of the European Common Agricultural Policy (CAP) has increasingly shifted from market price support measures to budgetary payments. This development has made support more visible and has raised public attention to the distribution of support, which in turn increased political awareness of the topic. Simulation models are tools frequently used for the ex-ante analysis of policy reforms. In other scientific areas, e.g. poverty analysis or tax reform analysis, it is quite common to assess impacts of macroeconomic shocks on income distribution on a national scale by the application of behavioural ex-ante models and referring to the level of individual incomes. Similar tools for the measurement of impacts of sectoral or macroeconomic policies on the individual farm income level are less frequent for the agricultural sector and, apart from few exceptions, ex-ante studies of redistributive effects of agricultural policy are rare. Yet, in general, ex-ante policy impact analysis in the agricultural sector has a long tradition. The combination of models to jointly assess effects at different levels of aggregation and taking behavioural effects into account is very common. Most of the model chains, however, take farm groups or average farms into account rather than accounting for effects at the individual farm level. Some attempts have been made to combine macro or sectoral models with micro models, which incorporate the behaviour of individual farms. Such research, however, is often restricted to the analysis of certain types of farms. In general, ex-ante analyses of redistributive effects among individual farms on a supra-regional level in the sense of evaluating a counterfactual distribution of income with regard to a reference distribution of income including an assessment of progressivity or related concepts can hardly be found for the agricultural sector. Against this background, the main objective of this work is to develop a tool that is able to consistently assess impacts of agricultural policy on individual farm incomes, thereby building on existing modelling approaches and thus, taking behavioural effects into account for the ex-ante analysis of redistributive effects of agricultural policy. Subsequently, different liberalization scenarios are defined and a detailed analysis of redistributive effects is carried out for the western German agricultural sector by the application of methodologies borrowed from the field of tax progressivity analysis. Thereby, several contributions to the understanding of modelling inequality effects are made, methodologically as well as empirically. The modelling system consists of three layers. At the sectoral and the meso-level two previously developed large scale models are applied. The European Simulation Model (ESIM) is an agricultural sector model with a strong focus on the CAP. It depicts the world agricultural sector though in different degrees of regional disaggregation and quantifies effects of agricultural policy at the European and member state level. It is, however, unable to estimate intra-sectoral income changes at the farm level. The Farm Modelling Information System (FARMIS) is a more disaggregate model that depicts the German agricultural sector in great detail. It applies 628 homogenous farm groups and is used in the modelling chain to estimate impacts on the intra-sectoral distribution of income at the meso-level. The two models at the sectoral and meso-level are consistently linked via an iterative solution process. After convergence is achieved between ESIM and FARMIS, the integrated results are further processed in a micro model, estimating impacts at the individual farm level. The micro model has been developed for this study, is static in nature, and relies on the results of the meso-model. After changes in individual incomes are calculated as a first step by the modelling system for different scenarios, model results are analysed in a second step by the application of a methodology for the measurement of redistributive effects that was originally developed for the analysis of tax reforms. Based on the comparison and decomposition of relative and absolute Gini coefficients, detailed redistributive impacts of changes in agricultural policy are presented. For the analysis, scenario results for the year 2020 are evaluated relative to the income distribution of a reference scenario where the CAP is still in place in 2020. To account for different conceptual impacts of inequality analysis on results, the analysis is carried out at different aggregation levels, for different income classifications, and for income data generated in a static way in comparison to data generated by the modelling system. It can be stated that inequality effects are robust with regard to the conceptual differences tested for, at least in terms of the direction of inequality changes. All calculated liberalization scenarios lead to decreasing absolute income differences among western German farms in 2020 because high-income farms lose higher absolute amounts of money than small-income farms. Relative to their Baseline incomes, however, low-income farms tend to lose a higher share compared to high-income farms which leads to increasing relative inequality due to liberalization. Only one exemption from this pattern of results exists: if grouped results are disaggregated and total household income is considered instead of family farm income. In summary, this work provides an innovative combination and extension of different simulation models, which enables the ex-ante measurement of income changes for individual farms. This information in turn facilitates the measurement of redistributive effects in the agricultural sector taking behavioural effects into account.Verschiedene Reformen der letzten Jahrzehnte haben die Ausgestaltung der Gemeinsamen Agrarpolitik (GAP) der Europäischen Union grundlegend verändert. Traditionelle Instrumente der Marktpreisstützung wurden in zunehmendem Maße durch Direktzahlungen an landwirtschaftliche Betriebe ersetzt. Diese Entwicklung führte zu einer erhöhten Transparenz in der politischen Stützung des Agrarsektors und rückte die Frage der Verteilung von Subventionen stärker in den Fokus des öffentlichen Interesses. Für die Analyse einer politischen Reform vor ihrer Umsetzung wird regelmäßig auf Simulationsmodelle zurückgegriffen. In anderen wissenschaftlichen Bereichen beispielsweise in der Analyse von Armutseffekten oder in der Analyse von Steuerreformen ist es gängige Praxis, die Auswirkungen makroökonomischer Veränderungen auf die individuelle Einkommensverteilung eines Landes durch die Anwendung von Simulationsmodellen vorab zu bewerten. Ähnliche Instrumente für die Bemessung von Auswirkungen sektoraler oder makroökonomischer Politiken auf die Höhe individueller Einkommen gibt es weniger oft für die Analyse des Agrarsektors. Grundsätzlich gibt es jedoch eine lange Tradition in der Entwicklung von Modellen für die Politikfolgenabschätzung im Agrarsektor. Auch die kombinierte Nutzung von verschiedenen Einzelmodellen für die gemeinsame, konsistente Bewertung von Politikszenarien auf verschiedenen Aggregationsstufen ist üblich. Die meisten Modell-Kombinationen beziehen sich jedoch auf die Auswertung von Betriebsgruppen oder Durchschnittsbetrieben als niedrigste Aggregationsstufe. Es existieren einige Ansätze, die Makromodelle mit Mikromodellen verknüpfen, die ihrerseits Verhaltensanpassungen einzelner Betriebe abbilden. Viele dieser Studien beschränken sich jedoch auf die Abbildung von bestimmten Betriebstypen oder Regionen. Grundsätzlich ist festzuhalten, dass bislang nur sehr wenige überregionale ex-ante Analysen von betriebsindividuellen Verteilungseffekten durchgeführt wurden. Vor diesem Hintergrund ist es Ziel der vorliegenden Arbeit, eine Analysemethode zur simultanen und konsistenten Bewertung von agrarpolitisch induzierten Einkommensverteilungswirkungen auf aggregierter und betriebsindividueller Ebene im Agrarsektor zu entwickeln. Dabei wird auf bereits bestehende Einzelmodelle zur Politikfolgenabschätzung zurückgegriffen. Mit der entwickelten Methode werden verschiedene Liberalisierungsszenarien der europäischen Agrarpolitik ausgewertet. Eine detaillierte Analyse von Auswirkungen auf die betriebsindividuelle Einkommensverteilung wird für den westdeutschen Agrarsektor präsentiert. Das in der vorliegenden Arbeit entwickelte Modellsystem besteht aus drei verschiedenen Stufen. Auf der sektoralen Ebene und dem Meso-Level kommen zwei bereits existierende Modelle zur Politikfolgenabschätzung zum Einsatz. Das European Simulation Model (ESIM) ist ein Agrarsektormodell mit einem starkem Fokus auf die europäische Agrarpolitik. Das Modell wird zur Quantifizierung von agrarpolitisch induzierten Effekten auf europäischer Ebene sowie auf Ebene der Mitgliedstaaten verwendet. Aufgrund seiner hohen Aggregationsebene kann das Modell jedoch nicht zur Bestimmung von intra-sektoralen Einkommensänderungen verwendet werden. Hierzu wird das Farm Modelling Information System (FARMIS) hinzugezogen. Letzteres operiert auf einer niedrigeren Aggregationsstufe und bildet die Produktionsseite des deutschen Agrarsektors in größerem Detail ab. In dem Modell werden 628 homogene Betriebsgruppen verwendet. Die beiden Modelle werden in einem iterativen Prozess miteinander verlinkt. Nachdem Konvergenz erreicht ist, werden die Ergebnisse für die 628 Betriebsgruppen in einem Mikromodell weiter disaggregiert. Das Mikromodell wurde für die vorliegende Studie entwickelt. Es handelt sich um ein statisches Modell, das eng auf das FARMIS Modell abgestimmt ist. Die in einem ersten Schritt unter Anwendung des Modellsystems simulierten betriebsindividuellen Einkommensänderungen werden in einem zweiten Schritt analysiert. Zu diesem Zweck wird eine Methode zur Messung von Verteilungseffekten angewendet, die ursprünglich für die Analyse von Steuerreformen entwickelt wurde. Basierend auf einem Vergleich und einer Zerlegung von relativen und absoluten Gini-Koeffizienten können detaillierte Aussagen über die Auswirkungen von agrarpolitischen Reformen auf die Einkommensverteilung im Agrarsektor getroffen werden. Um den Einfluss verschiedener methodischer Ansätze auf die Ergebnisse abzuschätzen, wird die Analyse für verschiedene Aggregationslevel, verschiedene Einkommensklassifizierungen und verschiedene Arten der Berechnung von Einkommensänderungen (statisch versus modellbasiert) durchgeführt. Bezüglich der Ergebnisse kann konstatiert werden, dass die getesteten konzeptionellen Unterschiede mit einer Ausnahme keinen Einfluss auf die Richtung der Verteilungseffekte haben. Die simulierten Szenarien, die einen Abbau der Agrarpolitik beinhalten, führen zu einer Verringerung von absoluten Einkommensunterschieden zwischen westdeutschen Betrieben im Jahr 2020. Betriebe, die im Referenzszenario ein hohes Einkommen erzielen, verlieren durch eine Liberalisierung absolut gesehen mehr Einkommen, als Betriebe mit geringerem Einkommen in der Referenzsituation. Relativ gesehen verlieren jedoch Betriebe mit geringerem Einkommen einen größeren Anteil ihres Referenzeinkommens in 2020 als Betriebe mit höherem Referenzeinkommen. Dieses führt zu einer Vergrößerung von relativer Ungleichheit, aber zu einer Verringerung von absoluter Ungleichheit

Food and nutrition security in Europe – a quantification of multi-stakeholder scenarios

Conference presentation PD

ERTRAGS- UND PREISINSTABILITÄT AUF AGRARMÄRKTEN IN DEUTSCHLAND UND DER EU

Agrarpolitik, Preisvolatilität, Ertragsschwankungen, Unsichereit, Gemeinsame Agrarpolitik, Agricultural and Food Policy, Demand and Price Analysis, International Relations/Trade,

Spatial distribution of arable and abandoned land across former Soviet Union countries

Knowledge of the spatial distribution of agricultural abandonment following the collapse of the Soviet Union is highly uncertain. To help improve this situation, we have developed a new map of arable and abandoned land for 2010 at a 10 arc-second resolution. We have fused together existing land cover and land use maps at different temporal and spatial scales for the former Soviet Union (fSU) using a training data set collected from visual interpretation of very high resolution (VHR) imagery. We have also collected an independent validation data set to assess the map accuracy. The overall accuracies of the map by region and country, i.e. Caucasus, Belarus, Kazakhstan, Republic of Moldova, Russian Federation and Ukraine, are 90±2%, 84±2%, 92±1%, 78±3%, 95±1%, 83±2%, respectively. This new product can be used for numerous applications including the modelling of biogeochemical cycles, land-use modelling, the assessment of trade-offs between ecosystem services and land-use potentials (e.g., agricultural production), among others

Land-based measures to mitigate climate change : potential and feasibility by country

Acknowledgements The design of this study and the data generated was guided by expert consultations and relied on the help of many. We thank all those who contributed: Sierra Gladfelter, Jo House, Mercedes Bustamante, Susan Cook-Patton, Sara Leavitt, Nick Wolff, and Thomas Worthington. We thank M.-J. Valentino at Imaginary Office for helping to design the first three figures. This work was supported by the authors’ institutions and funding sources, including the Climate and Land-use Alliance, the Dutch Ministry of Agriculture, Nature Management and Food Quality, and the EU H2020 projects VERIFY and ENGAGE (grant agreement no. 821471).Peer reviewedPublisher PD

Cost and attainability of meeting stringent climate targets without overshoot

Global emissions scenarios play a critical role in the assessment of strategies to mitigate climate change. The current scenarios, however, are criticized because they feature strategies with pronounced overshoot of the global temperature goal, requiring a long-term repair phase to draw temperatures down again through net-negative emissions. Some impacts might not be reversible. Hence, we explore a new set of net-zero CO2 emissions scenarios with limited overshoot. We show that upfront investments are needed in the near term for limiting temperature overshoot but that these would bring long-term economic gains. Our study further identifies alternative configurations of net-zero CO2 emissions systems and the roles of different sectors and regions for balancing sources and sinks. Even without net-negative emissions, CO2 removal is important for accelerating near-term reductions and for providing an anthropogenic sink that can offset the residual emissions in sectors that are hard to abate

Land-based implications of early climate actions without global net-negative emissions

Delaying climate mitigation action and allowing a temporary overshoot of temperature targets require large-scale carbon dioxide removal (CDR) in the second half of this century that may induce adverse side effects on land, food and ecosystems. Meanwhile, meeting climate goals without global net-negative emissions inevitably needs early and rapid emission reduction measures, which also brings challenges in the near term. Here we identify the implications for land-use and food systems of scenarios that do not depend on land-based CDR technologies. We find that early climate action has multiple benefits and trade-offs, and avoids the need for drastic (mitigation-induced) shifts in land use in the long term. Further long-term benefits are lower food prices, reduced risk of hunger and lower demand for irrigation water. Simultaneously, however, near-term mitigation pressures in the agriculture, forest and land-use sector and the required land area for energy crops increase, resulting in additional risk of food insecurity