69 research outputs found

    Sustainability indicators for improved assessment of the effects of agricultural policy across the EU: Is FADN the answer?

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    peer-reviewedPolicy reform of the CAP and society’s expectations of agriculture have resulted in a growing need for improved information on the effectiveness of policy in achieving high-level objectives for more sustainable practice in agriculture. This is a high priority given its importance for consumers, public policy and private industry. Data collection programmes will need to adapt their scope if their information is to adequately address new information needs about high-level objectives. Assessment of sustainability at the farm level is hindered by the lack of data with which to derive appropriate, meaningful, and relevant indicators. This is particularly problematic for assessment of agricultural sustainability across the European Union (EU). Various databases exist at the EU scale regarding agricultural data sources and we identify one of these, the EU Farm Accountancy Data Network (FADN), as having considerable potential to assess farm-level sustainability at EU level. We critique several examples of published work that has attempted to assess agricultural sustainability using: FADN data alone; FADN data in combination with data from supplementary surveys, and; FADN data in combination with data from other EU databases. We conclude that the FADN would need to broaden its scope of data collection if it is to address the new information needs of policy, and we discuss the challenges in expanding FADN with a view towards wider farm-level assessment of sustainability. These include careful selection of indicators based on various criteria, the representativeness of the FADN, and the need to include new themes to address environmental, social, and animal welfare effects of policy.This work was partly funded by the FLINT project under the EU Seventh Framework Programme grant number 613800

    Sustainability and Production Costs in the Global Farming Sector: Comparative Analysis and Methodologies

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    This report constitutes a comprehensive compilation and synthesis of the principle issues and outcomes of the joint Institute for prospective Technological Studies / Directorate-General for Agriculture and Rural Development workshop on "Sustainability and Production Costs in the Global Farming Sector: Comparative Analysis and Methodologies" held in Brussels between 21-22 June 2011. Gathering a range of international experts and specialists in the field of production costs analysis and development, covering a range of strategic agricultural sectors of global importance, the workshop aimed to review methodologies and approaches to calculating production costs used in various sectors nationally and globally, with emphasis on exploring the applicability for effective international comparisons. A special attention was given to the methodologies and approaches for data collection and processing, factor market structure and policy inter-linkages, sectoral coverage, horizontal technical issues, and the implications for global agricultural markets. Based on the participant deliberations and discussions, a number of practically based policy recommendations towards achieving such comparisons were highlighted. The production of this report, following completion of the workshop, has been the responsibility of the IPTS. This task has been facilitated through collaboration with four internationally recognised experts (Folkhard Isermeyer, von Thünen-Institute, Germany (Chapter 2), Dan L. Cunningham, University of Georgia, USA (Chapter 3), Jean-François Garnier, ARVALIS, France (Chapter 4), Ashok K. Mishra, Louisiana State University, USA (Chapter 5)) acting as rapporteurs for each of the workshop's four technical sessions, whose efforts in capturing the principle issues and outcomes of their respective session has been instrumental towards realisation of this report. Stephen Langrell, Pavel Ciaian and Sergio Gomez y Paloma acted as Editors and compiled Chapters 1 and 6. This report constitutes a particular and comprehensive technical overview of the state of production costs calculations for the sectors under consideration at global level, and a consideration of the prospects for effective international comparison. It reviews methodologies applied for production costs calculation at national and global level followed by the discussion on methodologies used for animal and arable crop sectors. Finally, the report discusses horizontal issues related to production costs calculations. The report closes with policy-relevant conclusions as a basis for policy recommendations. It is envisaged that this report will provide a valuable source of technical and conceptual information for on-going policy considerations, both at EU and third country/international level.JRC.J.4-Agriculture and Life Sciences in the Econom

    Sustainable technology adoption: who and what matters in a farmer's decision?

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    EU milk quota removal brings a renewed focus on continued adoption of sustainable technologies. This article explores spatial effects in their adoption using Bayesian spatial probit models employing a representative sample of Irish dairy farms. We consider global and local spatial effects, and overcome a missing neighbour problem by implementing census data in our spatial weight matrix. The findings reveal that spatial effects spill over to neighbours and better educated farmers with larger more intensively managed farms are more likely to adopt. The article concludes with policy recommendations that arise from our spatial analysis

    Development of a European Information System for Organic Markets - Improving the Scope and Quality of Statistical Data. Proceedings of the 1st EISfOM European Seminar, held in Berlin, Germany, 26-27 April, 2004

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    Contents Plenary Session Welcome address Massimo Burioni Introduction to the European Information System for Organic Markets and the aims of the 1st EISfOM European Seminar, Berlin, April 2004 Nicolas Lampkin The current situation of data collection and processing of organic farming and marketing across Europe Toralf Richter Problems and solutions for the collection of data on organic markets: experiences from previous research projects Ulrich Hamm Current Eurostat initiatives on organic farming statistics Ana Martinez Organic agricultural statistics and information at the United Nations Food and Agriculture Organisation: initiatives, opportunities and challenges Robert Mayo Stakeholder perspectives on the need for data and the role of private and public institutions Victor Gonzálvez Quality assurance issues in DCPS for agricultural commodities: an analysis of the theoretical and analytical tools and methods used in the assessment of data quality Guido Recke Data received from Member States in accordance with Regulation 2092/91 Per Ahle Group 1: Farm Production - Farm Structure Survey (FSS) and administrative (2092/91) data Results from the Community farm structure survey and Council Regulation (EEC) No. 2092/91 reporting: organic farming data and derived agri-environmental indicators Koen Duchateau Compilation of basic statistical data on organic farming in Europe and worldwide - challenges and opportunities Minou Yussefi, Santiago Olmos, Helga Willer Problems regarding the official statistical survey on organic agriculture in Italy 6 M. Adua and A. Pallotti Opportunities for the development of organic data collection and processing based on Finnish experiences Sampsa Heinonen The “Observatoire”of French organic production: data collection since 1995 and future developments Katell Guernic Organic production in official agricultural statistics of Germany Torsten Blumöhr Developing the data collection system for organic farming in Poland Marta Wroblewska, Ewa Szymborska International data harmonisation - learning from UK experiences Rob Haward Data collecting and evaluation of the organic agriculture system in Turkey Erdal Süngü Results of Group 1: Farm Structure Survey (FSS) and administrative (2092/91) data Lizzie Melby Jespersen and Helga Willer Group 2: Farm Incomes and Prices Information systems on organic farming: FADN and market statistics Krijn J. Poppe Summarizing results from earlier EISfOM activities on farm incomes and farm level prices Sjaak Wolfert Current and future perspectives for economic analyses on organic farming with the EU-FADN Alberto D’Avino Comparing organic and conventional farm incomes in FADN - Issues in international harmonisation and quality assurance Frank Offermann Acquisition of participants for the FADN in Germany and practical issues of quality management Rainer Meyer The integration and analysis of data on organic farming in the Swiss Farm Accountancy Data Network Beat Meier ZMP-Comparison of producer prices for milk Reinhard Schoch Determination of organic product prices at farm level Markus Rippin Producer price premiums – an indicator for the viability of organic farming at the European level? Nicolas Lampkin HDRA’s contribution to organic horticultural data collection in Europe Ulrich Schmutz and Chris Firth Results of Group 2: Farm Incomes and Prices Jürn Sanders and Johan Bakker Group 3: Supply chain/Trade (Import/Export) volumes and prices 147 Understanding organic markets and the production of relevant statistics with special focus on the trade/wholesaler/processor level Jens Vestergaard The price of organic fruit and vegetables: analysis of one year of monitoring from production to consumer in Italy Francesco Giardina and Luigi Guarrera BioStockManager®: A software solution for data collection along the whole supply chain Harald Falkner Statistics on organic farming and organic products in Denmark Poul Henning Larsen e-Cert, inspection and certification software Frank Rumpe Stakeholder perspectives and data management Conrad Thimm Results of Group 3: Statistics on organic farming: Supply Chain Level Norbert Gleirscher and Raffaele Zanoli Group 4: Retailers and consumers Information from household panels about the market for organic farming Micaela Schantl Retailer and consumer panel data: strengths and weaknesses in surveying organic food demand Paul Michels bioVista – retail panel for the organic food market Christoph Spahn Consumer Price Monitoring in Germany - ZMP-Panel of retail trade Hans-Theo Erkes A European information system for organic markets based on current panels: A critical assessment of possibilities and constraints Paul Michels The Household Budget Surveys as a source of information for the study of the consumption of organic products Antonio Puente Rodero Surveys carried out in Hungary in connection with organic products and arising problems Annamária Kovács Results of Group 4: Consumer and Retailer Level Sylwia Zakowska-Biemans, Toralf Richter, Susanne Lux, Gabriele Hempfling Group 5: Supply Balance Sheets Chair: Ulrich Hamm and Guido Recke; Rapporteur: Jessica Aschemann Supply Balance Sheets Francis Weiler Results of Group 5: Supply Balance Sheets Ulrich Hamm, Jessica Aschemann, Guido Recke Group 6: Policy Evaluation Evaluation of European organic farming policies - development of indicators employing the MEANS framework Jon Tuson and Nicolas Lampkin OECD Work on Agri-environmental indicators: Lessons for data harmonisation and policy evaluation Darryl Jones Results of Group 6: Policy Evaluation Nicolas Lampkin and Jon Tuson Summary and conclusions of the 1st EISfOM European Seminar, Berlin, April 2004 Nicolas Lampki

    EU wide analysis of the Common Agricultural Policy using spatially disaggregated data

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    Recent reforms of the Common Agricultural Policy shifted the emphasis towards competitiveness of the agricultural sector, rural development and environmentally sound farming approaches, acknowledging the considerable role agriculture plays in protecting nature and landscape. Significant progress in the evaluation of policy reform scenarios can be made if it is be possible to link existing economic and environmental models. An important methodological problem in this context is “bridging” the scales: whereas most bio-physical models work on field scale, comprehensive EU wide economic models generally work with large administrative regions. The research aims at improving integrated assessment of European policy options by developing methodologies that deliver spatially explicit agricultural data regarding crop shares and farming systems. First a procedure for estimating agricultural land use choices is developed bringing together high resolution information on crops and land cover as well as aggregate information from administrative regions. Combining a binary choice model with a Bayesian highest posterior density estimator, a statistical approach to break down land use choices from European administrative regions to about 100.000, so called Homogeneous Spatial Mapping Units is developed. The applied Bayesian method fully and transparently accounts for the prior information – mean and variance of land use shares obtained from binary choice models – when searching for consistency between the different scales. Next, an approach for the spatial allocation of farm information is developed. European wide farm information is so far only available at a rather aggregated administrative level. The suggested allocation approach adds a spatial dimension to all sample farms making it possible to aggregate farm types both to natural and to lower scale administrative regions. The allocation approach is implemented as a constrained optimization model searching for an optimal match between farm attributes and spatial characteristics subject to consistency constraints. The objective functions are derived from a Bayesian highest posterior density framework. Finally an approach to integrate spatially explicit farm information in an agricultural sector model in the context of a study on the abolition of the EU milk quota is presented. It presents an economic and environmental impact analysis using the CAPRI model, which has been updated with econometric estimates of milk quota rents from sample farms. Aggregated at EU level for the year 2020, production may increase by 5% while the price drop for raw milk is about 10%. Regions are identified where economic or environmental changes substantially exceed those at the Member State level. While regional nitrate leaching problems could be exacerbated, there is only weak evidence of an increased risk of land abandonment in marginal areas.EU weite Analyse der Gemeinsamen Agrarpolitik mittels räumlich disaggregierter Daten Die jüngsten Reformen der Gemeinsamen Agrarpolitik zielten auf eine verstärkte Förderung der Wettbewerbsfähigkeit des Agrarsektors, des ländlichen Raumes und der umweltverträglichen Landwirtschaft ab. Diese Reformen trugen damit auch der besonderen Rolle der Landwirtschaft beim Schutz von Natur und Landschaft Rechnung. Deutliche Fortschritte bei der Evaluierung von Politikreformen können erreicht werden, wenn die bestehenden ökonomischen und bio-physikalischen Modelle verknüpft würden. Ein wichtiges methodisches Problem liegt in diesem Zusammenhang in der Überbrückung von verschiedenen „Modellskalen“: Während die meisten bio-physikalischen Modelle auf der Ebene des Feldschlages arbeiten, modellieren EU-weite agrarökonomische Modelle in der Regel vergleichsweise große administrative Regionen. Der Forschungsbeitrag dieser Dissertation zielt auf eine Verbesserung der integrierten Bewertung der europäischen Agrarpolitikreformen ab. Hierfür werden Methoden entwickelt, die räumlich explizite landwirtschaftliche Informationen zu Bodennutzung und Anbausystemen liefern. Dabei wird zunächst ein Verfahren zur Abschätzung der landwirtschaftlichen Bodennutzung entwickelt. Dies geschieht durch die Verbindung hochaufgelöster Informationen zur pflanzlichen Bodennutzung mit aggregierten Daten aus administrativen Regionen. Ein statistischer Ansatz, der eine Kombination aus einem binären choice Modell mit einem Bayesian highest posterior density estimator darstellt, erlaubt die Disaggregation von regionalen Landnutzungsanteilen auf 100,000, so genannte homogene räumliche mapping units. Die angewandte Bayes'sche Methode erlaubt eine vollständige und transparente Darstellung der prior information - Mittelwert und Varianz der Landnutzungsanteile aus den binären choice Modellen - bei der Suche nach Konsistenz zwischen den verschiedenen Skalen. Nachfolgend wird ein Ansatz zur räumlichen Verteilung von landwirtschaftlichen Betrieben entwickelt, da EU-weite Betriebsinformationen nur auf einer hoch aggregierten Ebene erhältlich sind. Der entwickelte Allokationsalgorithmus ordnet jedem Testbetrieb eine räumliche Dimension zu, die es erlaubt, die Betriebe sowohl natürlichen als auch niedrigeren administrativen Skalen zu zuordnen. Dieser Allokationsalgorithmus ist als Optimierungsmodell mit Nebenbedingungen definiert, die bei der Suche nach einer optimalen Konsistenz zwischen betrieblichen Attributen und räumlichen Eigenschaften helfen. Die Zielfunktion wird von einem Bayesian highest posterior density estimator Ansatz abgeleitet. Zuletzt wird eine Methode zur Integration von räumlich expliziten Betriebsinformationen in das landwirtschaftliche Sektormodell CAPRI vorgestellt. Dieser Ansatz wurde im Rahmen einer Studie zu den wirtschaftlichen und ökologischen Auswirkungen der Abschaffung der EU-Milchquote entwickelt. Dabei wurden ökonometrische Schätzungen aus Testbetriebsdaten genutzt, um die regionalen Milchquotenrenten im CAPRI-Modell zu aktualisieren. Die Ergebnisse zeigen, aggregiert für die EU für das Jahr 2020, dass die Produktion sich um circa 5% erhöhen wird während der Preisrückgang für Rohmilch bei etwa 10% liegt. Weiterhin wurden Regionen identifiziert, in denen die wirtschaftlichen und ökologischen Veränderungen wesentlich die Änderungen auf Ebene der Mitgliedstaaten überschreiten. Regionale Nitratauswaschungsprobleme können sich in Folge der Quotenabschaffung verschärfen, wohingegen es nur schwache Hinweise auf eine Zunahme des Brachlandes in marginalen Gebieten gibt

    Analysis of farmers’ stated risk using lotteries and their perceptions of climate change in the Northwest of Mexico

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    Risk attitudes are relevant factors affecting production, management and investment decisions at the farm level. They are key factors related to farmers’ attitudes towards the environment and climate change. Several methodological approaches, which were considered to be preferable for measuring the level of risk of an economic agent, ranging from highly risk-tolerant to highly risk-averse attitudes, are available. The Multiple Price List (MPL) method is one of the stated approaches that is gaining relevance. In this study, we apply the MPL and relate the risk outcomes to farmers’ socio-economic characteristics and their perceptions of the environment and climate change. Data were collected using a face-to-face survey, carried out with a group of 370 farmers of an irrigation district, located in the northwest of Mexico. The results showed a risk level of about 0.32, according to the Constant Relative Risk Aversion (CRRA) coefficient, locating farmers of the region in a risk-averse group. The heterogeneity analysis showed that the socioeconomic factors and the perceptions of climate change are related to the farmers´ stated risk level. Farmers who are young women, with a tendency to use public support for structural investment, were shown to be risk-tolerant. Farmers considered floods, hail, diseases, pests, and weed growth incidences to be the most frequent weather patterns in the region.info:eu-repo/semantics/publishedVersio

    Investigation into the bio-physical constraints on farmer turn-out-date decisions using remote sensing and meteorological data.

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    ThesisDoctoral thesisAccepted versionGrass is the most common landcover in Ireland and covers a bigger percentage (52%) of the country than any other in Europe. Grass as fodder is Ireland’s most important crop and is the foundation of its most important indigenous industry, agriculture. Yet knowledge of its distribution, performance and yield is scant. How grass is nationally, on a farm by farm, year by year basis managed is not known. In this thesis the gaps in knowledge about grassland performance across Ireland are presented along with arguments on why these knowledge gaps should be closed. As an example the need for high spatial resolution animal stocking rate data in European temperate grassland systems is shown. The effect of high stocking density on grass management is most apparent early in the growing season, and a 250m scale characterization of early spring vegetation growth from 2003-2012, based on MODIS NDVI time series products, is constructed. The average rate of growth is determined as a simple linear model for each pixel, using only the highest quality data for the period. These decadal spring growth model coefficients, start of season cover and growth rate, are regressed against log of stocking rate (r2 19 = 0.75, p<0.001). This model stocking rate is used to create a map of grassland use intensity in Ireland, which, when tested against an independent set of stocking data, is shown to be successful with an RMSE of 0.13 Livestock Unit/ha for a range of stocking densities from 0.1 to 3.3 Livestock Unit/ha. This model provides the first validated high resolution approach to mapping stocking rates in intensively managed European grassland systems. There is a demonstrated a need for a system to estimate current growing conditions. Using the spring growth model constructed for estimating stocking density a new style of grass growth progress anomaly map in the time-domain was developed. Using the developed satellite dataset 1 and 12 years of ground climate station data in Ireland, NDVI was modelled against time as a proxy for grass growth This model is the reference for estimating current seasonal progress of grass growth against a ten year average. The model is developed to estimate Seasonal Progress Anomalies in the Time domain (SPAT), giving a result in terms of “days behind” and “days ahead” of the norm. SPAT estimates for 2012 and 2013 are compared to ground based estimates from 30 climate stations and have a correlation coefficient of 0.897 and RMSE of 15days. The method can successfully map current grass growth trends compared to the average and present this information to the farmer in simple everyday language. This is understood by the author to be the first validated growth anomaly service, and the first for intensive European grasslands. The decisions on when to turn out cattle (the turn out date (TOD)) from winter housing to spring grazing is an important one on Irish dairy farms which has significant impacts on operating costs on the farm. To examine the relationship of TOD to conditions, the National Farm Survey (NFS) of Ireland database was geocoded and the data on turn out dates from 199 farms across Ireland over five years was used. A fixed effects linear panel data model was employed to explore the association between TOD and conditions, as it allows for unobserved variation between farmers to be ignored in favour of modelling the variance year on year. The environmental variables used in the analysis account for 38% of the variance in the turn out dates on farms nationwide. National seasonal conditions dominate over local variation, and for every week earlier grass grows in spring, farmers gain 3.7 days in grazing season but ignore 3.3 days of growth that could have been used. Every 100mm extra rain in spring means TOD is a day later and every dry day leads to turn out being half a day earlier. A well-drained soil makes TOD 2.5 days earlier compared to a poorly drained soil and TOD gets a day later for every 16km north form the south coast. This work demonstrates that precision agriculture 1 driven by optical and radar satellite data is closer to being a reality in Europe driven by enormous amounts of free imagery from NASA and the ESA Sentinel programs coupled with open source meteorological data and models and new developments in data analytics
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