Suchergebnisse

The aim of this article is to investigate the relationship between size and farm growth. The existing theories of the association between size and farm growth give mixed results by countries and over time. This paper pursues a twofold objective: on one hand, to test the validity of Gibrat's Law for French, Hungarian and Slovenian specialized dairy and crop farms during the pre- and post-accession period to the European Union membership. Dairy and crops farms are prevailing in the farming structure of these countries. Using Farm Accountancy Data Network datasets makes it necessary to avoid biases due to heterogeneous structures across the farming systems. Thus we use quantile regressions to control for farm size related heterogeneity in the samples. On the other hand, the main novelty of this paper is the comparative analysis of the relationship between farm size and farm growth between transition Hungarian and Slovenian and non-transition French farming sectors, characterized by rather different farm structures. The results reject the validity of Gibrat's Law for crop farms in Hungary and to a lesser extent in France, and for French and Slovenian dairy farms. We provide evidence that smaller farms grew faster than larger ones over the studied period 2001-2007 for France, 2001-2008 for Hungary, and 2004-2008 for Slovenia. Conversely, the results for Slovenia suggest that the rate of growth of crop farms in terms of its land is independent from its size.

The aim of this article is to investigate the relationship between size and farm growth. The existing theories of the association between size and farm growth give mixed results by countries and over time. This paper pursues a twofold objective: on one hand, to test the validity of Gibrat's Law for French, Hungarian and Slovenian specialized dairy and crop farms during the pre- and post-accession period to the European Union membership. Dairy and crops farms are prevailing in the farming structure of these countries. Using Farm Accountancy Data Network datasets makes it necessary to avoid biases due to heterogeneous structures across the farming systems. Thus we use quantile regressions to control for farm size related heterogeneity in the samples. On the other hand, the main novelty of this paper is the comparative analysis of the relationship between farm size and farm growth between transition Hungarian and Slovenian and non-transition French farming sectors, characterized by rather different farm structures. The results reject the validity of Gibrat's Law for crop farms in Hungary and to a lesser extent in France, and for French and Slovenian dairy farms. We provide evidence that smaller farms grew faster than larger ones over the studied period 2001-2007 for France, 2001-2008 for Hungary, and 2004-2008 for Slovenia. Conversely, the results for Slovenia suggest that the rate of growth of crop farms in terms of its land is independent from its size.

The main purpose of this deliverable is to use technical efficiency scores obtained with three distinct methods, Stochastic Frontier Analysis (SFA), Data Envelopment Analysis (DEA), Operational Competitiveness Ranking Analysis (OCRA), based on national Farm Accountancy Data Network (FADN) data, in order to analyse the impact of European Union (EU) accession and the influence of farm classification, more precisely farm type, upon the performance on field crop and dairy farms in three New Member States (NMS), Bulgaria, Estonia and Hungary We provide theoretical and empirical evidence that farm classification is subject for empirical analysis, because using FADN and conceptual (e.g.Hill type) typology may result in considerably different farm structures. The main outcome of this research is that individual farms are not equivalent to family farms as usually assumed in previous research. We find that average size of individual farms is considerably higher than of family farms.

International audience ; In this paper we analyse and compare various efficiency indicators for a number of European Union (EU) countries: Belgium, Estonia, France, Germany, Hungary, Italy, The Netherlands and Sweden. The availability of long period datasets between 1990 and 2006, allow us to concentrate on the long time trends in technical efficiency especially in Old Member States. This study is the first which may provide a comprehensive overview on the development in farm level efficiency across eight European countries. Our main results are the following. Generally, all countries have relatively high levels of mean technical efficiency ranging from 0.72 to 0.92 for both field crops and dairy farms. Interestingly the majority of countries have better performance in dairy sectors in terms of higher levels of mean efficiency than in field crop production. A slightly decreasing trend however may be observed for all countries. Technical Efficiency estimates are largely in line with those obtained by previous studies. Stability analysis revealed that in average 60% of farms maintain their efficiency ranking in two consecutive years, whilst 20% improve and 20% worsen their positions for all countries. However, these ratios slightly fluctuate around these values for one year to next year. Mobility analysis ranks countries according to the mobility of SFA scores within the distribution. Farms in New Member States are more mobile than those in EU15. Total productivity changes are analysed in two steps. First, we do not find a definite trend in total factor productivity changes. Second, we address the question whether total factor productivity changes converge or diverge over time. Using panel unit root tests our estimations reveal a convergence of productivity across old EU member countries during analysed period. Finally, we decompose the total factor productivity changes into its main elements. Field crop farm indicators generally present significantly higher volatility than dairy farms. Random effect panel ...

This deliverable investigates the employment effects of ecological farming by analysing both the differences in the intensity of labour use and rewards to skills. It contributes to one of the main outcomes/achievements of the LIFT project, i.e. to "identify the sources of performance and sustainability differences between farms of different types, size and output complexity as observed in the landscape of the European Union (EU)". It is based on collaborative research on Task 3.5 'Employment effects of ecological farming at the farm level' of LIFT between UNIKENT (England) (Task Leader), INRAE (France), DEMETER (Greece), MTA KRTK (Hungary) and IRWiR PAN (Poland). The analyses reported consider the differences between farms on a scale from the most conventional farming systems to the most ecological as measured by the intensities of use of external inputs and labour, the receipt of agri-environmental payments (AEP), capital and involvement in organic production. This approach was used since, at the time of working on the deliverable the LIFT typology protocol on how to classify farms according to the different degrees of adoption of ecological approaches to farming has not been completed. The approach nevertheless makes use of the LIFT conceptual typology in Deliverable 1.1 (Rega et al., 2018). In the analysis, intensity of labour use is studied as a function of farming inputs (fuel, fertiliser, crop protection chemicals), capital and AEP. Dependent and independent variables have been standardised by dividing them by the output value and the resulting ratios named intensities of use. The standardisation by dividing by the overall output value was done to remove the effect of different farm sizes and to focus the discussion on the way output is produced, rather than how land is used. In order to reduce the impact of quality differences in the inputs, we make use of monetary value of input used to take account of quality differences that would be reflected in price differentials. Five EU Member States (MSs) are ...

The deliverable D6.1 of the LIFT project explores what types of discourses are used in six European Union (EU) member states' Rural Development Programs (RDP) and other agricultural policy documents and how they incorporate ecological approaches across three Common Agricultural Policy (CAP) periods. This multiple case study highlights similarities and differences in the dominant discourses as emerging from national policy documents in the following selected EU member states: France, Germany (Bavaria), Hungary, Poland, Romania and Sweden. It also demonstrates how discourse analysis can be used to gain understanding about the dominant discourses expressed in these documents in relation to how ecological approaches are defined, the policy rationale for encouraging ecological approaches and the expected consequences of doing so. Conceptually, we focused on two types of discourses identified from the literature: 1) the three CAP discourses: i) neomercantilism; ii) neoliberalism and iii) multifunctionality, and 2) the five socio-political discourses of Rural Development (RD): iv) agri-ruralist, v) hedonist, vi) utilitarian, vii) nature conservation and viii) community sustainability. These types of discourses were together integrated in a model, where each policy discourse depicts agriculture as accomplishing a specific function. The theoretical framework is grounded within a political economy perspective. This means that policy develops because of confrontation between different concerned agents with different interest, pushing for different objectives. The state acts as an intermediary between these agents and aims at ensuring consensus and maintenance of agreement. Policy documents are therefore often the result of competing discourses and contradicting policy objectives. Across EU member states, the results show that ecological approaches are mainly depicted with the multifunctionality discourse with two dominating sub-discourses of nature conservation and agri-ruralism. Nevertheless, we observe an increase in the ...

In light of the ambitions of the European Union (EU) to achieve an ecological transition of its agricultural sector it is crucial to assess and continuously monitor (i) the uptake of main ecological approaches by farms and (ii) associated effects on farm performance, considering all sustainability dimensions (economic, environmental, social) jointly. Given these needs, in the present deliverable D5.1 of the LIFT project, we develop a novel indicator system, which combines the LIFT farm typology and farm performance data, covering all sustainability dimensions. The approach compares performance of farms in five ecological groups (referred to as ecological farming approaches or ecological farming systems) from the LIFT farm typology (Conservation Agriculture, Low-Input farming, Integrated/Circular farming, Organic farming, Agroecology) as well as possible combinations of these groups with a less ecological group, referred to as Standard farming. This allows us to depict whether ecological farms perform differently or have different trade-offs and synergies than standard farms. Based on this system, we carry out a farm sustainability performance assessment with the two main data sources in the LIFT project, namely Farm Accountancy Data Network (FADN) data and data from the LIFT large-scale farmer survey, covering main farm types present in the European Union (EU) in several case study regions/countries. Additionally, we present in-depth analyses of further specific aspects, namely (i) the extension of the developed indicator framework to bio-economic models, (ii) the integration of the consumption and provision of ecosystem services into the developed indicator system through composite agri-environmental performance (AEP) indicators, derived from the body of secondary literature and region-specific stakeholder input, and (iii) working conditions and employment on farms in the context of an ecological transition. Overall, our results show the importance of considering trade-offs and synergies both within and between ...

This document presents the results of Task 3.2 (farm technical-economic performance) in workpackage (WP) 3 (farm performance of ecological agriculture) of the LIFT project. The overall aim of Task 3.2 is to assess and compare technical-economic farm performance across the European Union (EU) depending on the degree of ecological approaches adopted by farms and analyse drivers, affecting their performance. This requires an approach, which allows to consider regional specifics, while still allowing comparisons between different regions and countries. The deliverable thus consists of several academic papers, focussing on a range of different case studies, applying a wide range of methods, which can most generally be divided into empirical econometric approaches and bio-economic models. At the same time, all case studies follow a similar structure and include some common elements in terms of the applied methods, in particular a set of common indicators of technical-economic farm performance was implemented in several papers. Various approaches to differentiate farms according to the degree of ecological approaches adopted were explored, including the LIFT farm typology developed in WP1 and other strategies. Overall, our results show that the wide variety of farm types and biophysical, socio-economic and political framework conditions present in the EU matter: results of comparing technical-economic farm performance depending on the degree of ecological approaches adopted, as well as with respect to drivers of farm technical-economic performance, are heterogenous and vary between the different analyses. Therefore, this heterogeneity needs to be considered by policy makers and can most likely best be addressed by providing a policy framework, which provides the necessary flexibility to adjust measures to region-specific framework conditions in order to foster economic viability of farms in the context of an ecological transition of EU agriculture. Building on the results of this deliverable and the other deliverables ...