Volume 118 - Issue 3

Societal expectations about agricultural production are changing. There are increased demands on issues such as food safety, animal welfare and the impact of agriculture on the environment (land, water and air). These changes have been refl ected in the European Union’s (EU) Common Agricultural Policy (CAP), but information on these issues is lacking and this complicates the required evaluation of policies. The EU Framework 7 project FLINT tries to close this gap by analysing the feasibility of collecting data on these new topics. FLINT has established a data infrastructure with up-to-date farm-level indicators for the monitoring and evaluation of the CAP. The project created a pilot network of more than 1,000 farms to collect a set of sustainability indicators at farm level. The pilot represents farm diversity at EU level, including the different administrative environments in the Member States. This paper sets out the context and the main contributions of the project.

In recent decades, the concept of sustainability has become increasingly prominent in agricultural policy debates. This has led more and more stakeholders to pay attention to the questions of monitoring and evaluation of agricultural practices, and raised the question of appropriate indicators to assess sustainability aspects of given practices. We provide here a review of indicators of sustainability for agriculture. We describe sustainability indicators used in the literature following the typology based on the three sustainability pillars: environmental, economic and social. The literature review shows that the environmental pillar has undergone an ‘indicator explosion’, due to the multitude of themes covered and the attention given by society to this dimension of sustainability. By contrast, economic indicators target a relatively small number of themes. Social indicators typically cover two main themes: sustainability relating to the farming community and sustainability relating to society as a whole. The measurement of these social indicators is challenging as they are often qualitative and may therefore be considered subjective. Careful attention should be given to the choice of indicators, since the data measured will infl uence the calculation of that indicator and therefore the outcome of the analysis. It should first be decided whether individual or...

Increased attention for sustainability in agricultural production within the food sector has enhanced the need for farm-level information. This article aims to explore stakeholders’ perceptions of sustainability measurement at farm level in an established monitoring system. Qualitative research, including discussion groups and semi-structured interviews in nine European countries, identifies existing divergences in perceptions, especially for those indicators not expected to be used for farm-level decision making. The perception of feasibility and usefulness of an indicator is determined by (a) indicators’ intrinsic attributes, (b) the measurement system in which it is inserted, (c) farm characteristics and (d) farmers’ attitudes toward the measurement. Identifying stakeholders’ perceptions could help to improve the discussion between researchers and users in the selection, communication and use of sustainability information along the agricultural sector.

The European Farm Accountancy Data Network (FADN) collects detailed financial economic information on a sample of farms in Europe. These data are used intensively for the evaluation of the European Union’s Common Agricultural Policy. Owing to changes in policies, there is a need for a broader set of farm level data, especially on the sustainability performance of farms. This paper describes the different types of FADN systems in Europe and evaluates how these types affect the feasibility of collecting sustainability data. In addition to a theoretical evaluation, the practical experiences of collecting sustainability data on more than 1,000 farms in Europe are described. The paper concludes with a discussion on the advantages and challenges of extending the scope of FADN data collection with sustainability data.

This paper examines the use of extension services by farm households across eight European Union (EU) Member States, exploring the type of extension service engaged with, the degree of engagement and the type of information sought. The impact of extension on economic, environmental and social sustainability is also considered. European data utilised are those collected from a pilot sample of 820 households in 2015/2016 as part of the EU Framework 7 project FLINT, from which the Irish results are incorporated further with Irish Farm Accountancy Data Network data. The results outline the key contrasts across the countries investigated and suggest that the degree to which households engage with extension services is primarily infl uenced by national policies. In addition, this analysis indicates that the extent of this engagement has implications for sustainability at the farm level. The final conclusions and policy recommendations in this paper support the development of a large-scale version of the FLINT pilot survey.

Given the increased attention to risk management in the European Union’s (EU) Common Agricultural Policy (CAP), it is important to monitor and evaluate the rates of adoption by farmers and their determinants over time. Current European agricultural statistics (Farm Accountancy Data Network) capture few indicators that assess such strategies, but complementing data collected during the EU Framework 7 project FLINT have allowed the adoption of risk management strategies and the determinants of farmers’ preference for complementary or substitute instruments to be assessed. Adoption rates of risk management instruments such as insurance contracts, price contracts, off-farm income, other types risk of reduction measures and other gainful activities vary signifi cantly across EU Member States and farming types. Econometric analysis indicates that larger farms more often adopt crop insurance, occupational accident insurance, price contracts and diversifi cation but are less likely to adopt credit avoidance and off-farm employment (at a signifi cance level of 1 per cent). For policy analyses these indicators are a step forward for the determination of the net impacts and establishment of counterfactuals in the long term (i.e. time series encompassing also adverse years) for measuring the impact of the CAP at farm level.

The measurement of farm economic sustainability has received intermittent academic interest in recent times, while the conceptual discussions are often quite limited. Moreover, this concept receives more attention at periods of difficulty for the sector. The measurement of farm viability is an important precondition to enrich these discussions. Therefore, it is necessary to develop more comprehensive and detailed measurement techniques to provide more clarity on viability and vulnerability levels in the sector. This paper refocuses attention on this issue, using a pilot dataset collected at farm level across a range of EU Member States which facilitates the assessment of an additional category of viability, namely that of economically sustainable farms, i.e. farms that are economically vulnerable but which are deemed sustainable by the presence of off-farm income. Differences in viability and economic sustainability across the eight surveyed Member States are shown. The analysis is sensitive to the factors included in the measurement of viability as well as to the threshold income used to define viability. Although this is a pilot study, it enhances our understanding of the factors affecting cross-country evaluation of viability and sustainability, and the policy instruments that could improve viability levels.

Innovation and adoption of innovation are considered key indicators of competitiveness and sustainability. Analysing data from 821 farms from eight Member States of the European Union in the frame of the EU Framework 7 project FLINT, this study provides an insight into the different adoption rates of five types of innovation in agriculture across Europe and suggests the potential effects of different factors, including farm type and farm size, subsidies and age, on farmers’ decision to innovate.