Farm Accountancy Data Network Research Articles

Rizik dohotka u hrvatskoj hortikulturi i osiguranje dohotka

Due to the lack of reliable longitudinal data, farm income and income trends haven’t been much analysed in Croatia, specifically among horticultural producers. Based on Croatian Farm Accountancy Data Network (FADN), the goal of this paper is to research the income of all farms in comparison to horticultural farms. In addition, paper tests farm’s eligibility for Income Stabilization Tool (IST) compensation. Objectives of the paper are: (1) analysis of farm income in the period 2014-2017 for all farms and specifically for horticultural farms, and (2) analyse how many horticultural farms have potential for IST compensation. For the second objective, we prepared scenarios of annual income drop of 10%, 20%, and 30% of the three-year average income. Scenarios are shown for groups - wine, orchard, and olive farms (calculated group index) and for individual farms (calculated farm index). Results show that horticultural farms’ income is on the similar level to the data for all the farms in FADN. The group index calculation compared to farm index income calculation shows a higher number of farms eligible for IST. The paper might serve as a basis for the introduction of IST in Croatian agriculture.

Sustainability and competitiveness in farms: An evidence of Lazio region agriculture through FADN data analysis

The new legislative proposals related to the Common Agricultural Policy (CAP) reform 2021-2027 aim to promote a sustainable and competitive agricultural sector. The new CAP supports agriculture in making a much stronger contribution to climate, biodiversity, environment and improving farms' competitiveness in the agri-food sector, in a European context.The importance of a strong focus on results and performance in the CAP legislation requires a continuous assessment and monitoring of the effectiveness of the measures adopted in the Rural Development Programs (RDP) with respect to the specific goals set during the cap program. In order to assess the progress in improving the competitiveness and sustainability of the agri-food sector in reaching their targets and the objectives of the CAP, the need arises to investigate whether the RDP measures contribute to supporting the transition towards sustainable agriculture, to the competitiveness of the agri-food sector and to a balanced development of the rural areas. In this new legislative framework, where it becomes important to evaluate whether the CAP provides a much stronger contribution to achieving the specific objectives, our paper aims to describe agricultural sector in the Lazio region and to analyze the effects, in terms of sustainability and competitiveness, of the measures approved by RDP 2014-2020, which have almost expired. In particular, we provide a comparative analysis of the data collected by the Farm Accountancy Data Network (FADN), focusing on two different periods: one prior to the last programming and one referring to the latest available data. The collected data refer to farms, regarding their structural, economic, financial and patrimonial characteristics, as well as variables that describe attitudes and behaviour towards the environment. A multivariate analysis (clustering) is applied; it focuses on explorative factor analysis based on principal components, in order to identify homogeneous groups of farms with sustainability and competitiveness and identify similar characteristics and potential for development trajectories. The results found that farms are moving towards more sustainable and multifunctional development paths. The assessment of EU goals for social, environmental, and economic sustainability in agriculture and rural areas are a basis for discussion among public decisionmakers involved in the reforming process of the explanatory measures of the new strategic objectives of the post-2020 CAP.Our results can offer a contribution to meeting the current challenges posed by the EU to ensure a smooth transition to the future CAP program. Major challenges that raise policy debate on the considerable potential of the FADN for assessing sustainability and farm competitiveness in the EU framework which places strong emphasis on results and performance.

Modeling change in the ratio of water irrigation costs to farm incomes under various scenarios with integrated FADN and administrative data

The Water Framework Directive 2000/60/CE (WFD) of 2000 was issued by the European Union (EU) to prevent water deterioration and promote its restoration. It introduced a water pricing policy in the agricultural sector that is based on a ‘polluter-pays' principle.To date, some Member States have yet to comply with the pricing requirement for two main reasons: water cost estimates, as defined by the WFD, are particularly complex and difficult in the agricultural sector and farmers in marginal economic and environmental contexts may be unable to bear higher water costs.In Italy, water services are managed by regional administrations that also set irrigation water prices. This research estimated the effect of changes in irrigation water costs borne by farmers on farm incomes in a case study in the Aosta Valley Region where extensive farming is practice in a significantly naturallydisadvantage area. The analysis was modeled using four cost scenarios with economic data from the Farm Accountancy Data Network (FADN) integrated with irrigation water cost data provided by a regional administrative database. Estimated water costs averaged 2.65% and 1.06% of farm incomes, depending on the presence or absence of regional subsidies. Water costs represented higher income proportions on specialized grazing livestock farms, which is the predominant type of farming in Aosta Valley. These results raise concerns for WFD implementation, in particular, in mountain and agriculturallydisadvantaged areas with extensive and less-profitable farming.

Economic characterization of irrigated and livestock farms in The Po River Basin District

This article highlights the potential for collecting and processing territorial data in order to facilitate planning and programming that respond to real local problems and include the political and regulatory framework in force. A case study is explored that involves the joint use of two databases with institutional functions: the Farm Accountancy Data Network (FADN) and the National Information System for Water Management in Agriculture (SIGRIAN). Both databases are managed by the Council for Agricultural Research and Economics (CREA). Those data were used to calculate economic-structural indicators for irrigated and livestock farms located in the Po River Basin District and to run the socioeconomic analysis required to update the Water Management Plan. The updating of plans is governed by the Water Framework Directive (Directive 2000/60/EC), which establishes the community framework for water and requires all Member States to review and update their Plan every six years. The first update deadline was December 2015 and the second one will be December 2021. The integrated use of two databases made it possible to identify farms according to two types of irrigation: collective or self-supplied. With collective irrigation (Irrigation Water Service), the farm is a user of a Local Agency for Water Management (LAWM) that collects and distributes irrigation water. With self-supplied irrigation, the individual farmers collect and distribute water themself. The analysis carried out demonstrates the need and opportunity to develop coordinated data collection and management systems, thereby strengthening and refining the monitoring and programming of water use in line with the real needs of the territory.

Guest Editorial. Current use and new perspectives for the Farm Accountancy Data Network

Guest Editorial. Current use and new perspectives for the Farm Accountancy Data Network

Procjena tehničke učinkovitosti mađarskih i hrvatskih stočarskih sektora primjenom DEA modela na FADN podacima

The different sectors of the livestock industry play an important role in meeting the increasing demand for animal products in both Hungary and Croatia. The general objective of this study was to investigate and compare the efficiency of the livestock sectors in Croatia and Hungary using the Data Envelopment Analysis method. In this paper, the technical efficiency of the dairy, beef, broiler, sheep and goat, and pig sectors from 2014 to 2017 is investigated based on the Farm Accountancy Data Network database. This paper compared farms of different size classes based on the Standard Production Value for more detailed insights. Among the five main livestock sectors, Hungary performs better in terms of farm technical efficiency in the dairy and beef sectors, while Croatia has higher efficiency scores in the sheep sector. The performances in the pig and broiler sectors are almost the same in both countries. Moreover, in the Hungarian poultry, pig, sheep and goat sectors and the Croatian dairy, beef and pig sectors, the technical efficiency of small-sized farms is better than that of medium-sized farms.

The Role of Neighborhood Effects on Investing Dairy Farms

For the traditionally small-scaled Swiss agriculture, large economies of scale exist in dairy farming. Farm expansion is typically linked to a barn investment, but the opportunities for expanding the necessary acreage are limited. To enable an investing farm to expand its acreage, neighboring farms must shrink or phase out. Hence, the question arises how neighboring farms affect investing farms. To address this farm management question, we used a set of Farm Accountancy Data Network data and government data on subsidized projects. We combined this dataset with agricultural census data to assess the concentration of agricultural land as well as the number of subsidized investments within the municipality of an investing farm. By means of random-effects models for agricultural income per family working unit on the one side and herd size change on the other, we found two effects of neighborhood effects. A high number of subsidized projects and a high concentration of land (Gini coefficient) limited the growth in herd size due to scarcity of available land. At the same time, neighborhood positively influenced the management, leading to a higher agricultural income per family working unit. The results illustrate that an extension of the Farm Accountancy Data Network data, which in itself is extensive, can further help to address specific research questions.

How to Increase Productivity in Kosovo Agriculture: A Story of Size and Technical Efficiency

Kosovo is struggling with low productivity in agriculture and an overwhelming majority of small farms. This paper analyses changes in the factor mix that can bring the highest increase in marginal productivity, employing a non-parametric quantile regression based on Farm Accountancy Data Network (FADN) data. Two different quantile regressions are estimated, for the median 0.5th quantile, describing the nature of the input-output relationship for a ‘typical’ farm and for the 0.8th conditional quantile, characterising a reasonably ‘efficient’ farm. The results show that optimal marginal productivity can be achieved by ‘typical’ farms by increase in farm size but it requires drastic changes in factors which are currently hardly feasible in Kosovo (e.g. 3-4 FTEs family labour, 0.5 to 1.8 hired). For an efficient farm, the optimal marginal productivity is achieved at lower values of inputs. This suggests that productivity enhancements can be obtained by a careful balance of both efficiency and scale augmentation measures.

The Competitiveness of Agriculture in EU Member States According to the Competitiveness Pyramid Model

Agriculture in the European Union is highly differentiated, and one of the objectives of the Common Agricultural Policy is to improve agricultural competitiveness. Therefore, surveys regarding the competitiveness of agriculture and grouping countries of the European Union (EU) according to similar characteristics of agriculture are very valuable. They help make strategic decisions concerning the agricultural sector. This paper aims to evaluate the agricultural competitiveness of EU member states in 2010–2019. Data used is derived from the Eurostat and FADN (Farm Accountancy Data Network). The study employed a competitiveness pyramid model based on two groups of factors–competitiveness sources (bottom of the pyramid) and competitiveness effects. Partial components allocated to the groups mentioned above of factors were used to calculate a synthetic measure to determine the level of agricultural competitiveness in respective countries. The studies revealed that EU agriculture varies both in terms of resources and relationships between production factors, as well as the efficiency of their utilization. A clear difference in the level of competitiveness occurred between old and new member states, although some new countries ranked relatively high in terms of competitiveness sources (Czechia and Poland). Belgium scored highest for the synthetic measure of agricultural competitiveness in 2010–2019, and Cyprus had the lowest. It was demonstrated that human resources were of utmost importance in the structure of competitiveness sources. In turn, the average holding area determined the management conditions to the highest extent.

Assessment of Farm Accountancy Data Network System in Croatia

Croatia is the newest member of the EU Farm Accountancy Data Network (FADN). So far, no comprehensive evaluation of the national FADN system has been conducted, and this study based on a survey of staff involved and a desktop analysis was conducted to fill this gap. The three main elements of the Croatian FADN system are the National FADN Committee, the Ministry of Agriculture as Liaison Agency (LA) and the Croatian Bureau for statistics. All FADN survey activities are carried out by LA and the main burden of data collection lies with the data collectors and the farms. The system operates in accordance with relevant EU legislation and currently its main objective appears to be the fulfilment of its obligations to the FADN network. Other benefits like analysis of CAP measures etc. are not yet exploited. The main challenges are further development of quality assurance systems, the motivation of staff and farms to participate, the increased use of FADN data, and the expected changes in transformation of the FADN into the sustainability data network (FSDN). Croatia will successfully meet these challenges if it strengthens its capacity for FADN research and data analysis and establishes an effective quality assurance system.

AGRICULTURE AND SCIENCE COLLABORATION: THE CASE OF ŁÓDŹ VOIVODESHIP (POLAND)

The article aims to evaluate the cooperation of Polish farmers from Łódź Voivodeship with science and other farmers in the field of implementing innovation in farms. Paper and Pencil Interview (PAPI) method was used. The analysis covers 150 Polish farms located in the Łódź Voivodeship. The farms for the study were selected from the Polish FADN (Farm Accountancy Data Network) sample. The study was made in 2018. The conducted research has proved that interest in scientific achievements depends on the innovativeness of farms. The cooperation between Polish farmers from Łódź Voivodeship in the field of innovation activity do not differ in terms of their farming type. A consequence of the selection of farms is the lack of the ability to generalize the results to the entire population of farms in the Łódź Voivodeship. The added value of the analysis is the presentation of the results in terms of farm innovation.

Determinants of Fixed Asset Investment in the Polish Farms

The aim of this study was to determine the factors affecting the level of investment activity of agricultural producers in Poland. Detailed studies included 4309 farms that kept accounts within the Farm Accountancy Data Network (FADN) accounting system in the years 2010–2018. The study uses Person’s linear correlation method, the multiple correlation method, and regression analysis. For the regression analysis, both static and dynamic models were applied. The level of expenditure on agricultural investment varied in the surveyed households and showed an upward trend during the years 2010–2018. Studies have shown that the investment activity of Polish farms largely depends on the possibility of raising funds from European Union programs dedicated, inter alia, to the development of agricultural holdings. The regression analysis demonstrated that the principal factors affecting the level of agricultural investment include: the amount of long-term liabilities, the family income of the farm, and the amount of investment subsidies. Preferential loans are an important parameter in a dynamic investment model. This study suggests that agricultural policy factors should be taken into account to ensure the appropriate development of Polish farms.

Farm to Fork strategy and restrictions on the use of chemical inputs: Impacts on the various types of farming and territories of Italy

This study evaluates the impacts of reduction in chemical inputs use, as defined to the Farm to Fork strategy, on the Italian agricultural sector based on current production practices and technologies, as well as market and political framework. The impacts are evaluated in terms of some economic, environmental and social indicators, and are shown and discussed both geographic area and types of farming. The analysis was conducted on all Farm Accountancy Data Network (FADN) sample of Italian farms in various years, about 40,000 farms, by using the AGRITALIM model.The main results show an improvement in environmental sustainability of agricultural production in terms of lower use of chemical. Negative socio-economic and productive impacts are observed overall in the national territory, but some areas are more affected. The reduction of income could especially affect some types of farming and smaller farms.In conclusion, the Farm to Fork strategy could be a fundamental impetus to review some failings and weaknesses of European agriculture. Our analysis shows that targeted and forward-looking interventions are especially important for some types of farming, production sectors and territories. New research is needed to support the choices of stakeholders regarding policy support and innovation in agriculture. Political interventions are needed to incentivize farmers to adopt environmentally friendly agricultural practices and limit income losses. Genetic and technological innovations could play a fundamental role in limiting the reductions of agricultural production and modernizing farms.

Off-farm income and direct payments—an indispensable diversification strategy of Swiss farmers

Abstract Following the theory of a farm household model, the relations between farm and farmer characteristics, including two different kinds of direct payments, and their effects on the off-farm labour allocation decisions of farm operators were analysed. Swiss farm accountancy data network (FADN) data of the years 2017, 2018, and 2019 for the whole sample and two different income groups were used to model both off-farm labour participation and supply decisions. The results show that diversification into off-farm employment is a highly relevant strategy of Swiss farmers and that direct payments are a complementary income source. Above a certain level, biodiversity payments show a substitution effect, meaning that off-farm participation is reduced. Off-farm labour supply is related not to direct payments but to production type and technology, with dairy and organic farmers having spent fewer days engaging in off-farm employment. Education positively correlates to off-farm labour participation. Even though off-farm income and direct payments are an indispensable income source for Swiss farmers, income-related policy goals cannot be considered achieved in terms of either farm or household income. Whether public money would be better spent on education than on unprofitable farm businesses should be analysed in future studies.

The impact of geographical indications on farm incomes in the EU olives and wine sector

PurposeGeographical indications (GIs) are expected to stimulate rural development by increasing the viability and resilience of farms in disadvantaged and remote areas. However, little quantitative evidence exists to support this expectation. This study fills this knowledge gap by quantitatively analyzing the effect of GI adoption on farm incomes in the EU olives and wine sectors.Design/methodology/approachThe analysis uses data from the Farm Accountancy Data Network and EUROSTAT and an endogenous switching regression model to analyze the impact of GI adoption on farm incomes for specialized quality wine and olives producers in the year 2014.FindingsThe results show that GI adoption significantly improves farm incomes in both the olives and the wine sector.Research limitations/implicationsThe research uses data from the farm accountancy data network (FADN). This is seen as a limitation of the analysis. The research raises some concerns about the appropriateness of FADN for the assessment of farmers' involvement in food quality schemes and a reconsideration of FADN as a tool for farm performance analysis is advised.Originality/valueThis is one of few quantitative studies of the impact of geographical indications on farm performance. Furthermore, it gives insights into the mechanisms by which GI can affect farm incomes.

Modeling heterogeneous technologies in the presence of sample selection: The case of dairy farms and the adoption of agri‐environmental schemes in France

AbstractIn this article, we assess farms’ technical efficiency accounting for their production heterogeneity and correcting for the potential endogeneity associated with the adoption of Common Agricultural Policy (CAP) agri‐environmental schemes (AESs). We estimate a first‐step selection probit model. In a second step we estimate the latent class stochastic frontier model (LCSFM) separately on each of the two sub‐samples, the AESs adopters and the AESs non‐adopters. We also account for heteroscedasticity in the estimation of inefficiency effects in the LCSFM within each sub‐sample. The application is to Farm Accountancy Data Network (FADN) dairy farms in France during 2002–2016. We identify one class with intensive technology and one class with extensive technology for each of the two sub‐samples. The investigation of inefficiency effects shows that modeling production heterogeneity could help better target the CAP, since the relationship between operational subsidies and farms' efficiency differs depending on whether or not production heterogeneity is accounted for.

Yields variability as a determinant of production risk in agriculture

Agricultural activity is exposed to a number of adverse external factors known as production risks, which affect the quantity and value of production. One of the measures of production risk assessment in crops production is yields variability. The aim of the study is to determine the scope of the variability of the yields of selected agricultural crops on the basis of various sources of data covering the years 2015–2019. The study uses aggregated official statistics data compiled by Statistics Poland, published in the Statistical Yearbook of Agriculture, and individual data from the Polish Farm Accountancy Data Network (FADN), which takes into account commercial farms. The analysis of the differences in crops variability determined on the basis of different sources of information was carried out using basic statistical parameters: the arithmetic mean, standard deviation and the coefficient of variation. The research shows that the variability of yields in Poland depends not only on the type of crops, but also on the location of the production. Moreover, it indicates a greater stability of crops production among commercial farms when compared with farms in general. The comparison of the values of the coefficient of variation calculated from individual data with the values calculated on the basis of the average yields indicates fundamental differences which should be taken into account when applying the variation coefficient to assess production risk and, consequently, to optimise insurance tools.

Embedding animal welfare in sustainability assessment: an indicator approach

In line with growing consumer interest in sustainable food production, a number of farm-level sustainability indicator studies have been published in recent years. Despite the importance of animal welfare, many such frameworks fail to adequately take account of it, mostly due to difficulties in accessing suitable data. This paper demonstrates that it is possible to develop indicators of animal welfare that can be embedded within a wider sustainability framework using a representative farm-level dataset such as the European Union (EU) Farm Accountancy Data Network (FADN) for Ireland, the Teagasc National Farm Survey. The paper presents a set of sustainability indicators for dairy farms in Ireland for the 2014–2017 period and examines the impact of policy reform on sustainability performance. Headline results show that welfare standards on dairy farms in Ireland have remained stable over the period despite the considerable intensification of the dairy sector following EU milk quota removal. Furthermore, dairy farms that have expanded herd size significantly have improved welfare standards more than farms that have not increased production. An analysis of synergies and trade-offs between the various aspects of sustainability reveals that positive correlations exist between welfare standards and economic and environmental performance. The analysis facilitates the identification of win-win farm-level strategies that can be adopted to improve economic, environmental and animal welfare outcomes. The framework developed here presents opportunities for evaluating policy impacts at the farm level on various aspects of sustainability. The use of the FADN demonstrates the capacity to extend such an approach across the EU.

One or many European models of agriculture? How heterogeneity influences income creation among farms in the European Union

Agricultural structures are quite heterogeneous across the European Union (EU), and it is likely that the underlying technology also differs across regions. In this article, we claim that the heterogeneity of agriculture across the EU affects the process of income creation (i.e. the relative importance of the factors of farm income differ for different agricultural models). A panel of farms representative for 125 regions reporting to the EU Farm Accountancy Data Network (FADN) during the period from 2007 to 2018 is used. In this article, those regions are grouped into three clusters. A system generalised method of moments (GMM) panel estimator is applied to each cluster. The results showed that total factor productivity (TFP), relative prices and agricultural subsidies make different contributions to farm net value added (FNVA). In particular, the income growth of farms in regions dominated by large farms seems to react more to marginal changes of the explanatory variables.

Factors Influencing Technical Efficiency in the EU Dairy Farms

This paper aims to analyse the technical efficiency (TE) of dairy farms and find its determinants. To accomplish this problem, the Stochastic Frontier Analysis was applied. The data were obtained from the Farm Accountancy Data Network database for dairy farms (TF15-45—Specialist dairying) for 2004–2019. Dairy farms were divided into four clusters according to their physical size (number of livestock units per farm) and economic size (standard output per farm). The largest farms by physical and economic size are located in Denmark and Cyprus. The smallest, in comparison, are in Bulgaria, Croatia, Latvia, Lithuania, Austria, Poland, Romania, and Slovenia. Farms in the EU are relatively technically efficient, i.e., they use their resources efficiently to produce maximum output (production). However, they have the potential to achieve better economic results and be more competitive, as the size of farms’ is not fully optimised. The abolition of the milk quota can be considered a factor in improving technical efficiency, as the indicator is higher after the abolition. New and old member states have almost comparable technical efficiency levels (the p-value of the t-test is 0.463), with old members having slightly higher level TE. Subsidies have contradictory effects on TE. Farm efficiency with higher subsidies per cow is higher for farms with €51–100/cow. However, as subsidies increase, TE decreases. Only the group of farms with the highest subsidies has a higher TE. More diversified farms are more technically efficient than specialised farms. Milk yield did not influence the analysed indicator. The analysis results can serve the stakeholders as a tool for modelling future agricultural policy, as the European farms are very heterogenous and show different conditions and economic outcomes.