Abstract: Estimation of farm economic sustainability and viability became more topical when redesigning the Co- mmon Agricultural Policy which should stabilise farm income and make agribusiness more viable and sustainable (typically in Czech areas facing natural constraints). The key question is how to calculate the income of farms or farm households not only to survive but also to grow sustainably. The article summarises and compares knowledge from 51 studies to provide a comprehensive discussion on different ways how to measure economic viability and sustai- nability to set income support for farms in the areas with natural constraints optimally. The authors found family farms and off-farm income as important limitations of FADN database (FarmAccountancyDataNetwork) for eva- luation of the economic sustainability of farm household. Moreover, some financial ratios (Return on Assets – ROA and assets turnover) are not suitable viability indicators for farms with a high share of hired land (typically large legal entities). Joining family farms and legal entities, the authors recommend using modified Farm Net Value Added (MFNVA) allowing for opportunity costs of own land and non-land assets. The average wage in the economy or re- gion is a better proxy for opportunity labour costs of unpaid work rather than average agricultural wage.
Abstract: Italian farms have an average surface lower than 10 hectares and they are predominately scattered in the upland rural areas. Th e most important aspect of small family farms is to protect the rural environment against the socio-econo- mic marginalization of rural territories and reducing the out-migration from the countryside as well. Since the 1960s, the European Union has arranged a microeconomic survey on a sample of farms aimed at estimating the impact of the Com- mon Agricultural Policy strategies on farmers called the FarmAccountancyDataNetwork or the FADN. Th e purpose of the analysis was to assess by a quantitative approach using the FADN dataset the technical, economic and allocative eﬃ ci- ency in Italian family farms over the time 2000–2012. In particular, the aim of the paper has been to investigate if the legal typology of property has inﬂ uenced the eﬃ ciency of Italian farms. Some ﬁ ndings have pointed out that the co-operatives and family farms during the ﬁ ve year time 2008–2012 have had the same level of eﬃ ciency. Italian small farms smaller than 5 hectares need adequate ﬁ nancial supports allocated by the II. pillar of the Common Agricultural Policy and these subsi- des are pivotal in particular towards family farms located in the upland and hilly areas.
Sample representativeness veriﬁ cation is one of the key stages of statistical work. A er having joined the European Union the Czech Republic joined also the FarmAccountancyDataNetwork system of the Union. This is a sample of bodies and companies doing business in agriculture. Detailed production and economic data on the results of farming business are collected from that sample annually and results for the entire population of the country´s farms are then estimated and assessed. It is important hence, that the sample be representative. Representativeness is to be assessed as to the number of farms included in the survey and also as to the degree of accordance of the measures and indices as related to the population. The paper deals with the special statistical techniques and methods of the FADN CZ sample representativeness veriﬁ cation including the necessary sample size statement procedure. The Czech farm population data have been obtained from the Czech Statistical Oﬃ ce data bank.
Every year a sample of farm accounts is established in order to report Danish agro-economical data to the ‘FarmAccountancyDataNetwork’ (FADN), and to produce ‘The annual Danish account statistics for agriculture’. The farm accounts are selected and weighted to be representative for the Danish agricultural sector, and similar samples of farm accounts are collected in most of the European countries. Based on a sample of 2138 farm accounts from year 1999 a national agricultural model, consisting of 31 farm types, was constructed. The farm accounts were grouped according to the major soil types, the number of working hours, the most important enterprise (dairy, pig, different cash crops), livestock density, etc. For each group the farm account data on the average resource use, products sold, land use and herd structure were used to establish a farm type with coherency between livestock production, feed use, land use, yields, imported feed, homegrown feed, manure production, fertilizer use and crop production. The set of farm types was scaled up to national level thus representing the whole Danish agricultural sector and the resulting production, resource use and land use was checked against the national statistics. Nutrient balance methodology and state-of-the-art emission models and factors were used to establish the emissions of nitrate, phosphate, ammonia, nitrous oxide, methane and fossil carbon dioxide from each farm type. In this paper data on resource uses and emissions from selected farm types are presented and it is demonstrated that this approach can lead to an agro-environmental inventory, which is consistent with national level estimates and still has the advantage of being disaggregated to specific farm types. Conventional dairy farm types in general emitted more nitrate but less phosphate compared with pig farm types. The methane emission was higher from dairy farm types compared with all other farm types. In general the conventional dairy farms emitted more nitrate, ammonia, and nitrous oxide, compared with organic dairy farms. # 2006 Elsevier B.V. All rights reserved.
Agricultural land fragmentation is widespread and may affect farmers’ decisions and impact farm performance, either negatively or positively. We investigated this impact for the western region of Brittany, France, in 2007. To do so, we regressed a set of performance indicators on a set of fragmentation descriptors. The performance indicators (production costs, yields, revenue, profitability, technical and scale efficiency) were calculated at the farm level using FarmAccountancyDataNetwork (FADN) data, while the fragmentation descriptors were calculated at the municipality level using data from the cartographic field pattern registry (RPG). The various fragmentation descriptors enabled us to account for not only the traditional number and average size of plots, but also their geographical scattering. We found that farms experienced higher costs of production, lower crop yields and lower profitability where land fragmentation (LF) was more pronounced. Total technical efficiency was not found to be significantly related to any of the municipality LF descriptors used, while scale efficiency was lower where the average distance to the nearest neighbouring plot was greater. Pure technical efficiency was found to be negatively related to the average number of plots in the municipality, with the unexpected result that it was also positively related to the average distance to the nearest neighbouring plot. By simulating the impact of hypothetical consolidation programmes on average pre-tax profits and wheat yield, we also showed that the marginal benefits of reducing fragmentation may differ with respect to the improved LF dimension and the performance indicator considered. Our analysis therefore shows that the measures of land fragmentation usually used in the literature do not reveal the full set of significant relationships with farm performance and that, in particular, measures accounting for distance should be considered more systematically.