The redesign of the Common Agricultural Policy (CAP) allows for more room to address issues related to stabilising farmers’ income and developing their viability in areas facing natural constraints (ANC). Maintaining income levels, developing farm economies in rural areas, and encouraging competitive agricultural practises are the challenges facing the new CAP. ANCs in the Czech Republic are characterised by a lower level of income compared to areas outside ANCs and their generally prevailing specialisation in livestock production, which has been facing a relatively turbulent development in the last decade. The main aim of this paper is to evaluate the economic viability with regard to the level of natural disadvantage and with regard to farm specialisation. The database of Farm Accountancy Data Network (FADN) was used for assessment; the authors built the Farm Economic Viability indicator, which is based on modified Farm Net Value Added. The differences between the farm groups were tested through analysis of variance. Significantly lower viability was found in ANCs compared to farms outside ANCs. Field crops achieved significantly higher levels, both in and outside ANCs. The most threatened group of farms are grazing livestock in ANCs.
The purpose of this paper is to examine the internal structure of Czech agricultural holdings based on a multicriteria evaluation of the five dimensions representing the main functions of agriculture including production, economic<br />factors, financial stability, environmental, and social and other factors. A cluster analysis was performed to identify two clusters of farms. The first cluster consists of smaller holdings that specialize in livestock production and achieve poorer financial results compared to the second cluster, which includes a larger share of large holdings that focus on crop production. The first cluster exhibited better performance as regards environmental protection and financial stability. In contrast, the second cluster achieved better scores regarding production and economic factors. However, an evaluation of all dimensions showed that the second cluster of farms obtained slightly better ratings (2.7% above the overall average) then the first cluster (3.1% below the overall average score). It is up to policy makers to decide which group of farmers, is more approaching the aim of the new agricultural policy. Policy makers can consider the results of this study to find the areas where the sustainability rate should be increased and purposefully promote that by specific measures to achieve balanced farming system.
The paper aims at vertical price transmission of the agri-food market in the Czech Republic. It is focused on the analysis of price transmission in pork meat by investigating the short-run and long-run relationships within the product and the speed of establishing the equilibrium relationship. For this purpose, there is employed specially VECM (Vector Error Correction Model), impulse-response analysis, and decomposition of variance of VECM, which show the system’s reaction. The applied approach considers five alternatives in the Johansen approach. The results suggest that there is an existence of the equilibrium relationship in vertical markets and this relationship is simultaneous and demand-driven. The impulse-response analyses show the response of the processing price to one standard deviation shock to the agriculture price from approximately 15–20 periods reaching long-run equilibrium. The response of the agriculture price to one standard deviation shock to the processing price reaching long-run equilibrium is also from approximately 15–20 periods.
The paper submitted offers an assessment and comparison of three approaches to agricultural cost inputs short-term forecasting, that have been proposed as possible alternatives to tackle the problem. The data applied have been taken from the Czech Statistical Office and the Farm Accountancy Data Network data sources. The forecasts were prepared using time series analyses based on methods of exponential smoothing and Box-Jenkins methodology of autoregressive integrated process moving averages. The proposed change index numbers for the 2012, 2013 and 2014 years from three approaches were confronted with the real development of costs time series as it was found in the statistical FADN survey results. The main conclusion drawn pointed out that, for the purpose of economic income estimation based on the FADN database, the cost prediction approach based on the same database, i.e., on time series analysis of the FADN panel data, is the most applicable one. However, it is recommended, too, to use other approaches for crops protection products cost and labour cost development.
The current paper aims to assess farming enterprise outcomes in the Czech Republic from a socio-economic perspective. The relationship between the age of a farms’ managers and its economic results has been analysed for 1 351 farms using the FADN (Farm Accountancy Data Network) database in order to determine whether farms’ economic results differ on the basis of the age of their managers. Our analysis confirms that there is indeed a correlation between manager age and a farming enterprise’s economic results. The results have been analysed in detail according to the age groups of managers and farm owners, farm specialization, and farm size. The farm net value added per annual work unit reached the best values in businesses managed by young farmers in crop production (EUR 34 445) and young farmers in large enterprises (EUR 43 400). The oldest farmers, specializing in milk production, had the highest level of indebtedness (0.39). The data reveal that the age of farmers is inversely proportional to the level of indebtedness, with level of debt decreasing with increasing farmer age. A Mann-Whitney U test (with Bonferroni correction) confirms a statistically significant difference between young farmers and the remaining three age groups in the ratio of production to cost.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.