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The issue of productivity and performance in agriculture is significant because it affects a country's competitiveness, sustainability, and self-sufficiency in agricultural production and is reflected in European policy. This study aims to determine which country had the most efficient large farms compared to other V4 countries and whether efficiency in each country translates into the performance of large farms. The data were obtained from the EU FADN (Farm Accountancy Data Network) database from 2005 to 2019. These data were then evaluated using the statistical methods DEA: CCR-O (Data Envelopment Analysis: constant returns to scale), DEA: BCC-O (Data Envelopment Analysis: variable returns to scale), and Pearson correlation coefficient. Regarding international comparisons in achieving efficiency as measured by DEA, Hungary is the best performer among the countries compared, followed by Czechia, Poland, and Slovakia. The correlation between efficiency and performance measured by Farm Net Value Added was demonstrated only for Hungary. The international comparison provided information about which country had the most efficient large farms, what the ranking of countries was in terms of efficiency, and for which countries efficiency had / did not have a potential impact on performance. At the same time, the relationships regarding the efficiency and performance of farms with an economic size above EUR 500 000 of standard output were clarified.

When analysing drivers affecting the farm performance, the presence of different technologies should be taken into account. We assume that the technology used by crop farms is not the same for all producers and therefore we use latent class model to identify technological classes at first. Class definition is based on multidimensional classification and determination of indices given by the values of individual components. The principal components analysis is applied to estimate significant and robust weights for the index components. FADN (Farm Accountancy Data Network) database, Czech crop farms data from 2005 to 2017 were used and three groups of technology classes of farms were identified with a determinant influence of the structure index and localisation. The other indices characterise sustainability, innovation, technology, diversification, and individual characteristics. Three distinct classes of crop farms were found, one major class and two minor classes. Family driven farms are usually smaller farms in terms of acreage. Highly sustainable crop farms are most likely located in lower altitudes and not in less-favoured areas. Innovative farms are also likely to be more productive. The results indicate that agricultural production farms with a more sustainable way of farming are most likely to be more productive.

Organic farming has become an important part of Czech agriculture. The aim of this study is an evaluation of the technical efficiency of Czech organic farms and determining the main factors, including subsidies, which affect the technical efficiency of both conventional and organic farms. The Farm Accountancy Data Network Czech Republic (FADN CR) database provides sufficient panel data for this kind of research focusing on types of farming with livestock production. The methodological tool used to achieve the aim of this paper is the parametric stochastic frontier analysis, "True" Random Effects model, supposing farms heterogeneity and time variant determinants of inefficiency. The results of the research verified differences in the technical efficiency of organic and conventional agriculture related both to the different farming methods and to the production conditions. The type of farming and the economic size of farms influence the farms' profitability, economic performance and comparability with conventional farms. The technical efficiency of organic farming is growing over the long term. Farms with growing technical efficiency show a decline in the proportion of operating subsidies to production, irrespective of their classification in quartiles by the technical efficiency estimate.