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The new Common Agricultural Policy (CAP) for the period 2023–2027 commits farmers towards achieving ambitious environmental objectives through farm organization and management. This European agricultural policy has adapted to the contemporary challenges faced by the new model of agricultural development. It aims to enhance the contribution of agriculture to the EU's environmental and climate objectives while providing better targeted support to small-scale farmers to promote farms' competitiveness. The main objective of this paper is to describe Italian farms and classify them into groups based on their main characteristics, as well as to analyze their performance and behavior in terms of sustainability and competitiveness. The novelty and innovativeness of this study are found in the data used; a 2020 dataset from the Italian Farm Accounting Data Network (FADN) was used. The quality of FADN data in farm sustainability assessment is widely acknowledge in the literature. To achieve the purpose of this study, a multivariate analysis, in particular, the Principal Components Analysis (PCA), and a Cluster Analysis (CA) were applied. These analyses helped us to obtain the factorial axes which then enabled us to identify economic information on farms, and a better interpretation of farmers' aptitude to undertake environmentally friendly actions. As a result, eight groups of farms were identified, and their characteristics and performance were described at Italian district level. The results of the study reflect the influence of European interventions towards encouraging farmers to use more environmentally friendly agricultural practices. Under this perspective, the findings contribute to the current debate on green architecture pursued by the future European agricultural policy. [ABSTRACT FROM AUTHOR]

Small farms are gaining space and importance within the agricultural policies implemented by the European Union, mainly for the role that they play for the preservation of the territory and for the economic development of local rural areas. Small farms represent a new opportunity to guarantee the permanence of populations and agricultural workers in rural areas, contributing to the formation of the income of farming families. Therefore, in this study, after identifying small farms as those farms that have a Standard Output (SO) of less than EUR 25,000, their structural characteristics were defined, as well as their economic and financial situation. The analysis was performed using the Italian FADN data for the years 2018–2020 and using a set of structural and economic–financial indicators. Furthermore, the study analyzes the relationship between farm performance and agricultural resources and also with farmer demographics and farm size. The principal Component analysis was used to reduce the number of variables used in the Ordinary Least Square (OLS) regression model which was applied to identify the factors contributing to the small farms' profitability. The territorial distribution of small farms shows a polarization: 37% of them are in Southern Italy, and more than 34% of them are in Northern Italy. The analysis also reveals that about 67% of the Italian small farms are specialized, in particular, in arable land (37.6%) and herbivores (16.8%). They are mainly conducted by men with a high school education level and with an age that is between 40 and 65 years. The economic results also show a good performance, however, there is a wide district differentiation: while the Northern regions have the best results in terms of farm net income, those of Southern Italy are more dependent on the public support they receive. The results of the multiple linear regression analysis revealed which variables (e.g., land size, labor, public aid, etc.) had a direct relationship with the profitability of small farms. The research provides interesting insights to stakeholders on the public support (specific measures) that needs to be designed and implemented to favor the survival of small farms in rural areas. [ABSTRACT FROM AUTHOR]

Land concentration and land grabbing have been a reality for many years in Europe. In fact, in the 27-member EU, only 3% of farms already controlled 50% of the land used for farming purposes. This paper investigates the dynamics of land concentration in Italy using the Italian Farm Accountancy Data Network (FADN). Some of the most used concentration measures have been applied to the FADN database in the period 2015-2017 over a total of about 7,000 constant farms. How the above mentioned measure has influenced the probability of expansion of farms is analysed in the second part of the paper through a model that considers, among others, some characteristics of farms, including the size of the farm, the presence of organic methods and the presence of extra-agricultural activities. Preliminary results of the model show a significant effect of farm size on the probability of expansion of farms; larger farms are therefore more likely to expand by acquiring new agricultural land. This paper offers the starting point for discussing the theme of the concentration of land market through an empirical interpretation. [ABSTRACT FROM AUTHOR]

The paper provides an application of micro-data statistical analysis for agricultural economics studies. We use data from the 2000 and 2010 Censuses to build a short, two-year panel of 823.771 farms and we used the panel to describe specialization in Italian agriculture. We classified Italian farms into four groups according to their adoption of specialized Type of Farming (TOF) in 2000 and 2010 or de-specialized TOF in both surveys, or the change from a specialized to a de-specialized TOF or vice versa. The degree of specialization in Italian agriculture increased over the decade and the result was driven mostly by a relevant shift toward specialization of farms located in the mountain areas of central and southern Italy. We also found an association between the age structure of the family workforce and the choice of adopting a specialized TOF. [ABSTRACT FROM AUTHOR]

Although describing the primary sector of a given country is a common institutional practice, such studies usually offer aggregated information on holding rather than supplying the information required for farm-level simulations. The present study aimed to identify the main typologies of Italian farms from the 2007 database of RICA (the Italian section of the European Union's Farm Accountancy Data Network). Using a hierarchical strategy driven by climates (5) and slopes (3), farms have been grouped by super-structure, described in terms of the presence and extent of primary activities (livestock, farmland use). The resulting picture of Italian farms is based on 35 farm types, the most common of which grow low-input orchards (e.g., olive trees). On the plains in warm climatic areas, low-input orchards and arable crops dominate; in hilly and mountainous areas, mixed farms with forage crops, meadows, ovines, and cattle prevail. In more temperate areas, the most common farm type is based on intensive and field crops (e.g., durum and bread wheat). In temperate hilly and mountain areas, mixed farms combining meadows, woods, and cattle become predominant. [ABSTRACT FROM AUTHOR]

In this paper, the case of the Italian fruit-drink industry is presented to discuss the strategic issues of product-innovation in imperfectly competitive markets. In particular, three main topics are addressed: the incentives to the adoption of innovation-based strategies, R&D investments in imperfectly competitive markets and the role of vertical coordination. To address the topics, a brief description of the industry, a game-theory conceptual framework and a strategic analysis of the marketing channels are proposed. The major conclusions can be summarized as follows: (i) product-innovation strategies are the result of an evaluation of the option value of the R&D investments, the risk of failure and competitors' strategies (ii) demand pull only may be insufficient to trigger innovation: an efficient retailing system, costs of failure and production efficiency may influence the firm's strategic approach to innovation. [ABSTRACT FROM AUTHOR]