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Farm succession is a relevant issue, as it is related to rural and youth migration, sustainability and the ageing of the agricultural sector. Understanding the factors behind the willingness of potential successors to take over the family business is crucial for farm continuity. We examine the factors affecting children's likelihood of carrying on the family business in a sample of 216 potential heirs of Italian horticultural farms. Using local labour market conditions (income gap and employment rate) and surrounding context variables (population density), we plug the farm labour migration/occupational choice theory into farm succession analysis. This approach allows us to treat child succession as the opposite of the choice to migrate out of the farm sector. While farm labour migration theory predicts linear negative effects of labour market/contextual variables on farm transfer, we find that the income gap, employment rates and population density exert both negative and positive effects on child succession, according to their intensity. The pro-succession effects we find suggest that, despite potential threats, the proximity to wealthy areas may represent an opportunity for farm continuity and thriving. We also examine explicitly the effect of child characteristics (gender and birth order), finding that male and first-born potential successors are more likely to take over the family farm, in accordance with results from previous firm succession studies. This finding suggests a persistence of traditional normative beliefs in the agricultural sector.

Sustainable development is more often considered by media, public opinion, and politicians to be the main goal our society should attempt to pursue in the coming years. To this aim, academic researchers have made sustainability one of the main objects of their studies. This work focuses on environmental sustainability and presents a brief overview of how it is taken into consideration in the agricultural economics field by considering this topic from different perspectives and thus highlighting how this field is gradually broadening its scope to include sustainable development objectives. Our analysis shows that the path towards sustainable development is strongly correlated to the protection of the environment. Therefore, agricultural policies aimed at protecting and preserving the environment, and, more in general, innovation along the agri-food chain, together with consumer attention towards environmental issues, can play an important role in achieving this objective.

The problem of detecting a major change point in a stochastic process is often of interest in applications, in particular when the effects of modifications of some external variables, on the process itself, must be identified. We here propose a modification of the classical Pearson χ 2 test to detect the presence of such major change point in the transition probabilities of an inhomogeneous discrete time Markov Chain, taking values in a finite space. The test can be applied also in presence of big identically distributed samples of the Markov Chain under study, which might not be necessarily independent. The test is based on the maximum likelihood estimate of the size of the 'right' experimental unit, i.e. the units that must be aggregated to filter out the small scale variability of the transition probabilities. We here apply our test both to simulated data and to a real dataset, to study the impact, on farmland uses, of the new Common Agricultural Policy, which entered into force in EU in 2015.

The transfer of farm activity over time occurs through different pathways, among which the more frequent is intra-family farm succession. Thus, better information on farm succession determinants is crucial for understanding farm succession and informing appropriate sectoral policies. To date, substantial research has focused on the effect of farm, farmer and potential heir features on farm succession, while the role played by socioeconomic conditions around a farm has been relatively less examined. Building on previous contributions, the present paper considers farm succession as the opposite of labour migration out of the agricultural sector. Thus, the effect of the labour market and surrounding conditions (LMSC) around a farm on its succession probability is explored. The aim of this paper is therefore to explore whether and to what extent the inclusion of LMSC variables may contribute to a better understanding of farm succession. Using data from a sample of 266 fruit and vegetable farms (gathered for informative purposes by a producers' organization consortium), empirical evidence that LMSC variables play an important role in explaining the succession probability in these types of farms is provided. Specifically, the results show that (i) including LMSC variables in a farm succession analysis increases the explanatory power and robustness of the model estimates; (ii) LMSC variables have a non-linear effect on succession; and (iii) some explanatory variables (farmer education and farm age, specialization and dimension) are significant across various specifications, while other variables (farmer age, territorial location and distance of a farm from its producer organization) change their sign and/or significance when LMSC variables are included in the model. As a consequence, our findings suggest that LMSC variables should be included in farm succession and labour market analysis to provide a better estimate of farm succession probability.