Le scelte di investimento delle aziende agricole e la PAC post-2013: valutazione di scenari mediante un modello real options

Negli ultimi decenni la Politica Agricola Comune (PAC) è stata sottoposta a diverse revisioni, più o meno programmate, che ne hanno modificato gli obiettivi operativi e gli strumenti per perseguirli. In letteratura economica agraria sono state eseguite diverse ricerche che affrontano analisi ex-ante sui possibili impatti delle riforme politiche, in particolare al disaccoppiamento, riguardo all’allocazione dei terreni alle diverse colture e all’adozione di tecniche di coltivazione più efficienti. Ma tale argomento, nonostante sia di grande importanza, non è stato finora affrontato come altri temi del mondo agricolo. Le principali lacune si riscontrano infatti nella carenza di analisi ex-ante, di modelli che includano le preferenze e le aspettative degli agricoltori. Questo studio valuta le scelte di investimento in terreno di un’azienda agricola di fronte a possibili scenari PAC post-2013, in condizioni di incertezza circa le specifiche condizioni in cui ciascuno scenario verrebbe a verificarsi. L’obiettivo è di ottenere indicazioni utili in termini di comprensione delle scelte di investimento dell’agricoltore in presenza di incertezza sul futuro. L’elemento maggiormente innovativo della ricerca consiste nell’applicazione di un approccio real options e nell’interazione tra la presenza di diversi scenari sul futuro del settore agricolo post-2013, e la componente di incertezza che incide e gravita su di essi. La metodologia adottata nel seguente lavoro si basa sulla modellizzazione di un’azienda agricola, in cui viene simulato il comportamento dell’azienda agricola in reazione alle riforme della PAC e alla variazione dei prezzi dei prodotti in presenza di incertezza. Mediante un modello di Real Option viene valutata la scelta della tempistica ottimale per investire nell’acquisto di terreno (caratterizzato da incertezza e irreversibilità). Dai risultati emerge come in presenza di incertezza all’agricoltore convenga rimandare la decisione a dopo il 2013 e in base alle maggiori informazioni disponibili eseguire l’investimento solo in presenza di condizioni favorevoli. La variazione dei prezzi dei prodotti influenza le scelte più dell’incertezza dei contributi PAC. Il Real Option sembra interpretare meglio il comportamento dell’agricoltore rispetto all’approccio classico del Net Present Value.

A farm-level programming model to compare the atmospheric impact of conventional and organic farming

A model is developed to represent the activity of a farm using the method of linear programming. Two are the main components of the model, the balance of soil fertility and the livestock nutrition. According to the first, the farm is supposed to have a total requirement of nitrogen, which is to be accomplished either through internal sources (manure) or through external sources (fertilisers). The second component describes the animal husbandry as having a nutritional requirement which must be satisfied through the internal production of arable crops or the acquisition of feed from the market. The farmer is supposed to maximise total net income from the agricultural and the zoo-technical activities by choosing one rotation among those available for climate and acclivity. The perspective of the analysis is one of a short period: the structure of the farm is supposed to be fixed without possibility to change the allocation of permanent crops and the amount of animal husbandry. The model is integrated with an environmental module that describes the role of the farm within the carbon-nitrogen cycle. On the one hand the farm allows storing carbon through the photosynthesis of the plants and the accumulation of carbon in the soil; on the other some activities of the farm emit greenhouse gases into the atmosphere. The model is tested for some representative farms of the Emilia-Romagna region, showing to be capable to give different results for conventional and organic farming and providing first results concerning the different atmospheric impact. Relevant data about the representative farms and the feasible rotations are extracted from the FADN database, with an integration of the coefficients from the literature.

Technology Development and Consumer Acceptance of Innovation in Fruit Production

Precision Agriculture (PA) and the more specific branch of Precision Horticulture are two very promising sectors. They focus on the use of technologies in agriculture to optimize the use of inputs, so to reach a better efficiency, and minimize waste of resources. This important objective motivated many researchers and companies to search new technology solutions. Sometimes the effort proved to be a good seed, but sometimes an unfeasible idea. So that PA, from its birth more or less 25 years ago, is still a “new” management, interesting for the future, but an actual low adoption rate is still reported by experts and researchers. This work aims to give a contribution in finding the causes of this low adoption rate and proposing a methodological solution to this problem. The first step was to examine prior research about Precision Agriculture adoption, by ex ante and ex post approach. It was supposed as important to find connections between these two phases of a purchase experience. In fact, the ex ante studies dealt with potential consumer’s perceptions before a usage experience occurred, therefore before purchasing a technology, while the ex post studies described the drivers which made a farmer become an end-user of PA technology. Then, an example of consumer research is presented. This was an ex ante research focused on pre-prototype technology for fruit production. This kind of research could give precious information about consumer acceptance before reaching an advanced development phase of the technology, and so to have the possibility to change something with the least financial impact. The final step was to develop the pre-prototype technology that was the subject of the consumer acceptance research and test its technical characteristics.