Descrizione del progetto
Garantire la sostenibilità della PAC dell’UE
La futura Politica agricola comune (PAC) dell’Unione europea svolge un ruolo fondamentale nello sviluppo di un settore agricolo sostenibile. La futura PAC sarà più flessibile e adattabile nei confronti delle esigenze degli Stati membri dell’UE e delle unità decisionali individuali nel settore. A tal fine, gli Stati membri sviluppano piani strategici per la PAC che dovrebbero definire obiettivi misurabili e mezzi per la loro realizzazione. Il progetto MIND STEP, finanziato dall’UE impiegherà dati agricoli e biofisici e includerà l’unità decisionale individuale in modelli politici nuovi ed esistenti per la valutazione d’impatto. Attraverso statistiche agricole e ampi set di dati, saranno stimati e calibrati nuovi modelli decisionali individuali, sulla base di tecniche economiche stabilite e di apprendimento automatico in evoluzione.
Obiettivo
Agricultural policies like the EU CAP are widening the scope to contribute to the Paris climate agreement and the Sustainability Development Goals. From the Commission's legislative proposals (June 2018) it is expected that the European Union (EU) Common Agricultural Policy (CAP) will be redesigned in line with this. Consequences are among others a move of the CAP to farm specific measures and an improved link to environment, climate change and ecosystem services. It is proposed that Member States and regions develop their own CAP strategic plan with more attention to the regional implementation of the CAP. This wider scope and measures with a focus on individual farmers ask for a new generation of impact assessment tools. Current state-of-the-art agricultural models are not able to deliver individual farm and local effects as they are specified at higher levels of aggregation. Making use of improved possibilities opened up by progress in the ICT area, our project MIND STEP will improve exploitation of available agricultural and biophysical data and will include the individual decision making (IDM) unit in policy models. Based on a common data framework MIND STEP will develop IDM models, including agent-based models, focussing on different topics in an integrated manner in different regional case studies. The IDM models will be estimated and calibrated using agricultural statistics and big datasets, drawing on established econometric and evolving machine learning techniques and using both traditional models of optimising behaviour and theories from behavioural economics. MIND STEP will closely cooperate with a range of stakeholders to co-create and apply the MIND STEP model toolbox to selected regional, national and EU wide policy cases. MIND STEP cooperates with other consortia under the topic to share ideas and innovations. Finally, MIND STEP develops an Exploitation Strategy and Plan to guarantee the sustainability of the project results upon its completion.
Campo scientifico
- social scienceseconomics and businesseconomics
- natural sciencesbiological sciencesecologyecosystems
- agricultural sciencesagriculture, forestry, and fisheriesagriculture
- natural sciencesearth and related environmental sciencesatmospheric sciencesclimatologyclimatic changes
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Parole chiave
Programma(i)
Argomento(i)
Meccanismo di finanziamento
RIA - Research and Innovation actionCoordinatore
6708 PB Wageningen
Paesi Bassi