Normative, positive and econometric mathematical programming as tools for incorporation of multifunctionality in agricultural policy modelling

Enlarging the scope of agricultural policy analysis, with contemporary issues such as multifunctional farming, means that conventional models should be adjusted. Starting from the intrinsic nature of multifunctionality, we show that the link between farm and policies is becoming increasingly important in the general framework of model-based policy impact analysis. This argues for the use of farm-level programming models. The paper presents three mathematical programming approaches, of which the choice depends on the type of problem and the availability of historical data. First is shown how normative mathematical programming (NMP) can help to simulate the impact of new activities when historical data are scarce. The second approach is positive mathematical programming (PMP), which allows taking both historically observed behaviour and new normative information into account. The similarities and differences between both approaches are illustrated with a simplified dairy farm model that simulates the uptake of meadow bird management. Finally, a more advanced programming technique, econometric mathematical programming (EMP), is introduced combining the advantages of econometrics and programming techniques. Advantages and disadvantages as well as the integration with other quantitative methods are discussed for relevance and
applicability in multifunctionality research.