In Belgium, an agricultural sector model for ex ante policy analysis is developed. The model, called SEPALE, uses an adapted version of Positive Mathematical Programming allowing for simultaneous modelling of individual farms. SEPALE applies farm level calibrated cost functions to the sample of the Farm Accountancy Data Network to account for the large variability among farms. Due to the recent discussion on the Sugar Common Market Organization (CMO) reform, the need raises for an appropriate methodology to cope with quota in positive programming models. Modelling quota at farm level implies three important challenges: i) estimation of the marginal cost or the quota rent, ii) simulating over- or undersupply and iii) quota exchange. Present paper describes a methodology dealing with the three quota issues. Simulations of sugar beet policy options draw on the proposed approach. The paper also demonstrates that other types of quota could benefit as well.