Ocupaciones de Almacenamiento.

The overall objective of this PhD thesis was to develop and evaluate generic bio-economic farm models that can be used for integrated assessment of agricultural and environmental policies at multiple levels and different biophysical and socioeconomic conditions.

First, we looked into the modelling requirements for developing a generic and re-usable bio-economic model for integrated policy assessment. A farm model was developed that can be readily adapted to simulate arable, livestock and mixed farming systems located in various socio-economic, political and physical environments (i.e. different regions, soil types, climatic zones). Most resource constraints related to arable farm types are relevant also for livestock and mixed farm types and they are always included in the model specification. The constraints and the data inputs have been separated in different modules (e.g. arable, livestock, calibration) so that constraints related to different kinds of farming systems can be switched on and off easily in the model’s code.

For non-modellers, switching on and off of constraints can be done in the SEALMESS- IF graphical user interface. Using the SEAMLESS integrated database (Janssen et al., 2009) enables uniform reproduction of data inputs for different farm types across the EU. Both current and alternative agricultural activities are defined as crop rotations and/or herd structures capturing possible spatial and temporal interactions between different crops and livestock. The calculation of a number of environmental indicators is also enabled. The reusability of the model was demonstrated in Chapter 2 and it is confirmed by the significant number of applications that have already been using it. Louhichi et al., (2008) used the model with detailed information available at regional level to assess the consequences of the nitrate directive in Midi-Pyrennes (France). Kanellopoulos et al.,

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out Europe. The effects of CAP reform to the European dairy sector were revealed by Louhichi et al. (2009b). Majewski et al. (2009) investigated scenarios of bio-fuel promoting policies in Poland. The effects of the 2003 CAP reform to water quality in a Scottish region were assessed in Mouratiadou et al. (2009). Price-supply elasticities calculated by the proposed bio-economic model for a representative sample of regions were used in Pérez Domínguez et al. (2009) for extrapolating the production structure across EU. The model has been also used to simulate farming systems of developing countries (Traoré et al., 2009).

Second, different options for calibration and methods to recover unknown parameters underlying the farmer’s decision making have been explored. We proposed alternative calibration procedures that improve the existing PMP methodology (Chapter 3 and 4). A method based on Maximum Entropy estimation for quantification of the farmer’s risk attitude was also proposed. We used “back-casting” simulations (i.e. ex-post experiments) to assess the forecasting performance of the model calibrated with different methods. In these simulations, the bio-economic farm model is calibrated with historical data of a particular base year and it is used to forecast effects of policies and price changes on the following historical years. The capacity of the model to reproduce changes in activity levels of the past is assessed.

The proposed calibration methods involve a number of underlying assumptions that better comply with the actual decision making of farmers. The values of limited resources were raised to the average gross margin instead of the gross margin of the least preferable activity; increasing marginal costs were assumed for all activities and complementarity, substitution and risk aversion were quantified. Despite the improved forecasting performance, it was concluded that there is no general calibration method appropriate for all cases. The data availability and the aim of the study appear to be the most important factors that determine the best calibration option for a specific case. For example, the Röhm & Dabbert (2003) PMP variant can be used if there is available information on observed levels of crop-management combinations in order to account for different elasticities between managements and crops. The PMP variant proposed in Chapter 3 can be used to exploit available information on own price elasticities or information on historical data that allows for designing an ex-post experiment. The Maximum Entropy estimation approach proposed in Chapter 4 can be used to exploit panel data on activity levels and expert’s knowledge on agro-management to estimate explicitly complementarity, substitution and risk aversion. The standard PMP approach (Howitt,

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1995) can be a solution in cases where such information is not available. To give enough options to model users and policy makers, we implemented a number of different calibration procedures in the developed bio-economic farm model. The related equations and constraints of different calibration procedures are included in separate modules so that they can be switched on and off easily.

Finally, we investigated approaches for identifying a set of alternative activities that could be used for integrated assessment of future scenarios. Combinatorial methods (Dogliotti et al., 2003; Janssen, 2009) can be used to generate all possible alternative agricultural activities in a uniform and reproducible way for a large number of farm types with relatively limited information. The limitation of the method is that the number of alternative activities that is generated in combinatorial approaches can easily explode. Only a fraction of the generated activities are relevant from a policy point of view. We proposed a generic approach based on Data Envelopment Analysis (DEA) for reducing the number of interesting alternative activities to a level that can easily be applied in bio- economic farm models.