A methodological tool for the ex ante evaluation of CAP reforms based on FADN data
This tool, developed, by the FACEPA project, designs and tests economic models appropriate for the ex ante analyses of agricultural policy interventions across selected Member States based on FADN data.
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Output Description
An essential objective of the FACEPA project was the evaluation of public policies based on FADN data. This objective includes the design, development and testing of FADN-based economic models appropriate for ex ante analyses across selected Member States. The ex ante evaluations used flexible cost functions and utilised FADN data. The impacts were derived by simulating the cost functions under different scenarios concerning price or other changes.
The ‘general cost of production model’ (GECOM) functions are estimated for dairy farms in Lower Saxony and Bavaria (Germany) and crop farms in Lower Saxony. The ex ante model analysed the impact of the dairy and sugar quota abolishment for different scenarios of accompanying price decreases of milk and sugar beet. In Austria, the model was tested with an ex ante examination of a possible abolition of milk quotas.
Relevance for monitoring and evaluation of the CAP
Ex ante evaluation of policy impacts: The proposed methodology allows the estimation of various developments such as price changes or policy changes on the cost function of EU farms utilising only FADN data. It was tested on several commodities and in three different European countries. It is a valid methodology for scenario analysis and the ex ante evaluation of likely policy impacts. In the current CAP context, the method could assess the ex ante effects of the CAP Strategic Plans on productivity and farm viability. It may also support the ex ante assessment of future CAP reforms.
The cost production model (GECOM) is a valuable source of information for competitiveness analysis. FADN data is the basis for product-level data so that evaluators can show the gross margin of one product or unit cost for another product. In the case of gross margin, they can allocate variable costs to different products, and in the case of unit cost, they need to allocate the total cost to different products. A sophisticated methodology is needed for this procedure, and the cost production model is such a methodology. The data can also be used for agricultural policymaking (ex ante stage). For instance, gross margin and total cost data in Hungary have been used to build the income stabilisation policy.
The tool describes the ‘general cost of production model’ (GECOM) methodology and the rationale for setting up the econometric model based on FADN variables to fit and test the model and interpret the results. The model requires only econometric skills and access to FADN farm-level data and can be adapted and used to evaluate policy and other impacts on various products and for all Member States.
Relevance of the output per CAP Objectives
- Specific Objective 1 - Ensure a fair income for farmers
Additional output information
Data collection systems used:
- FADN(FSDN)
Type of output:
Methodology
Associated evaluation approaches:
- Scenario analysis
Spatial scale:
- Farm holding
Project information
Farm Accountancy Cost Estimation and Policy Analysis of European Agriculture. FACEPA developed tools and methods to analyse production costs in European agriculture using FADN data. It has provided information, expertise and economic models on the cost of production for various agricultural products.
Specific objectives:
- To address the usefulness and appropriateness of the FADN data to measure the cost of production for agricultural commodities.
- To develop a ‘general’ cost of production model for EU agriculture.
- To test and implement this cost model in an EU context on a large scale.
- To assess the relationship between cost structure and farm performance, farm technology, environmental quality and farm heterogeneity.
- To provide methodological improvements to the ‘general’ cost of production model.
- To evaluate agricultural policy measures using models based on the production cost estimates.
Project’s timeframe: 2008 – 2011
Contacts of project holder: Yves Surry, Swedish University of Agricultural Sciences (yves.surry@slu.se)
Territorial coverage: Belgium, Bulgaria, Estonia, France, Hungary, Italy, Sweden, The Netherlands