Production cost estimation and policy impact analyses using farm accountancy data
Only those who know the costs can make the right decisions. This phrase holds true for farmers and policy makers alike. However: how to accurately determine costs?
Information on production costs is scarce. Often, data on costs is available only as generalized figures for planning purposes, or for a few selected farms. Representative farm level data, as is provided by the national and EU farm accountancy data networks (FADN), often does not comprise detailed information on how costs are allocated to individual activities or products. Against this background the EU research project FACEPA aims at determining productions costs on the basis of farm accounting data using statistical methods, and to use the results for policy impact analysis. We specifically are interested in the question whether it is possible to formulate one single model for all EU member states.
Together will partners in different EU member states we have developed an econometric model which estimates production costs for a wide range of products on the basis of accounting data. Costs are differentiated for different inputs, e.g. fertilisers, plant protection, etc. We discussed and validated the results with experts from agricultural advisory services in nine EU member states.
In addition, in cooperation with partners of the Universite catholique de Louvain, we estimated flexible cost functions for different farm types. By integrating these in mathematical programming models it is possible to assess ex-ante farm-level adjustments to policy changes.
We subjected the developed econometric model GECOM to thorough inspection: Overall, the model provides plausible estimates of production costs for main products in most countries, reflecting developments over time as well as cost composition. However, results for products with smaller output shares were often not convincing and highly variable over time.
During the testing of the GECOM, it was repeatedly observed that even small and/or infrequent data errors can have a significant impact on estimated cost share coefficients. Pre-checking the data in each case, dealing with outliers and taking into account details and changes in the data definition and collection is therefore essential for robust results. The model should be specified to take into account country specific characteristics, e.g., size-dependent technologies.
We used the farm simulation model to analyse the impacts of policy changes like milk or sugar quota abolishment. The results of these first applications point to the large diversity of adjustment reactions across farms. This underlines the need to perform policy impact analyses at the farm level.
4.2008 - 9.2011
Project status: finished