The aim of this study is to analyse the efficiency of Estonian grain farms after Estonia's transition to a market economy and during the accession period to the European Union (EU). The non-parametric method Data Envelopment Analysis (DEA) was used to estimate the total technical, pure technical and scale efficiency of Estonian grain farms in 2000-2004. Mean total technical efficiency varied from 0.70 to 0.78. Of the grain farms 62% are operating under increasing returns to scale. Solely based on the DEA model it is not possible to determine optimum farm scale and the range of Estonian farm sizes operating efficiently is extensive. The most pure technically efficient farms were the smallest and the largest but the productivity of small farms is low compared to larger farms because of their small scale. Therefore, they are the least competitive. Since pre-accession period to the EU, large input slacks of capital have replaced the former excessive use of labour and land. This raises the question about the effects on efficiency of the EU's investment support schemes in new member states.

The success of the decision support systems, developed within GIS with application of different models, depends on the quality of initial data and the models themselves as well as on the possibilities of their linking. The aim of the present study was to analyse the application of different agro-economic models in a computer-based decision support system, developed for optimisation of agricultural land use and fertilisation, on the example of barley production of Kullamaa rural municipality in Estonia. The algorithms used in the agronomical models were obtained from the regression analysis of numerous field experiments. The calculated new agronomical values serve as a basis for the application of economic models. GIS and modelling remain as two separate systems with the capacity for information exchange between them. Profitability of barley cultivation varied in a very broad range in the study area. The optimal fertiliser amounts established for each field allow increasing crop productivity in the region and at the same time preventing environmental pollution due to production intensification. The proposed decision support system can be further supplemented by several agro-economic models and implemented throughout Estonia.

No abstract

No abstract