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Efficiency analysis of dairy farms in the Northern Great Plain region using deterministic and stochastic DEA models
Published December 31, 2012

Running any dairy enterprise is a risky activity: the profitability of the enterprise is affected by the price fluctuation of feed and animal health products from inputs, as well as by the fluctuation of end-product prices. Under these circumstances, it is essential for the cattle breeders, in order to survive, to harness the reserves in manage...ment as effectively as possible. In this research the efficiency and risk of 32 sample dairy farms were analysed in the Northern Great Plain Region from the Farm Accountancy Data Network (FADN) by applying classical Data Envelopment Analysis (DEA) and stochastic DEA models. The choice of this method is justified by the fact that there was not such an available reliable database by which production functions could have been defined, and DEA makes possible to manage simultaneously some inputs and outputs, i.e. complex decision problems. By using DEA, the sources that cause shortfall on inefficient farms can be identified, analysed and quantified, so corporate decision support can be reinforced successfully. A disadvantage of the classical DEA model is that the stochastic factors of farming cannot be treated either on the side of inputs or outputs; therefore, their results can be adopted with reservations, especially in agricultural models. This may have been because we could not discover that many agricultural applications. Considering the price of inputs and outputs as probability variables, 5000 simulation runs have been done in this research. As a result, it can be stated that at which intervals of the input and output factors can become competitive and the fluctuation of these factors can cause what level of risk at each farm.

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A Quantitative Assessment of the Rurality and an Efficiency Analysis of Emigration in Romania
Published December 13, 2018

In Romania, as in many other Eastern European countries, the early 1990s were marked by a significant emigration from the countryside as a consequence of the transition from a centralised economy to an open one and due to key changes in the political framework. The permanent emigration has predominantly been concentrated in rural areas where mu...ltiple socio-economic variables such as GDP per capita, unemployment, and public financial subsidies aimed at supporting people at risk of severe deprivation and poverty have all had a direct effect on rural depopulation. The rurality is a complex theoretical construct comprising many items and variables and is, therefore, difficult to define in a concise manner. The aim of this paper is to assess the evolution of emigration in Romania between 2001 and 2016 through a quantitative approach, estimating an index of rurality for the same period composed of a set of socio-economic variables having a direct or indirect nexus to it. In the first phase of research, a matrix of correlation and a multiple regression model has been used in order to estimate the direct links among all investigated variables. Following the quantitative methodology, in the second phase Partial Least Square Structural Equation Modelling (PLS-SEM) has been used in order to assess the main cause-effect relationships among a few selected endogenous variables and a set of socio-economic items. Furthermore, using a non-parametric Data Envelopment Analysis (DEA) output-oriented model, this research has assessed the efficiency in terms of permanent emigration from Romania estimated as an output to minimise and not as an output to maximise, as investigated by traditional efficiency approaches. In terms of efficiency, financial subsidies allocated by national authorities and the level of per capita Gross Domestic Product have acted directly on the level of emigration. The index of rurality in 2016 has been influenced in particular by he pluriactivity in farms in terms of agritourism, the dimension of farms in terms of land capital endowment, and the level of GDP per capita.

JEL Classification: Q10; Q18

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Dutch, Hungarian and German dairy farms technical efficiency comparison
Published June 30, 2011

The abolishment of the dairy quota system in the EU is expected to increase competition across dairy farms in Europe. Assuming a common price for milk in the EU, only the most efficient farms will survive in the new environment. The main objective of the paper is to compare dairy farms in Germany, The Netherlands and Hungary about their efficiency. In the first part of the research, the efficiency is measured by partial efficiency indexes using one dimensional efficiency measuring. In the second part, the Data Envelopment Analysis (DEA) have to be used to measure efficiency in a multidimensional space, using six inputs and two outputs. It appears from the results that the highest efficiency farms are in the Netherlands, and then Germany and Hungary follow. If we want to eliminate the low sample size effect, we can assume a common frontier, which decreases the efficiency scores a bit, and makes the Hungarian results more reliable. With respect the abolishment of the dairy quota system, our results suggest that the Dutch farms are the most efficient, thus probably they will increase their production after the quota system. But because the size of the country we cannot expect dramatic changes in the European Dairy market. The Germans farms efficiency is lower, but their efficiency is also lower, so we won’t expect high increase about the dairy supply. The Hungarian dairy sector is not so efficient like the Dutch, and the size of the sector has also small among the European countries, thus if they want to survive the quota system demolishing, they have to increase their technical efficiency.


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Using DEA to evaluate efficiency of higher education
Published September 30, 2009

The aim of the higher education reform process both in Hungary and in the European countries is establishing a competitive, qualitative higher education with efficiently operating institutions. The question of efficiency needs increased attention not only because of the decline of the state support but also the rapid raise of the student mass. ...In the educationsystemit’snot easy to measurethe output of the services.The situation is more complicated if an organisation or a sector has multiple inputs and outputs. In this case a possible method of determining efficiency is Data Envelopment Analysis. In my paper I’d like to introduce this method and use it to compare the efficiency of higher education systems. urthermore I am examining whether their efficiency is influenced by the extent of the contribution of the state and the private sector or socio-economic factors like GDP per capita and education level of parents.


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