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Agricultural soft budget constraints in new European Union member states
In: Journal of institutional economics, Band 16, Heft 1, S. 49-64
ISSN: 1744-1382
AbstractThis article investigates farm investment behaviour and the presence of soft budget constraints in the agricultural sectors of three Central and Eastern European countries – Estonia, Hungary and Slovenia – using individual farm accountancy panel data for the 2007–2015 period. Gross farm investment is positively associated with gross farm investment for the previous year, growth in real sales and public investment subsidies. Mixed results for debt square and cash flow variables imply that the different investment behaviour of farms pertains to different structures of investment sources among the countries under analysis. A particularly significant negative cash flow coefficient implies strong soft budget constraints for Estonian farms, while insignificant cash flow coefficients imply weak soft budget constraints for Hungarian and Slovenian farms.
The impact of EU accession on farms' technical efficiency in Hungary
In: Post-communist economies, Band 22, Heft 2, S. 165-175
ISSN: 1465-3958
Assessment of the impact of EU accession upon farms' performance in the New Member States with special emphasis on the farm type
The main purpose of this deliverable is to use technical efficiency scores obtained with three distinct methods, Stochastic Frontier Analysis (SFA), Data Envelopment Analysis (DEA), Operational Competitiveness Ranking Analysis (OCRA), based on national Farm Accountancy Data Network (FADN) data, in order to analyse the impact of European Union (EU) accession and the influence of farm classification, more precisely farm type, upon the performance on field crop and dairy farms in three New Member States (NMS), Bulgaria, Estonia and Hungary We provide theoretical and empirical evidence that farm classification is subject for empirical analysis, because using FADN and conceptual (e.g.Hill type) typology may result in considerably different farm structures. The main outcome of this research is that individual farms are not equivalent to family farms as usually assumed in previous research. We find that average size of individual farms is considerably higher than of family farms.
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EU farms' technical efficiency and productivity change in 1990 – 2006
In: 85. Annual Conference of the Agricultural Economics Society (AES) Annual Conference, Warwick, GBR, 2011-04-18-2011-04-20
In this paper we analyse and compare various efficiency indicators for a number of European Union (EU) countries: Belgium, Estonia, France, Germany, Hungary, Italy, The Netherlands and Sweden. The availability of long period datasets between 1990 and 2006, allow us to concentrate on the long time trends in technical efficiency especially in Old Member States. This study is the first which may provide a comprehensive overview on the development in farm level efficiency across eight European countries. Our main results are the following. Generally, all countries have relatively high levels of mean technical efficiency ranging from 0.72 to 0.92 for both field crops and dairy farms. Interestingly the majority of countries have better performance in dairy sectors in terms of higher levels of mean efficiency than in field crop production. A slightly decreasing trend however may be observed for all countries. Technical Efficiency estimates are largely in line with those obtained by previous studies. Stability analysis revealed that in average 60% of farms maintain their efficiency ranking in two consecutive years, whilst 20% improve and 20% worsen their positions for all countries. However, these ratios slightly fluctuate around these values for one year to next year. Mobility analysis ranks countries according to the mobility of SFA scores within the distribution. Farms in New Member States are more mobile than those in EU15. Total productivity changes are analysed in two steps. First, we do not find a definite trend in total factor productivity changes. Second, we address the question whether total factor productivity changes converge or diverge over time. Using panel unit root tests our estimations reveal a convergence of productivity across old EU member countries during analysed period. Finally, we decompose the total factor productivity changes into its main elements. Field crop farm indicators generally present significantly higher volatility than dairy farms. Random effect panel regression of Total Factor Productivity Change on its components shows Technological Change as being the significant positive driver for crop farms, whilst Technical Efficiency Change followed by Technological Change are the most important for dairy farms. In addition we do not find significant impacts of CAP reforms in 1992 and 2000 on total productivity changes.
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EU farms' technical efficiency and productivity change in 1990 – 2006 ; Efficacité technique et changement de productivité des exploitations agricoles européennes 1990-2006
International audience ; In this paper we analyse and compare various efficiency indicators for a number of European Union (EU) countries: Belgium, Estonia, France, Germany, Hungary, Italy, The Netherlands and Sweden. The availability of long period datasets between 1990 and 2006, allow us to concentrate on the long time trends in technical efficiency especially in Old Member States. This study is the first which may provide a comprehensive overview on the development in farm level efficiency across eight European countries. Our main results are the following. Generally, all countries have relatively high levels of mean technical efficiency ranging from 0.72 to 0.92 for both field crops and dairy farms. Interestingly the majority of countries have better performance in dairy sectors in terms of higher levels of mean efficiency than in field crop production. A slightly decreasing trend however may be observed for all countries. Technical Efficiency estimates are largely in line with those obtained by previous studies. Stability analysis revealed that in average 60% of farms maintain their efficiency ranking in two consecutive years, whilst 20% improve and 20% worsen their positions for all countries. However, these ratios slightly fluctuate around these values for one year to next year. Mobility analysis ranks countries according to the mobility of SFA scores within the distribution. Farms in New Member States are more mobile than those in EU15. Total productivity changes are analysed in two steps. First, we do not find a definite trend in total factor productivity changes. Second, we address the question whether total factor productivity changes converge or diverge over time. Using panel unit root tests our estimations reveal a convergence of productivity across old EU member countries during analysed period. Finally, we decompose the total factor productivity changes into its main elements. Field crop farm indicators generally present significantly higher volatility than dairy farms. Random effect panel ...
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