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Risk and risk management in Hungarian sheep production
Published December 31, 2007
61-65

The aim of this paper is to give an overview of the risk attitudes of Hungarian sheep producers regarding the changes they have had to go through since the political changes of 1989–1990. Moreover, the objective of this study is to strengthen the empirical basis for risk analysis by identifying the importance of farmers’ risk attitudes. The... results of a nationwide survey of over 500 sheep farmers presented a framework of risk attitudes, risk sources and applied risk management techniques of livestock producers.

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40
9
Factors influencing the gross value added in the sheep production chain
Published December 31, 2012
141-146

The competitiveness of the sheep sector in East Europe has been decreasing from year to year. The value added in the sector is not generated in the countries as a high proportion of the lambs are exported. For example, in Hungary, 95% of the lambs, unnecessary for replacement, are sold at an average weight of 21 kg and are slaughtered abroad. A... stochastic model was constructed to investigate the connections between the cycle phases of the mutton production. Three modules were distinguished, the lamb production, fattening and slaughtering-processing sub-modules. The aim of our study was to identify the gross value added generated in the three sub-modules and to analyse the main factors influencing its volume using the conditions in Hungary as an example. The major hypothesis of our research was that the profitability of the production chain is mainly determined by the breed. The results showed that, considering market prices, the gross value added in the processing module was mostly influenced by the number of lambs sold per ewe per year at the bottom level of the mutton product chain. The next most important factors were the weight gain in the lamb producing and fattening sub-modules and dressing percentage in slaughtering-processing sub-module. Contour plots were constructed which help to describe the relationship among analyzed factors. Using the contour plots, the gross value added for different combinations of these factors might be forecast.

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49
14
Role of innovations and knowledge – infrastructure and institutions
Published October 30, 2010
7-10

There is a well known saying: Research converts money into knowledge, innovation converts knowledge into money. The knowledge-based economy has four pillars: innovation, education, the economic and institutional regime, and information infrastructure. Transformation towards a knowledge-based economy will necessarily shift the proportion and gro...wth of national income derived from knowledge-based industries, the percentage of the workforce employed in knowledge-based jobs and the ratio of firms using technology to innovate. Progress towards a knowledge-based economy will be driven by four elements: human capital development, knowledge generation and exploitation (R&D), knowledge infrastructure. Increased investment in these four areas will certainly have an impact. National experience, however, suggests that an incremental approach will not work. Nations that have achieved accelerated growth in outputs and capabilities have acted decisively, targeting investments in areas of strategic opportunity. The organizational and infrastructural improvement of research requires supranational cooperation and the promotion of the free movement of knowledge. Therefore, the EU decision on the establishment of the European Institute of Innovation and Technology (EIT), which ensures that the GDP proportion for research and development (R&D) shall achieve 3% stipulated by member states in the long run, is particularly welcome.

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