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Cost analysis of pig slaughtering: A Hungarian case study
121-129Views:245The scale of Hungarian slaughterhouses is small in international comparison and the cost of slaughter and cutting a pig of average live weight is relatively high at 16.1-19.4 EUR on average. The aim of this study is to evaluate the cost of pig slaughter and cutting through the case study of a medium-scale plant in Hungary. Based on data from the enterprise, a calculation was performed in relation to the “output” quantity of pig slaughter and cutting, as well as its value and the cost and cost structure of processing. The capacity of the examined plant and its utilisation were analysed and cost reductions were estimated for various increases of output. In 2015, the direct cost of slaughter and cutting was 18.9 EUR per pig for the medium-scale plant which processed 100 thousand pigs. When the purchase cost of pigs is excluded, labour costs accounted for the highest share (30%) of costs, followed by services (29%) and energy costs (21%). For this reason, the level of wages and employer’s contributions has a rather high significance. Analysis showed that significant increases in Hungarian minimum wage and guaranteed living wage in 2017 resulted in an estimated 7% increase in the cost of slaughter and cutting compared to 2015, despite the decrease of contributions. The capacity utilisation of the plant was a low 28% when compared to a single 8-hour shift considered full capacity. The cost of slaughter and cutting was estimated to be reduced to 14.2-17.0 EUR per pig if the plant operated at full capacity. This may be considered a lower bound estimate of cost because there are numerous restricting factors on optimising capacity utilisation, such as: 1) number of live animals available for purchase and related logistics; 2) cooling capacity availability; 3) labour availability; 4) market position of the enterprise and potential for marketing additional pig meat products. Enterprises of this scale are recommended to consider producing more value-added products and, accordingly, investing in product development.
JEL Classification: Q13, Q19
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Hungarian dairy and beef production sector technical efficiency comparsion using DEA
131-138Views:223To examine and compare the technical efficiency of dairy sector and the beef sector, this research introduced the main indicators of milk and beef production in the world, EU and Hungarian aggregates. Based on the data it can be said that the milk and beef production of Hungary does not occupy any significant position in the world as well as in the European Union neither today nor even in the past. If Hungry must compete in the European counties and international market, their dairy sector must focus to increase of their production efficiency as the key breakthrough point. This paper we compared technical efficiency of both dairy and beef sectors in total, for the year 2014 and 2015 separately and based on the farm size. The specific objectives of the research are: comparing dairy and beef farms efficiency in Hungary. Based on the results, we can determine which sector in Hungary is more effective. The second objective is to compare the efficiencies of both the sectors in 2014 and 2015 separately and from the results we can determine which year was more effective in terms of production efficiency and the third objective of the research is technical efficiency comparison of certain economic sizes for both sectors. In the research, we used (KOVACS, 2009) deterministic (DEA) model adapted to the Hungarian dairy farms and beef farms. For the dairy farms milk and dairy products as well as meat (other income). The input factors originated from the domestic AKI - FADN database. Summarizing the results of the research it can be conclude that the dairy sector is more effective than the beef sector in Hungary. In terms of years compared 2014 was more effective for both sector as compared with 2015. In regards to the farm size almost the same result in evaluating the scale of efficiency, which means that large economies can in most cases, manage resources more efficiently than small farms. In the examined years, based on the results of the DEA model, the VRS technical efficiency of the test for these two years was 72.90% for the dairy farms and 63.60% for the beef farms, which means that the dairy sector is more efficient than the beef sector in Hungary. The VRS technical efficiency of the research was 82.10% in 2014 and 75.10% in 2015 for the dairy farms and 77.50% in 2014 and 68.90% in 2015 for the beef farms, which means that both the dairy sector and the beef sectors followed the same trend and were more efficient in 2014 compared to the efficiency in 2015. The large size dairy farms were most effective in Hungary in the examined period (90.90%). VRS technical efficiency for small farms is 88% and the total number of small, the technical efficiency medium farms was 72.80% For the beef sector VRS technical efficiency for small farms is 71.30% and the technical efficiency medium farms was 74.40% and 70% of the beef meat producing farms in Hungary are medium sized. So, the conclusion is the small size dairy farms have a higher VRS efficiency than the small size beef farms whereas medium sized beef farms had higher VRS efficiency than the medium size dairy farms. As a conclusion, both dairy and beef sectors in Hungary have the potential to overcome technology and knowledge constraints and attain the upmost attainable productivity level through improvements in; farmer volume of production i.e. output, beef cattle technologies, and advertising, and the efficiency of the technology transfer process.
JEL Code: Q13
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Diversification strategies and their impact on farm performance
57-61Views:161The objective of this study is to identify factors determining the economic performance of agricultural holdings in Italy, with specific attention to the impact of the adoption of on-farm diversification strategies, namely income diversification and product differentiation. The adoption of these kinds of strategies has been increasingly recognised as a viable business option in agriculture as they allow better allocation of farm resources and an increase in the quota of value added retained on farms and therefore not passed on to other agents operating at the end of the food supply chain. By using a panel of professional Italian farms over the time period of 2003-2009, we estimate random effect, ordinary least square and quantile regression models to estimate the impact of income diversification and product differentiation strategies on the levels of farm income per unit of labour income. Our findings show that scale economies are important positive determinants of farm economic performance. On the contrary, when the family play an important role in the farm business, economic performance is worse. Finally, we do not find evidence of a statistically significant impact of the adoption of income diversification and product differentiation strategies. This latter result may be interpreted as a signal that farms use these strategies as risk management tools rather than as income increasing ones.
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