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Hungarian dairy and beef production sector technical efficiency comparsion using DEA
131-138Views:184To 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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Analysis of economic issues relating to the dairy sector, with emphasis on price transmission
61-70Views:145The dramatic decline in consumption after 1990 was an important problem during the analysis of the sector. Even today, consumption is still below the degree that was before the political change, and significantly lags behind the EU level.The importance of this topic is emphasized by the fact that surplus milk could be marketed through the increased domestic consumption; this would create a more stable and calculable situation for farmers. Therefore, I considered it important to reveal what factors and by what shares influence the consumption of milk and dairy products. The relationship, time series and cross-sectional analysis based on national and international databases demonstrate the relationship between the consumption of milk and dairy products and the other determining factors of consumption in Hungary and in the EU-25 through diagrams. I draw the conclusion that there is a medium correlation between the development of the economy, the higher income level and the consumption of milk and dairy products. Just before our EU accession, the dairy sector was one of the most critical industries of Hungarian agriculture, which is why I chose this for my analysis. I regard as a new scientific result the econometric analysis of the asymmetric market conditions in the price transmission approach within our dairy sector between 1995 and 2003. I confirmed and quantified that the market is under an oligopoly and defined the direction of price adjustment. Furthermore, I regard as a new result in the price transmission analysis (also published in the article published with Dr. József Tóth), that the three possible dimensions (elasticity, a symmetry relations,lag) are analysed simultaneously.Therefore,a more sophisticated picture is given on price transmission. The theoretical advantages and disadvantages are verified by an example of a vertical coordination based on the horizontal cooperation in the dairy sector (Alföldi Tej Ltd).
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Integrated agribusiness in the dairy industry of Ukraine: main characteristics and success factors
59-68Views:116Ukraine belongs to the TOP 20 global producers of milk. Despite its position, the Ukrainian dairy industry is suffering from a permanent deficit of raw milk supplied for processing. on average, in 2007–2011 over half of the produced raw milk did not reach the processors. one of the reasons behind this lasting trend is that the structure of initial production of raw milk is dominated by households (having a share of 80%); the latter produce milk mostly for their own consumption and leftovers are sold at marketplaces where they can get more attractive prices. nevertheless, already today we observe results of largescale investments into the industrial production of milk made in the last few years. This article stresses an important place of the dairy industry in the agriculture of Ukraine, as it provides the population of vital food products, many of which are strategic in the export potential. Authors present essential characteristics of the concepts “agro-industrial integration” and “agroholding”, discloses their role and place in the agrarian sector of the economy, and justifies the necessity of the creation an integrated production in the Ukrainian dairy sub-complex. The study aims at identification and description of latest trends in Ukraine’s dairy market. Moreover, authors present a successful Ukrainian example of Milkiland N.V. as one of the TOP 5 players in the Commonwealth of Independent States (CIS) dairy market.
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World importance and present tendencies of dairy sector
119-123Views:156The general objective of this paper is to present the world importance of dairy sector and to illustrate present tendency of milk production, consumption, trade and prices mainly based on FAO data base. World milk production was 711 million tonnes in 2010 and it is expected to increase in the future. The most significant milk producers are the EU(27), the United States and from the Asian countries, India and China. Developed countries give one-third of world milk production, while more than two-third of world dairy herd can be found in developing countries. Milk production growth is a future tendency mainly in China, India, Pakistan, Argentina and Brazil. The average level of consumption of milk and milk products is 103,6 kg/capita/year and it will increase in developing and developed countries as well. The ratio of international trade of milk and milk products to production is 6 percent and itmay expand in the future. New Zealand, the EU(27), theUnited States andAustralia are themajor exporters. There is a strong demand formilk andmilk products among others from the Asian countries, the Russian Federation,Algeria,Mexico, Saudi Arabia and the United States.Analysis of world market price of the most important dairy products it represents a strong recovery from last year, but it still remains 20 percent below its peak value in early 2008. However prices have doubled compared with prices of period of 2002–2004.
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HOUSEHOLDS’ FOOD CONSUMPTION BEHAVIOUR DURING COVID-19 PANDEMIC: EVIDENCE FROM RURAL HOUSEHOLDS IN SOUTH AFRICA
Views:45The food consumption behaviour of households has been affected by the lockdown restrictions that were implemented to reduce the COVID-19 infection rate. This study was aimed at analysing the food consumption behaviour of rural households during the COVID-19 pandemic in South Africa. To achieve this, a simple random technique was used to collect data from 120 in Merry Pebble (MP) Stream Village. Thereafter, an Ordered Probit Model was used to examine the extent to which households have increased, decreased or maintained the same quantity of food consumed during COVID-19. The results indicated that 46.7% of the rural households had consumed less food during COVID-19 pandemic, 32.5% consumed about the same amount of food, and 20.8% consumed more food. The variables that contributed towards a decrease in food consumption are employment status, household size, loss of income, and social relief grants. On the contrary, bulk buying and food parcels had stabilised food consumption, while the number of employed people in a household and food bought from restaurants contributed towards an increase in food consumption during COVID-19 pandemic. With regard to consumption behaviour per food item, fresh produce, meat, snacks and fast food were consumed less during COVID-19, while there was a constant consumption in dairy products, and an increase in consumption of canned food, frozen food, prepared food, grains and water. The study recommends that the government should continue with the economic and social relief programmes that were created during COVID-19, as they play an important role in increasing and stabilising food consumption by rural households.
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Efficiency analysis of dairy farms in the Northern Great Plain region using deterministic and stochastic DEA models
113-122Views:126Running 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 management 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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