Agricultural Economics, 2010 (vol. 56), issue 2

Classification of companies with theassistance of self-learning neural networks

Vladimír KONEČNÝ, Oldřich TRENZ, Eliška SVOBODOVÁ

Agric. Econ. - Czech, 2010, 56(2):51-58 | DOI: 10.17221/60/2009-AGRICECON  

The article is focused on rating classification of financial situation of enterprises using self-learning artificial neural networks. This is such a situation where the sets of objects of the particular classes are not well-known. Otherwise, it would be possible to use a multi-layer neural network with learning according to models. The advantage of a self-learning network is particularly the fact that its classification is not burdened by a subjective view. With reference to complexity, this sorting into groups may be very difficult even for experienced experts. The article also comprises the examples which confirm the described method functionality...

The methods of valuation in agricultural accounting

Jaroslav SEDLÁČEK

Agric. Econ. - Czech, 2010, 56(2):59-66 | DOI: 10.17221/1487-AGRICECON  

This paper deals with the valuation of the biological assets and agricultural production. There are analyzed two approaches: Czech and international. The International Accounting Standards are emulative of more authentic presentment of economic processes in agricultural activities than Czech accounting legislation. From the comparison the both approaches accrued some differences, which can influent the financial statements of enterprises. The causation of main difference appears an application of fair value, which is prescribed for biological assets and agricultural production in international accounting standards. In international accounting standards...

Perceived risks and safety concerns about fluid milk among Chinese college students

Pei XU, Shi ZHENG, Mesbah MOTAMED

Agric. Econ. - Czech, 2010, 56(2):67-78 | DOI: 10.17221/18/2009-AGRICECON  

The study uses the questionnaire information collected through personal interviews with college students at a large university in Beijing, China to discuss the students' perceived milk risks and their milk safety concerns. We analyzed the milk risks perceived by students and found out that the top three listed risks are: (1) the use of low quality materials in milk packaging; (2) bacteria contaminations in milk production and processing; and (3) unsafe milk caused by the use of cow antibiotics. The binomial probit regression analysis shows that the health conscious milk consumers who consume milk frequently are likely to be worried about the safety...

Productivity of the hired and family labour and determinants of technical inefficiency in Ghana's fish farms

Edward Ebo ONUMAH, Bernhard BRÜMMER, Gabriele HÖRSTGEN-SCHWARK

Agric. Econ. - Czech, 2010, 56(2):79-88 | DOI: 10.17221/38/2009-AGRICECON  

This paper examines the productivity of hired and family labour and determinants of technical inefficiency of fish farms in Ghana. A modified Cobb-Douglas stochastic frontier production function which accounts for zero usage of family and hired labour is employed on cross-sectional data of 150 farmers collected in 2007. The results reveal that family labour, hired labour, feed, seed, land, other costs and extension visit have a reasserting influence on fish farm production. Findings also show that family and hired labour used for fish farming production in Ghana may be equally productive. The combined effects of operational and farm specific factors...

The efficiency analysis of organic and conventional olive farms: Case of Turkey

M. Metin ARTUKOGLU, Akin OLGUN, Hakan ADANACIOGLU

Agric. Econ. - Czech, 2010, 56(2):89-96 | DOI: 10.17221/620-AGRICECON  

This paper investigates technical and economically efficiency of 62 organic and 62 conventional olive producing farms in Turkey. According to the study results; by using the CRS model which is input and output-oriented, the average technical efficiency of organic olive farms is 67.68%, the average technical efficiency of conventional olive farms is 47.93%. The technical efficiency of the output-oriented VRS model is 74.78%, and the technical efficiency of the input-oriented VRS model is 93.46%. Also, considering the same model, the average efficiency of the conventional olive farms in the input and output are 59.58% and 94.97%, respectively. Therefore,...