The aim of this article is a detailed investigation of financial performance of milk processing companies of Central Europe and the Russian Federation before the Russian embargo. An investigated object is a data base of accounting reports of 5 countries over the period of 2009 -2013. The number of selected companies is 370. The article also involves a short review of the dairy industry condition. In order to compare financial performance of two regions 4 types of criteria i.e. profitability ratios, turnover ratios, liquidity and capital structure were implemented. The differences between the Visegrad group and the Russian Federation were tested through Kolmogorov-Smirnov test at the significance level of 0.05. The main difference between the financial performances is the following: profitability (ROCE) of Russian companies is 3 times higher than in the Central Europe, stock turnover ratio is 2 times lower in the Russian Federation, and credit period is 4 days shorter. Generally speaking, the key difference is higher profitability of Russian companies which may be associated with reduced cost component, different technology of production of dairy products as well as with different capital structure.
The article covers issues of bankruptcy detection in the context of dairy milk processing companies of the Republic of Belarus. Republic of Belarus is exporter of milk products i.e. more than 60% of products are exported abroad. Gross output of milk products is more than 7 thou tons. To keep successful functioning of diary milk processing companies it is important to estimate financial condition of the companies and detect possibility of bankruptcy in time. The article contains 11 models of bankruptcy detection, which provide the basis for the new model taking into account specificity of diary milk processing industry. Suggested methodology of ranking score to detect threat of bankruptcy classifies financial coefficients by reliability for specific diary milk processing company. Condition of the company may be evaluated as crisis, pre-crisis, unstable normal or absolute. This study includes examples of calculation for 6 major diary milk processing companies of the Republic of Belarus. These calculations prove the fact that possibility of bankruptcy is unstable every year. Such condition might be caused by many internal and external factors such as sanctions, embargo, restructuration and loss-making company takeover. Practically implemented this methodology should only be included into the notes of accounting reports of the company. It may be helpful for auditors and external users to estimate stability of the company and risk of bankruptcy and take reasonable decision about management of risks.
Agricultural activity is a strategic direction of the work of agricultural organizations, ensuring food independence and security of the country. In this regard, in modern conditions there is an objective need to improve the management of biotransformation of biological assets and its accounting and control functions. The work defines the objects of management and accounting of agricultural activity: biological assets; agricultural products; income, expenses and financial results from biotransformation of biological assets; government grant related to a biological asset measured at fair value less costs to sell. Recommendations are proposed on the determination and analysis of changes in the fair value of biological assets less costs to sell due to changes in unit prices and the amount of these assets. In addition, methodological aspects of monitoring the effectiveness of the use of biological assets and the production of agricultural products collected from them are identified. Each of these indicators provides indicative indicators, methods of calculation and comparison with similar indicators of the base period or planning. The following are methods for determining individual indicators from the proposed system that allow organization managers at all levels of internal management to make scientifically sound economic decisions to improve the efficiency of the processes of biological transformation of biological assets and agricultural production in agricultural organizations.
The European Union is Russia’s largest agricultural trading partner, and this cooperation has a long history. The imposition of sanctions on certain product groups in 2014 significantly affected trading relations. A gravity model helps us to understand and evaluate the characteristics of agricultural trade between countries. The aim of the research is to compare the agricultural trade flow between Russia and the European Union for the period 2000-2017, find some regularity, and estimate the influence of Russian sanctions using regression models for each European country and for particular types of agricultural products. The dataset sample consists of 12,096 observations and 29 countries. The gravity model of the dependence on Russia of imports and exports from each European country takes into account such variables as GDP (US dollar), distance (km) and dummies (a common border, common language, common history and seaport availability). The findings of the research are as follows: the classical gravity model is feasible for imports from Russia to EU countries. Thus, the smaller the distance between countries, the greater the trade flow between them, and the larger the GDP of both countries, the greater the trade flow between them. In addition, the gravity model is feasible not only for countries, but also for the particular group of products. The results of the cluster analysis show the impact of sanctions on each of 24 groups of products imported into Russia (not just those products that have been under Russian sanctions). It is possible to say that the impact of sanctions is deeper than previously thought.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.