Qualitative and quantitative analysis of micro and macro aspects of agricultural finance

In this study, we aimed to identify the factors of the greatest impact on the banking sector liquidity in order to support agricultural business. The main goal of the research is based on the assessment of whether and how the variation of macroeconomic factors affect the exposure of the banking sector to liquidity risk, which is determined by the willingness of the banking sector to respond to the growing financial needs of agriculture. By using the appropriate statistical methods such as correlation and multiple regression analysis, we obtained significant results that can form the basis for monitoring and measuring il/liquidity of the banking sector in relation to the real agricultural sector. The obtained results confirm inflation and unemployment rates as determinants of liquidity in the banking sector. More importantly, this can help to plan, i.e. predict the funds for agricultural sector.

Section: Source: Work Of Authorsmentioning

confidence: 99%

The analysis of macroeconomic determinants of the banking sector liquidity with role in financing agricultural sector

Milić

Soleša²

2017

“…Despite rich tradition and natural resources, agricultural enterprises in Serbia are disabled when it comes to financial investment in new technologies, equipment, knowledge and innovation, and therefore, their competition is seriously impaired, not only in international but the local market as well. Of course, financial mix in the agricultural sector is significantly different from the financial mix in other industries, due to its specific features (Veselinović, Drobnjaković, 2014).…”

Section: Literature Reviewmentioning

confidence: 99%

Financing of permanent working capital in agriculture

Vučković¹,

Veselinović²,

Drobnjaković³

2017

Self Cite

“…Furthermore, these financial indicators are presented by some state institutions dealing with the analysis in this area. For example, the share of the agricultural budget in the national budget is given in (Veselinović, Drobnjaković, 2014) and in (Radović, 2009), while the financial indicators of companies in the agricultural sector are analyzed in (National Agency for Regional Development, 2012). Data on investment in agriculture till the beginning of the global economic crisis can be found in (Pejanović, Milić, 2008), where data source was the Bulletin of the Statistical Office of the Republic of Serbia "Investments of the Republic of Serbia" 10 , while the direct foreign investment data can be found in (Kapor, 2009), where data sources were the National Bank data on direct foreign investment and UNCTAD (United Nation Conference on Trade and Development).…”

Section: The Possibilities Of Using Database In the Analysismentioning

confidence: 99%

Series of agriculture in the statistical office of the Republic of Serbia database

Stojanović

Zečević

Kojčin³

2015

The objectives of this Paper have been to examine which data on agriculture can be found in the Statistical Office of the Republic of Serbia Database, and what are the possibilities for the use of the Database in the research and analysis of agriculture. The Statistical Office of the Republic of Serbia Database physically represents normalized database formed in DBMS SQL Server. The methodological approach to the Paper subject is primarily related to modelling and the way of using Database. The options of accession, filtering and downloading of data from the Database are explained. The technical characteristics of the Database were described, indicators of agriculture listed and the possibilities of using Database were analysed. We examined whether these possibilities could be improved. It was concluded that improvements were possible, first, by enriching Database with data that are now only available in printed publications of the Office, and then, through methodological and technical improvements by redesigning the Database modelled on cloud founded databases. Also, the application of the achievements of the new multidisciplinary scientific field-Visual Analytics would improve visualization, interactive data analysis and data management.