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A Study of the Impact of the Main Factors on the Financial Condition of the Agricultural Holdings
J. BUMBAROVA-NACHEVA
Резюме: The aim of the article is to determine the grade of the existing reference between the obtained financial results in the agricultural holdings and the main factors, which lead to these results. For the solution of the so conceived problem are applied the means of the multidimensional regression and correlation analysis. On the base of the performed three factors regression model, describing the linear relation between the profit size and the chosen financial factors are proved basic dependences and possibilities for the model’s validity for practice application. The study was carried out on the basis of averaged data presented by the National Statistical Institute (NSI) for 102 agricultural holdings from the Plovdiv Region between 2003¦2006. The factor ‘profit’ was used as an indicator for measuring the financial condition of the holdings, while their non-current and current tangible assets and their fixed and current liabilities were used as main factors having influence on the financial result. To prove the working hypothesis that the above factors determine to a large extent the amount of the generated profit, the method of successive elimination of the factors (predictors), i.e. backward elimination, was used. Initially, all predictors are included in the multi-factor regressive model which indicates the hypothetical connection between the dependent variable and the chosen factors. At the next step, one of the factors, which according to a criterion chosen in advance does not contribute sufficiently to the higher level of adequacy of the model and the regression factors is eliminated. In this manner, the degree of correspondence existing between the financial results generated in the agricultural holdings and the factors on which these results depend is determined.
Ключови думи: agricultural farms; financial condition; regression and correlation analysis
Дата на публикуване: 2024-09-03
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