Analysis and Forecasting of Budget Accounting Systems Using Machine Learning Algorithms
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| Pages: | 13 : 24 |
| Abstract: |
The paper debates and amplifies a topic of great interest, related to the current socio-economic context of the field, trying to establish new relationships of interdependence between social-economic factors and the evolution of income and expenditure. Through this paper we will address and analyze aspects of the evolution of income and expenditure, finding certain measurable links between socio-economic factors and the evolution of income and expenditure, finding and expressing strong or weak relationships between cause (socio-economic factors) and effect (amount of income and expenses). The present research was motivated by the use of modern analysis and prediction elements for modeling economic phenomena and for achieving a more accurate decision support. An important objective is to analyze the applicable regression methods in relation to the implementation of Machine Learning algorithms. The public budget is a perfect source of Big data for the implementation of a Machine Learning algorithm, because it allows us to define multiple dimensions for the same information contained. The conclusions and proposals resulting from the analysis of the causality and the interdependence of the analyzed factors are intended to represent a decisional support for the state institutions and at the same time an element of understanding and forecasting of the economic phenomena. |
| JEL classification: | M41, O21, H61, H68, H83 |
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