"Scientific research" Almanac

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  EFFECTS OF GOVERNMENT BUDGET BALANCE ON ECONOMIC GROWTH

  The necessity of adequate use of public budget as a fiscal instrument for economic regulation is even more tangible in conditions of slow economic growth rate. The debate on whether the public budget can maintain a balance between economic stability and social equity has a long history. Another question is whether budget deficit or budget surplus ... The necessity of adequate use of public budget as a fiscal instrument for economic regulation is even more tangible in conditions of slow economic growth rate. The debate on whether the public budget can maintain a balance between economic stability and social equity has a long history. Another question is whether budget deficit or budget surplus would trigger higher economic growth. The main objective of the empiric analysis is to evaluate the budget deficit/ surplus impact on real economic growth rate by using econometric analysis and comparative analysis between Bulgaria and the other Member States of the European Union as well as the Balkan States (Cyprus, The Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, Slovakia, Slovenia, Romania, Croatia, Greece, Serbia, Turkey and North Macedonia). The specific task is to justify the need to balance the public budget and reduce the budget deficit in order to achieve sustainable real economic growth. The thesis of the research is that balancing public budget and reducing distributive and redistributive government activities contribute to higher real economic growth rate in the analyzed Bulgarian and European economies. The main results of the research prove that reduction of budget deficit and balanced government budget have a positive effect on realized economic growth rate in the analyzed European countries over the period 2007 – 2018.

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  DEEP NEURAL NETWORKS FOR DETECTION OF CREDIT CARD FRAUD

  This publication presents research on the possibility of using Deep Neural Net-works (DNNs) for detection of credit card fraud. The research is based on an open da-taset and aims to determine how the varying number of hidden layers and other archi-tectural parameters (width of each layer, activation functions) affects training and predictive ... This publication presents research on the possibility of using Deep Neural Net-works (DNNs) for detection of credit card fraud. The research is based on an open da-taset and aims to determine how the varying number of hidden layers and other archi-tectural parameters (width of each layer, activation functions) affects training and predictive potential of the network. It also aims to determine how to use generative-adversarial approach efficiently in order to overcome the problem with the imbalance between legitimate and fraudulent transactions, which is crucial characteristic of the datasets related to detection of credit card fraud. The publication presents the results of various experiments, conducted to achieve the stated goals. A number of experiments have been carried out combining network training of various depth of the network and with different parameters of the learning process, for example, activation function and dropout values. The experiments focus on using generative-adversarial approach as a method for oversampling, in par-ticular. The results indicate that deep neural networks with moderate hidden layers, combined with methods for oversampling are performing much better in identifying fraudulent transactions than the classical neural networks, consisting of only one hid-den layer. The results also indicate that using generative-adversarial approach as a method for oversampling is comparable in efficiency to other widely used techniques.

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  TRAINING IN THE DOCTORAL PROGRAM "ACCOUNTING, CONTROL AND ANALYSIS OF BUSINESS (ACCOUNTING)" AT D. A. TSENOV ACADEMY OF ECONOMICS – PROBLEMS AND PROSPECTS

  Achieving an economic and social standard of society is related to the need for highly qualified scientists and specialists. Policies and activities in the field of education and science are a guarantee for such achievement. Higher schools face the problem of developing and continuously improving doctoral education, incl. education in the field of ... Achieving an economic and social standard of society is related to the need for highly qualified scientists and specialists. Policies and activities in the field of education and science are a guarantee for such achievement. Higher schools face the problem of developing and continuously improving doctoral education, incl. education in the field of accounting. The purpose of the research is to outline the existing problems and directions for the development of the doctoral program "Accounting, control and analysis of business activities (accounting)" at D. A. Tsenov Academy of Economics, based on theoretical and empirical study of training in this programme in the context of the European priorities. The main research thesis is that training at D. A. Tsenov Academy of Economics in a doctoral degree in the field of accounting requires integrated management of all aspects of its regulation, organization and practical implementation, which will contribute to increase the competitiveness of the doctoral programme and its position as a leader in the educational market in the country and abroad. By examining the regulatory and strategic documents in the country and within the EU in the field of education at Doctoral level of tertiary education and by outlining the characteristics of the doctoral programme under study, as well as by applying a survey method to study the motivation and satisfaction of those interested in the programme, the state and prospects for its development and opportunities for increasing its competitiveness have been outlined.