Andrey Zahariev

This report presents an econometric model of type ARIMAX (0,2,1), developed to forecast and explain the dynamics of the House Price Index for New Dwellings in Bulgaria for the period 2015Q4-2025Q3 on a quarterly basis (40 observations in total). The model is based on a preliminary screening of 16 potential factors across four thematic groups: macroeconomic indicators, income and labour market, credit indicators, and investment and wealth. The objective is to identify statistically significant determinants of housing prices, assess the quality of the model, and formulate conclusions regarding its practical applicability for analysis and short-term forecasting of the new residential property market in Bulgaria.

Special economic zones (SEZs) are widely used to stimulate investment, employment, and industrial growth. Yet their contribution to sustainable regional development remains poorly measured. This is especially true in Kazakhstan, where zone-level assessment is largely absent from regional planning frameworks. This study addresses that gap. We construct a Regional Sustainable Development Index (RSDI) that integrates economic, social, and environmental indicators across nine Kazakhstani regions hosting active SEZs. Economic performance alone gives an incomplete picture. Omitting social and environmental dimensions distorts policy conclusions and masks structural imbalances. Our results reveal sharp differentiation across regions. In the Atyrau region, high investment volumes correspond closely with sustainability gains. This suggests structural coherence between zone operations and broader regional outcomes. The Pavlodar region presents a contrasting case. There, the leading driver of sustainability performance is not investment volume but the reduction of environmental pollution. This finding underscores why disaggregating sustainability components matters—the composite index alone is not sufficient. A comparison against official target indicators identifies both achievements and systematic shortfalls. Investment and employment targets are frequently decoupled: capital attraction does not reliably generate proportional job creation. The social dimension remains the weakest across most zones. Environmental governance shows formal recognition but limited implementation. The RSDI framework offers a practical diagnostic tool for public authorities. It makes imbalances visible before they become entrenched. Beyond Kazakhstan, the index provides a transferable instrument for resource-dependent emerging economies seeking to embed sustainability criteria into SEZ governance and regional planning.

This study examines the relationship between house prices and the factors driving their growth during the transition from a long-standing currency board regime to Eurozone membership. The main objective is to identify and quantify the key factors explaining the variation in house price growth in Bulgaria under conditions of prolonged currency convergence. The study applies a set of econometric techniques, including stationarity tests (ADF and KPSS), diagnostic checks for normality, serial correlation and heteroscedasticity, and robustness checks. The study is based on 40 quarterly observations covering the period 2015Q4–2025Q3 and 48 selected predictors of the General house price index. The final ARIMAX(0,2,1) model is estimated using second-differenced data. The model includes a first-order moving average component and three exogenous regressors: the owner-occupiers’ housing expenditures, the actual rentals for housing in Bulgaria and the homeowners’ utility expenses. The model explains 87% of the variation in house price acceleration, with a comparatively low mean squared error. The diagnostic analysis confirms model adequacy. The three exogenous regressors are statistically significant at the 1% level with strong and stable effects on house price dynamics. No statistically significant relationship is found for the set of traditional macroeconomic, demographic, financial, and sectoral factors. The results show that during Bulgaria’s transition from a currency board to the Eurozone, the sustained house price growth was driven by country-specific factors. The three statistically significant determinants of the house price acceleration in Bulgaria reflect, respectively, the active investment behaviour of homeowners in improving existing properties, the rational assessment by housing market participants of the balance between mortgage and rental payments, and the burden of utility and maintenance costs borne by owners and tenants, depending on property size and energy efficiency. The first factor is most influential for homeowners, the second for tenants, and the third has a similarly significant impact on both groups.

This study examines the relationship between house prices and the factors driving their growth under conditions of transition from a long-standing currency board regime to Eurozone membership. The main objective is to identify and quantify key factors explaining the variation in house price growth in Bulgaria in conditions of prolonged currency convergence. The study applies a set of econometric techniques, including stationarity tests (ADF), Ljung-Box estimation, Shapiro-Wilk test, Kolmogorov-Smirnov test, ARCH LM test, t-tests. The study is based on 40 observations of quarterly data for the period 2015Q4-2025Q3 on 48 selected predictors with an impact on the general house price index. The final ARIMAX(0,2,1) model contains estimates of second-differenced data. The model includes a first-order moving average component and three exogenous regressors: the homeowners' expense index, the average rents of housing in Bulgaria and the homeowners' utility expenses index. The model explains nearly 90% of the variation in the acceleration of housing prices, with a low mean squared error. The diagnostic analysis confirms the adequacy of the model with a lack of autocorrelation in the residuals and successful capture of all systematic information in the data. All three exogenous regressors are statistically significant at the 1% level with strong and stable impacts on the dynamics of housing prices. The non-parametric correlation analysis shows statistically significant monotonic relationships between all regressors and the dependent variable. For the set of traditional macroeconomic, demographic, financial and industry factors, no statistically significant relationship is established. The results show that during Bulgaria's transition from a currency board to the Eurozone, the sustainable growth of housing prices was due to factors of national specificity.

This paper analyses the influence of macro-environment on the efficiency of small and medium-sized enterprises (SMEs) in the Republic of Serbia (RS) in period from 2004 to 2021. The aim of the paper is to identify the factors that have a positive impact on the SMEs’ business i.e. encourage their development, as well as factors with negative impact which limit their further growth. Our starting assumption is that the macro-environment has a positive impact on the development of SMEs due to the fact that number of SMEs and number of their employees and their business performances has been constantly increasing throughout the observed period. By applying regression method, on the sample of 75,000 SMEs (in 2004) to a sample of 109,000 SMEs (in 2021), impact of legal-political, economic, social, technology-related factors on ROA of SMEs in RS is examined. The results show that political instability and inefficiency in relation to the law application are a great hindrance in the development of SMEs in the Republic of Serbia, while the continuous growth of the economic activity (accompanied by an increase in the standard of living), social change (accompanied by collective welfare) and technological improvement have positive effect on the efficiency of SMEs in RS.

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The first quarter of the 21st century marked global engineering progress that surpassed even the wildest predictions of futurist researchers. The modern technological revolution has successfully rediscovered three supporting capital foundations, finding their constant revaluation and development through intellectual capital, industrial capital and financial capital. As a connecting link between them, we can categorically define аrtificial intelligence, with its genetic code – the Machine learning. Estimates for the net effect of the deployment of Artificial intelligence on global GDP are to add a new 15 trillion USD by 2030. This is growth that manifests itself in four directions: improved quality, increased labor productivity, implementation of new customized products and services, and saved time. On this basis, the research debates the effects of the application of artificial intelligence in business in its financial, economic and marketing aspects.

У центрі уваги дослідження є алгоритм поведінки бізнесу в умовах погіршення його економічної безпеки. Алгоритм дозволяє адекватно оцінити ситуацію щодо фінансових загроз і розробити відповідні стратегічні заходи щодо їх усунення. Із метою універсалізації оцінки тенденцій елімінації бізнес-гравців на міжнародних фінансових ринках запропоновано системно-ситуаційну модель із фінансовими гравцями. Мета дослідження – теоретичні та прикладні підходи до розробки стратегій зміцнення економічної безпеки бізнесу в контексті глобальних викликів світової фінансової системи. У статті емпірично встановлено найбільш важливі чинники виникнення та поширення фінансових труднощів усіх задіяних у фінансовій системі суб’єктів бізнесу, що підтверджено результатами реактивної поведінки бізнесу за умов погіршення економічної безпеки та активації імпульсів поширення ймовірності банкрутства. Для універсалізації вимірювання тенденцій усунення бізнес-гравців на міжнародних фінансових ринках досліджено системно-ситуаційну модель, яка базується на консолідації системного й ситуаційного уявлень фінансових гравців щодо інтерпретування фінансової інформації, та адаптовано до умов поведінки інвесторів на міжнародному фінансовому ринку. Для подолання стану розбалансування системи економічної безпеки запропоновано систему критеріїв, використання яких дозволяє послідовно визначити домінанти зовнішнього та внутрішнього впливу на функціональні складові. У ході дослідження доведено, що усунення негативного впливу факторів глобальних фінансових викликів здатне збалансувати систему економічної безпеки бізнесу, вивести її на новітній етап еволюційного реагування та забезпечити подальший сталий фінансовий і соціально-економічний розвиток бізнесу. Сукупність використаних наукових методів стратегування можливостей балансування в системі економічної безпеки й запропонованих емпіричних інструментів усунення негативних факторів зовнішнього та внутрішнього впливів дозволяють створювати нові сценарно-емпіричні підходи до забезпечення зміцнення економічної безпеки бізнесу.

At a solemn joint session, the Faculty Councils of the Faculty of Finance and the Faculty of Economic Accounting at the D.A. Tsenov Academy of Economics celebrated the 70th anniversary of their establishment. By Decree No. 289 of August 20, 1953, effective from September 1, 1953, the Presidium of the National Assembly redistributed and regrouped the specialties at the Higher Financial and Economic Institute in Svishtov, into two faculties - Financial-Statistical and Accounting. Over the years, the faculties have changed their names several times - Financial-Statistical (1953), Financial-Economic (1973), and the Faculty of Finance (1993), and respectively - Accounting (1953), Accounting-Economic (1973), and the Faculty of Economic Accounting (1993). The purpose of this article is to present the results of celebrating the 70th anniversary of the Faculty of Finance and the Faculty of Economic Accounting at the D.A. Tsenov Academy of Economics through the organization and conduct of a prestigious international scientific forum.