Ganna Kharlamova

The article contains a thorough study of tourist flows in Ukraine during the last 18 years. The tendencies of the development of international tourism during the last 20 years and their influence on the development of tourism in Ukraine have been explored. Particular attention is paid to the analysis of inbound tourist flows. The negative dynamics of tourist arrivals in Ukraine led to the construction of a forecast model for the development of this component of tourism activity with the aim of an objective assessment of future tourist arrivals and the adoption of effective management decisions on improving the situation of tourism in Ukraine. Tourist destinations today are rigorously competing for consumer interest in tourism products. In view of this, tourist facilities operating in the tourist market place particular emphasis on the elements of tourism marketing (product, price, distribution, advertising, human capital, actual data, processes).
Modern forecasting systems and methods have been used to build a forecast of tourism development in Ukraine and, in particular, arrivals of foreign tourists to Ukraine. An analytical forecasting model was built by the system of CurveExpert in the form of a polynomial function, analytical forecasting models were built by the system of computer algebra Maple in the form of piecewise linear and piecewise polynomial functions. Numerical prediction models in the MathCAD system using different types of spline-interpolation and predictive functions have been constructed. A comparative analysis of the results of forecasting in different systems was carried out. The results of the comparative analysis give confidence in the development of inbound tourism in Ukraine.

Actuality
The concept of output gap plays an important role in traditional macroeconomic theory, applied research and monetary policy.

Goal
The paper reveals analyses of the potential economic development in Ukraine and in some countries of the world under limited information. Thus, the practical goal is to consider the best modelling approach for the possibility to regulate GDP in Ukraine, as it has been experienced in other countries of the world.

Method
The research is realized with the help of economic-mathematical modelling of GDP gap based on the analysis of the production function, statistical methods of distinguishing the trend component, one-dimensional filtration, multidimensional filtration.

Results
Practical importance of the paper includes implementation of methods for estimating potential GDP and the GDP gap, in particular, the authors proposed to use an approach based on the production function for the potential growth of European countries modelling. The model reveals that for the Eurozone countries, in the short term, it is not expected that the economy will reach its potential level. The negative forecast is explained by the fact that the Eurozone has been severely affected by the debt crisis. There has been a significant increase in the gap in production volumes, which in turn led to deflation. Despite the uncertainty in the assessment of potential GDP and GDP gap for Ukraine the multidimensional method provided the best modelling result. Thus, it is disclosed that Ukraine is under the growing wave of the business cycle, but not in the synergy with the EU dynamics.

Strengthening the integration of higher education, research, and innovation is a crucial requirement of time. The entrepreneurial university today is considered and analyzed as a promising model for their combination. The educational and scientific systems of many countries are faced with the task of converging all vertices of the “knowledge triangle.” The problem of Ukrainian educational and scientific system is a necessity to implement the concept of formation of the innovation and entrepreneurial model of a modern university, which will enable the effective implementation of administrative reforms in this field. The article aims to analyze the impact of innovative environmental factors on the development of entrepreneurial universities in Ukraine, based on correlation and panel regression analysis. The method of quantitative analysis (panel regression) is used to formulate the key results of the article. The results show that the growth of government expenditures by 1% leads to an increase in the Global Innovation Index by 0.375 in 4 years. Also, every additional 1% of people working with new technologies increases the level of Global Innovation Index by 0.75 annually. Despite European trends, Ukrainian educational environment does not contribute to the development of innovation and entrepreneurial universities (the education expenditures are ineffective). The research provides a vector for understanding the implementation of the most effective strategies of promising innovation and investment development of education and science in Ukrainian universities, considering their existing potential and contemporary world trends of development.

The process of world globalization, labor, and academic mobility, the visa-free regime with the EU countries have caused a significant revival of migration processes in Ukraine. However, there is still the research gap in the most informative, and, at the same time, accurate method of the assessment and forecasting of the migration flows. Thus, the object of research is migration processes (mostly emphasizing the emigration flows). The motives, causes of emigration processes, and their relationship with the economic state were analyzed. The impact factors of external labor migration on the economy of the host countries were revealed, particularly the negative and positive impacts of emigration on the socio-economic situation in Ukraine and the migration attitude of Ukrainians were assessed.
The main result of study is further development of the econometric model for forecasting the number of emigrants from Ukraine to other countries in the nearest future. The model considers the factors of minimum wage lavel in Ukraine, the number of open vacancies in the countries of Eastern Europe, and the level of competition for jobs. According to the results of forecasting based on Maple computer algebra system and Microsoft Power BI analytical platform, by the end of 2019, the number of emigrants from Ukraine supposed to be the largest in the last four years and to reach the estimates in the range from 2,444 to 2,550 million people, which may indicate a new third wave of emigration processes.

The difference in the GDP levels is crucial for the macroeconomic forecasting to develop adequate and supportive fiscal and monetary policies. Most mismeasurements under current geoeconomics challenges can be explained by the difficulty in predicting recessions and the overestimation of the economy’s potential capacity. The research aims to consider the GDP gap’s effectiveness for the possible forecasting of the monetary policy, particularly the central bank’s interest rate. The study uses quantitative methods, particularly VAR modeling. The VAR model is chosen as a proven useful tool for describing the dynamic behavior of economic time series and forecasting. The data sample is chosen as Eurozone, the United States, and Japan. The similarity is detected on output gaps implementation in the considered states; however, the variety in the responses to the financial crisis is revealed. This difference is due to the different sensitivity of economies on the impact of monetary instruments. In particular, the Japanese economy has a relatively low level of sensitivity to changes in monetary instruments. In terms of the reactions of central banks to the current economic crisis caused by COVID-19, then due to the global lockdown and the incredible decline in economic activity, almost all countries are in a situation of negative GDP gap according the paper’s approach. However, the measures to mitigate it will vary in different states.

Acknowledgment
The paper is done in the framework of scientific faculty research 16КF040-04 “Steady-state security assessment: a new framework for analysis” (2016–2021), Taras Shevchenko National University of Kyiv (Ukraine).