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Practical use of certain tools to assess the financial instability of the region's economy

Granitsa Yu.V. Institute of Economics and Entrepreneurship, Lobachevsky State University (UNN), Nizhny Novgorod, Russian Federation ( ygranica@yandex.ru )

Journal: Regional Economics: Theory and Practice, #8, 2019

Subject This article explores the economic and statistical tools adequate for predicting the financial instability of the regional economic system.
Objectives The article aims to analyze the existing methods and develop original ones for assessing the instability of the region's economy.
Methods For the study, I used statistical, calculation and constructive, economic and mathematical methods, and the methods of data analysis.
Results The article identifies a set of factors contributing to the onset of recession and presents an adequate logit model for its prediction. It shows the volatility of economic indicators affecting the financial instability of the region's economy and builds three alternative models to determine the variability of economic indicators.
Conclusions Fractal analysis and calculation of the cost measure of risk show a significant effect when analyzing the volatility of economic indicators. The logit models used provide a significant result if the data of social and economic indicators that characterize the social sector of the region's economy combined with the business sector is defined as regressors.


Using distributed lag models to predict regional budget revenues

Granitsa Yu.V. National Research Lobachevsky State University of Nizhny Novgorod (UNN), Nizhny Novgorod, Russian Federation ( ygranica@yandex.ru )

Journal: Economic Analysis: Theory and Practice, #6, 2020

Subject. The article addresses projections of regional budget revenues, using distributed lag models.
Objectives. The purpose is to review economic and statistical tools that are suitable for the analysis of relationship between the revenues of the regional budget system and regional macroeconomic predictors.
Methods. The study draws on statistical, constructive, economic and mathematical methods of analysis.
Results. In models with quantitative variables obtained under the Almon method, the significant predictors in the forecasting of regional budget revenues are determined mainly by the balanced financial result, the consumer price index, which characterizes inflation processes in the region, and the unemployment rate being the key indicator of the labor market. Models with quantitative variables obtained through the Koyck transformation are characterized by a wider range of predictors, the composition of which is determined by the peculiarities of economic situation in regions. The two-year forecast provides the average lag obtained during the evaluation of the models. The exception is the impact of unemployment rate, which is characterized as long-term.
Conclusions. To generate forecasts of budget parameters, the results of both the Koyck method and the Almon method should be considered, though the former is more promising.


Methods to identify and quantify the relationship between regional economic indicators

Granitsa Yu.V. National Research Lobachevsky State University of Nizhny Novgorod (UNN), Nizhny Novgorod, Russian Federation ( ygranica@yandex.ru )

Journal: Economic Analysis: Theory and Practice, #12, 2019

Subject The article analyzes methods for identifying and quantifying the relationships between economic indicators to predict the financial instability of regional structures.
Objectives The purpose of the study is to investigate economic and statistical tools, which are adequate for the analysis of interrelations between regional economic indicators.
Methods I employ statistical, calculation-constructive and economic-mathematical methods, and corresponding methods of data analysis.
Results Estimating the interrelations of absolute values of economic indicators with the help of the panel data analysis model with random effects gave grounds to identify significant regressors for assessing the volatility of per capita income. Fixed investments have a reverse effect on the volatility of per capita income. Comparable dependence is obtained in the linear model, where the growth rates of economic indicators are determined as regressors. The estimation of interrelations of factors, using the logit model showed that the most significant direct impact on the process of recession is characterized by per capita income, the share of influence of the standard regressor value is 46 percent. The standard indicator of the volume of deposits with the share of influence of 25% also show inverse dependence.
Conclusions Economic indicators of regional statistics clustered by Federal district should be evaluated, using the panel data analysis models with random effects. The preferred way to eliminate multicollinearity is the method of principal components. If compared with the Belsley method, it enables to build models with a full set of original economic determinants.


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