Analysis of the Current State of the Investment Climate in Russia

The general economic situation of the countries can be characterized by one important factor – the investment climate. A favorable investment climate is the most important condition for attracting investment flows and subsequent eco-nomic growth in the country. Important criteria for making decisions in the field of investment activity are the assess-ment of the investment climate at the macro level. The article analyzes the current state of the investment sphere and the investment climate in the Russian Federation. The study provides an assessment of the dynamics of the number of foreign direct investment projects in the country from 2015 to 2019, the main investment donor countries for Russia as of 2019, and the most attractive industries and sectors of the Russian Federation for 2010–2019. The article considers the main regions-recipients of foreign investments. The study contains an analysis of the implementation of investment projects in the Russian Federation as of 2019. When studying the investment climate of the Russian Federation, it is necessary to take into account the corona virus pandemic, since this crisis could not but affect the volume of invest-ments and the implementation of investment projects. That is why the data for 2020 are considered separately: the impact of the corona virus infection on the implementation of investment projects, the factors of the corona crisis af-fecting investment flows, and the forecast state of the investment market at the end of 2021. The article presents the megatrends that have intensified after the pandemic and affect the investment climate of countries.

FORMALIZATION OF SAFETY ASSESSMENT AND MANAGEMENT

The article is the first in a series of articles, united by a single theme of improving the organization of the country's security management system. The article is limited to the general principles of the organization of security management of the country. It is proposed to divide all activities and values of the country into three types of potentials, which are characterized by quantitative or objective formal parameters and provide for different types of management influences; describe with potentials the current, target, forecast state of the country and allowable limitations of potentials. It is proposed to divide the components of complex parameters into three groups: positive potentials, which should be increased, negative potentials, which should be reduced, and passive potentials, which are not formalized or the relation to which is not defined. Of these components, positive and negative components have an impact on decision-making. The passive component can eventually be transformed into a positive or negative component. Examples of application of the offered approach are resulted.

Model for making decisions on renewal the railway rolling stock of a transport organization

Background: At present, there is an urgent problem of renovation of rolling stock characterized by a high degree in Russia. The leading position in the country's transport system belongs to railway transport. In the context of declining demand for transportation investments in railcars, which represent a significant amount of capital investment, require reasonable management decisions. Aim: is to work out a decision-making model for renewal the transport organization's railway rolling stock. Methods: of technical, economic, investment and financial analysis, decision tree, graphical modeling, system approach. Results: The basic components of the decision-making model are determined. The key indicators of railway rolling stock renewal are defined, reflecting the criteria for making managerial decisions in the field of operational, investment and financial activities. A graphical model is proposed that interprets the decision support system for purchasing new railcars. Conclusion: Using the proposed model of decision-making in the field of renovation of rolling stock allows to transfer this process to a qualitatively new level, based on the results of an objective assessment of the current and forecast state of the management object according to various alternative scenarios and based on the selection of the rational decision by comparing the expected results for each of the considered alternatives and analysis degree of their compliance with the determined goals due to its versatility and complexity.

ANALYSIS AND FORECASTING OF THE PUBLIC BUDGET EXPENDITURE OF UKRAINE

Introduction. In modern conditions of growing crisis phenomena in the global economy, the development of each country's economy is inevitably accompanied by the need to overcome such global problems as aggravation of inter-country competition in the world energy market, financial expansion of transnational financial corporations, global warming and the global food crisis, migration of the population between rich and poor countries, information wars between leading global players in the sphere of influence. The combination of these and other factors in the context of deepening globalization with each one increases their influence on the development of the national economy of developing countries and post-Soviet countries, which stipulates them to forecast state expenditures in terms of separate articles, to budget them in short and long-term periods, to adjust plans in accordance to their execution or non- execution. Purpose. The article aims to forecast the expenditures of the state budget of Ukraine for 2018-2021 with the help of a regressive multivariate model on the basis of annual social and economic macro indicators of Ukraine. Method (methodology). The general scientific and economic methods are used for the achievement of the given task. They are the method of system and structural analysis, method of analysis and synthesis, method of scientific generalization, statistical method, method of comparative analysis, method of analogies and modelling. Methods of econometric analysis, such as regression method, are also used in this research. Results. The results of the study proved the feasibility of using an econometric approach to assessing the expenditures of the state budget. Public debt, unemployment rate and GDP deflator are recommended to be used as interdependent indicators. According to the results of regression analysis it is established the relationship between these indicators is. On the basis of the model, the forecast has been made for 2018-2021 years. A comparative description with the proposed forecasts has been made by the Ministry of Economic Development and Trade of Ukraine. The directions for improving the optimization or effective use and sending of budget expenditures with the aim to improve the quality of auditing the use of budget funds have been proposed.

Inflation method for ensemble Kalman filter in soil hydrology

The ensemble Kalman filter (EnKF) is a popular data assimilation method in soil hydrology. In this context, it is used to estimate states and parameters simultaneously. Due to unrepresented model errors and a limited ensemble size, state and parameter uncertainties can become too small during assimilation. Inflation methods are capable of increasing state uncertainties, but typically struggle with soil hydrologic applications. We propose a multiplicative inflation method specifically designed for the needs in soil hydrology. It employs a Kalman filter within the EnKF to estimate inflation factors based on the difference between measurements and mean forecast state within the EnKF. We demonstrate its capabilities on a small soil hydrologic test case. The method is capable of adjusting inflation factors to spatiotemporally varying model errors. It successfully transfers the inflation to parameters in the augmented state, which leads to an improved estimation.

Inflation Method for Ensemble Kalman Filter in Soil Hydrology

The ensemble Kalman filter (EnKF) is a popular data assimilation method in soil hydrology. In this context, it is used to estimate states and parameters simultaneously. Due to unrepresented model errors and a limited ensemble size, state and parameter uncertainties can become too small during assimilation. Inflation methods are capable of increasing state uncertainties, but typically struggle with soil hydrologic applications. We propose a multiplicative inflation method specifically designed for the needs in soil hydrology. It employs a Kalman filter within the EnKF to estimate inflation factors based on the difference between measurements and mean forecast state within the EnKF. We demonstrate its capabilities on a small soil hydrologic test case. The method is capable of adjusting inflation factors to spatiotemporally varying model errors. It successfully transfers the inflation to parameters in the augmented state, which leads to an improved estimation.

Dynamic State Estimation of Electric Power System Integrating Wind Power Generation

This paper is concerned with a problem of operation control of the electric power systems integrating wind farms. Dynamic state estimation is used to obtain reliable information about state variables and to promptly forecast the upcoming operating conditions. To predict the state variables, we assume that the wind farms are loaded first, and the remaining load is covered by traditional generation. Active power balance is maintained by a balancing plant. The problem of considering the information about wind speed at an upcoming time to forecast state variables is studied.

FORECAST MANAGEMENT PROVISION OF NATURAL RECREATIONAL AND TOURISM RESOURCES

The article substantiates the components of state forecasting �adastres system of natural recreational resources and the necessity to develop a regional forecast cadastre on their basis. The proposed system of forecast state inventories should ensure the mutual integration, complexity, availability and efficiency of providing information about the natural resources that can potentially be used for recreational purposes. Forecast cadastral research of potential natural recreational and tourist resources and activities recommended for their use should be carried out according to the principles, among which the main ones are: forecast inventories are conducted for natural resources that are not involved in economic turnover and can be used in various spheres of economic activity; the objectivity information about forecasts and alternatives of their use; completeness of information on the availability of natural recreational resources in the regions of Ukraine with their natural recreational characteristics, economic, environmental and social assessments, national values, uniqueness, exhaustibility, recoverability, recommended forms of ownership for business entities. State authorities should determine alternative directions of natural resources usage, including recreational purposes, as well as economic efficiency of alternative activities based on the natural resources usage, taking into the consideration the perspectives the of the national economy development. It is important that the forecast cadastral documentation defines the boundaries of natural resources, which are used by the cats as recreational and their monetary assessments. The proposed regional forecast cadastres (regions and districts of Ukraine) should represent the official combination of the actual location of various natural resources, u are currently not in the economic turnover and potentially should be used as recreational, their actual volumes and recreational properties, their perspective priority directions usage by types of recreational activities in order to ensure a scientifically based development of the administrative territory.

Ensemble-Based Exigent Analysis. Part II: Using Ensemble Regression to Estimate Conditions Antecedent to Worst-Case Forecast Damage Scenarios

In Part I of this series on ensemble-based exigent analysis, a Lagrange multiplier minimization technique is used to estimate the exigent damage state (ExDS), the “worst case” with respect to a user-specified damage function and confidence level. Part II estimates the conditions antecedent to the ExDS using ensemble regression (ER), a linear inverse technique that employs an ensemble-estimated mapping matrix to propagate a predictor perturbation state into a predictand perturbation state. By propagating the exigent damage perturbations (ExDPs) from the heating degree days (HDD) and citrus tree case studies of Part I into their respective antecedent forecast state vectors, ER estimates the most probable antecedent perturbations expected to evolve into these ExDPs. Consistent with the physical expectations of a trough that precedes and coincides with the anomalously cold temperatures during the HDD case study, the ER-estimated antecedent 300-hPa geopotential height trough is approximately 59 and 17 m deeper than the ensemble mean at around the time of the ExDP as well as 24 h earlier, respectively. Statistics of the explained variance and from leave-one-out cross-validation runs indicate that the expected errors of these ER-estimated perturbations are smaller for the HDD case study than for the citrus tree case study.

Validation of a Tropical Cyclone Steering Response Function with a Barotropic Adjoint Model

The steering of a tropical cyclone (TC) vortex is commonly understood as the advection of the TC vortex by an “environmental wind.” In past studies, the environmental steering wind vector has been defined by the horizontal and vertical averaging of the horizontal winds in a box centered on the TC. The components of this environmental steering have been proposed as response functions to derive adjoint-derived sensitivities of TC zonal and meridional steering. The appropriateness of these response functions in adjoint sensitivity studies of TC steering is tested using a two-dimensional barotropic model and its adjoint for a 24-h forecast. It is found that these response functions do not produce sensitivities to TC steering because perturbations to the model initial conditions that change the final-time location of the TC also change the response functions in ways that have nothing to do with the steering of the TC at model verification. An alternate response function is proposed wherein the environmental steering vector is defined as the wind averaged over the response function box attributed to vorticity outside of that box. By redefining the response functions for the zonal and meridional steering as components of this environmental steering vector, the effect of small changes to the final-time location of the TC is removed, and the resultant sensitivity gradients can be shown to truly represent the sensitivity of TC steering to perturbations of the model forecast state.