2022. vol. 26. No. 4

Huge volumes of world liquidity which were followed by the splurge of the global inflation once more highlighted fundamental shortcomings of the fiduciary money. Its promising al­ternative, as shown in the paper, could be a currency collateralized by the value of a natural re­source to be formed on a соmpetitive and liquid market. Until recently, such a theoretical construction could be viewed as a free ruble/euro conversion in the framework of selling natural gas on the European market. The forex rate dynamic was modelled as a logistic process of depreciation (appreciation) of a currency used by a resource supplier against that of its buyer. The process was driven by changes in prices for the exported resource. For the forex rate follo­wing stationary gamma distribution the maximal discrepancy between the secured rubles supply and demand corresponded to its most probable, albeit unstable, value. In particular, an important relationship between the rate of change in the ruble price of gas and the forex rate volatility has been established. Some ways of «embedding» portfolios of resource-backed assets into the process of ruble issuance were discussed as well.

The competitive storage model is analyzed in the literature in discrete time and is applied for empirical studies of the markets for agricultural commodities. In this model, there is a storable commodity supplied at every period with stochastic disturbances, and there are traders who aim at making speculative profits by using their storage. The literature has established results such as the existence of an equilibrium price function, which depends on the current availability of the commodity. The present article proposes an extension to the competitive storage model by considering continuous time. The relevance of this extension is justified by the technical convenience it brings, as well as by its suitability to the mineral markets in which the time series data is available for daily frequency. I consider serially correlated disturbances of net supply together with an upper bound on storage capacity, and characterize the equilibrium price function in this framework. The no-arbitrage and no-trade conditions define the intertemporal choice of commodity traders and imply the existence of an equilibrium price function. The equilibrium price depends on "the long-term availability of commodity" defined as the sum of storage and the expected cumulative disturbances of net supply over the infinite horizon. The various cases of the equilibrium price dynamics, such as "full storage", "empty storage" and "the trading zone", are characterized. The two types of the equilibrium price function, which are relevant to full storage, are revealed, and an explicit approximate solution for the case of a low-elastic net demand is derived. Numerical simulations of the equilibrium price function demon­strate the effects of the model parameters on this function.

Territorial differences in living standards are typical of all countries worldwide; this explains enduring interest in research into this phenomenon at the national level, especially in countries with a pronounced inhomogeneity in spatial development. The international organizations of the UN system, the OECD, Eurostat also focus on this.

Monitoring of the Sustainable Development Goals proclaimed by the UN in 2015 with regard to the accomplishment of poverty eradication and inequality reduction objective necessitates studying the local manifestations of those phenomena. This problem is especially acute for the authorities of large regions which are comparable size-wise with some countries. Such characteristics of inequality and due regard for the «subregional» factor in the levels and purchasing power of income are important for the formation of social programs and the assessment of effectiveness of measures taken for the population of parts of a region or human settlement.

This article focuses on describing the results of measurement of household income inequality among the residents of municipalities and the measurement of impact of territorial differences in consumer prices on the welfare. The purpose of undertaken research was to createa methodological platform, which allows assessing spatial inhomogeneity in the monetary component of well-being through indicators such as income and the cost of living of local communities, and to conduct its experimental testing based on real data. The choice of countries is motivated by the sizes of their territories and populations.

The practical findings provided in the paper are based on the available statistical information and emphasis the regional differences in natural climatic and socio-economic conditions of inhabitants.

The article presents the results of the conducted research, the purpose of which was to develop recommendations for the use of socio-economic benefits from the use of wind and solar energy in the environmental section of ESG instead of the most toxic generation – coal. On the basis of theoretical assumptions, the methodology developed by the author for determining the achieved savings is described in detail on the example of the largest energy enterprises Enel, Eni. The article presents not only the author's model, but also the calculations themselves with comments. The calculations carried out were carried out on the basis of the actual amount of carbon dioxide emissions charges, taking into account the damage caused, the number of people saved from premature death due to harmful emissions into the atmosphere, the economic cost of lives determined by the World Bank by country, the costs of treating emerging concomitant diseases, the social discount rate. This makes it possible to determine the real socio-economic effect of replacing fossil energy sources with cleaner energy carriers. The argumentation refuting the argument about the occurrence of a significant increase in costs in the economy, which may arise due to the introduction of a fixed fee for harmful emissions, is presented. This allows you to set more accurate benchmarks and indicators in the environmental section of the ESG system and use them in attracting investors, forming ratings, and training specialists.

The paper discusses the problem of nowcasting the current growth rates of Russian GDP and its components using quarterly data. The quality of restricted and unrestricted MIDAS models (models with mixed data), MIDAS model with L1 regularisation and MFBVAR model (Bayesian vector autoregression of mixed frequency) are compared. The results are compared with classical autoregression to justify the need to use nowcasting models for the rapid assessment of macroeconomic indicators. Production indices for various industries and macro indicators characterising Russian GDP and its components were used as explanatory variables. The paper proposes a way to quickly assess the current state of the economy and proposes a nowcasting method based on data only for the first or first two months of the quarter under consideration. As a result, for each dependent variable, the best model for building a nowcast based on the last 12 points is selected based on the criterion of mean absolute error (MAE) and root mean square prediction error (RMSE).

This study raises the problem of modeling conditional volatility under the random shocks’ normality assumption violation. To obtain more accurate estimates of GARCH process parameters and conditional volatilities, we propose two semi-nonparametric GARCH models. The implementation of the proposed methods is based on an adaptation of the [Gallant, Nychka, 1987] semi-nonparametric method to the family of GARCH models. The approach provides a flexible estimation procedure by approximating the unknown density of random shocks both using po­lynomials (PGN-GARCH) and splines (SPL-GARCH). To study the properties of the obtained estimators and compare them with alternatives, we conducted an ana­lysis of simulated data considering forms of distributions other than normal. As a result, statistical evidence was found in favor of the significant advantage of the proposed methods over the classical GARCH model and some other counterparts introduced earlier in the literature. Further, the proposed PGN-GARCH and SPL-GARCH models were applied to study Bitcoin conditional volatility dynamics. Du­ring the analysis, we found statistical evidence that Bitcoin distribution of shocks in returns differs from normal. Probably due to this reason the proposed SPL-GARCH model was able to demonstrate an advantage over alternative GARCH models according to the information criteria.