Economic Interpretation Research Articles

A data-driven explainable case-based reasoning approach for financial risk detection

The rapid development of artificial intelligence methods contributes to their wide applications for forecasting various financial risks in recent years. This study introduces a novel explainable case-based reasoning (CBR) approach without a requirement of rich expertise in financial risk. Compared with other black-box algorithms, the explainable CBR system allows a natural economic interpretation of results. Indeed, the empirical results emphasize the interpretability of the CBR system in predicting financial risk, which is essential for both financial companies and their customers. In addition, our results show that the proposed automatic design CBR system has a good prediction performance compared to other artificial intelligence methods, overcoming the main drawback of a standard CBR system of highly depending on prior domain knowledge about the corresponding field.

О концепте «Русский Север» замолвить слово

The purpose of the review is to study the essence of the concept “Russian North” in the available written sources and in various branches of scientific knowledge. The historical process of the article is localized in a vast space from the Velikiy Novgorod, the Novgorod Veche Republic to Karelia, the coasts of the White and Barents Seas — the Arkhangelsk and Kola North, the NorthEast (Komi). The Russian North is un-derstood as a hybrid concept that requires interpretation of economics, politics, society, culture, archeology, history, geography, ethnology, ethnography, philosophy, philology and other branches of scientific knowledge. The conceptual content is associated with modern understanding of historical evolution from the past to the present as a result of the thesaurus of knowledge accumulated over centuries.

Robust optimal asset–liability management with delay and ambiguity aversion in a jump-diffusion market

In this paper, we consider a robust optimal asset–liability management problem with delay for an ambiguity-averse investor (AAI), who does not hold a firm belief towards not only the drift parameters but also the jump intensity in the wealth process. The objective of AAI is to maximise the robust value involving the expected utility of a weighted sum of terminal wealth and a penalisation of model uncertainty. In addition, the wealth process is modelled by a stochastic delay equation with jump via introducing the performance-related capital inflow/outflow. Applying the technique of robust optimal theory and Hamilton–Jacobi–Bellman equation, we derive the optimal results and the proof of verification theorem for the general utility functions and liability processes. In the case of the exponential utility function and a positive liability process, we prove the existence and uniqueness of the robust optimal investment strategy and find it naturally satisfies the constraint of no-short selling. Meanwhile, we adopt a special method to solve the corresponding Riccati equation and obtain the value function in explicit form. Furthermore, the results under the complete memory are discussed in detail. Finally, some numerical examples are provided to illustrate the influence of model parameters on the optimal strategy as well as the economic interpretation behind it.

Optimal dividend and risk control strategies for an insurer with two groups of reinsurers

ABSTRACT This paper assumes that an insurer can control the dividend, reinsurance and refinancing strategies dynamically, and needs to bear proportional and fixed transaction costs. Different from previous literature, we assume that the insurer can buy reinsurance from two groups of reinsurers, i.e. the first group consists of m reinsurers and the second group consists of n reinsurers. The two groups of reinsurers have different risk attitudes and use the variance premium principle and the exponential premium principle in pricing, respectively. By using the optimal control methods, we obtain the optimal joint strategies for maximizing the insurance company's value. The results prove that dividends should be paid according to the impulse strategy; refinancing should be considered if and only if the transaction costs are not too high and the surplus is null; the insurer should diversify risks to all reinsurers in the market simultaneously when the surplus is not too large. The proportion of risk ceded to each reinsurer depends on its quoted price. Finally, numerical examples and economic interpretations are provided to make illustrations.

Forecasting Coke's Price by Combination Semi-Parametric Regression Model

According to the characteristics of consumption of coke, the article utilized combination semi-parametric regression method rather than usual regression analysis to forecast the coke's price. Coke' price was divided into two parts. Parameter part was analyzed through error correction model and BP artificial neural network. Nonlinear part was fitted by core function. Nonparametric sector was described by coke yield. The article utilized cross validation method to select optimum bandwidth, choosing the Parabola kernel for the kernel function. The least squares estimation was selected in new model estimation. The estimation results of real case demonstrate that error correction-semi-parametric regression model and BP artificial neural network-semi-parametric regression model not only reduced boundary estimation error but also strengthen economical interpretation. It is an effective method to forecast coke's price, which can largely raise the estimation precision of coke's price.

THE SLUTSKY EQUATION AND ITS PRACTICAL SIGNIFICANCE THROUGH THE MAPLE SOFTWARE PRODUCT

In this paper, we will consider the Slutsky equation for the function of demand for goods depending on the prices of these goods and the consumer’s income, taking into account compensation. The practical application of this one-factor model for calculating the demand of two interchangeable goods and the economic interpretation of the results obtained are also given. The work will be useful to those who wish to familiarize themselves with the Slutsky model for demand and consider its use in practice.

Asset Pricing and Machine Learning: A critical review

AbstractThe latest development in empirical Asset Pricing is the use of Machine Learning methods to address the problem of the factor zoo. These techniques offer great flexibility and prediction accuracy but require special care as they strongly depart from traditional Econometrics. We review and critically assess the most recent and relevant contributions in the literature grouping them into five categories defined by the Machine Learning (ML) approach they employ: regularization, dimension reduction, regression trees/random forest (RF), neural networks (NNs), and comparative analyses. We summarize the empirical findings with particular attention to their economic interpretation providing hints for future developments.

Termodynamiczne ujęcie teorii godziwego wynagradzania

Limiting itself within the framework of this article only to the issues of the theory of fair remuneration, the key questions are: what is the criterion of fair remuneration, where does it come from, and where to look for it? The main purpose of this article is to present a model of a fair wage in terms of the fundamental principles of thermodynamics. In an economic interpretation, this is the principle of preservation of capital and the principle of its spontaneous and random dissipation, which is related to the second principle of thermodynamics. Based on thermodynamic knowledge of the functioning of the human body as an abstract heat engine, a thermodynamic model of a fair wage was presented, which consists in compensating the worker for the natural dissipation of their personal capital. It was confirmed that, as a result of the application of this principle of remuneration, the earnings of two working parents make it possible to bring two descendants to the level of human capital they have achieved: that is, this wage guarantees the preservation of human capital in the family.

RUSSIA IN THE 2020S: ECONOMICS AND LAW FACING CHALLENGES INDUSTRY 4.0

The article is devoted to the analysis of the main direction of the prospective development of the world community-Industry 4.0, as a materialized expression of the fourth scientific and technological revolution, which will be decisive for the prospects for the development of modern civilization for the next 25-30 years, and possibly more. The study is conducted from the perspective of the two most important areas of modern public life-economics and law. Based on this, the purpose of the work is the formation of a comprehensive understanding of the current stage and prospects for the integration of Industry 4.0 into the modern global and domestic social structure, specifically in the prism of its interpretations in the economy and the legal sphere. The economic interpretation of Industry 4.0 today consists of three main hypostases-the introduction of Artificial Intelligence technologies into the functioning of economic actors, the transformation of the modern Internet in the direction of such innovative forms as the Internet of Things (IoT) and the Internet of People (IoP) with the deepening of the integration of economic actors into this virtual environment, formation of a «smart enterprise» through the creation of cyber-physical systems. The legal sphere, in the context of integrating the components of Industry 4.0 into the public environment as a whole, will face a number of challenges, among which, first of all, it is necessary to highlight the need to adapt the political and legal system to new conditions and form adequate responses to emerging trends. Also, already today, in order to predict, a list of those economic and legal problems that society will face in the practice of introducing the above elements into socio-economic practice can be proposed.

The Impact of Tax Control on Tax Revenues: An Aggregate Metric Analysis of the Case of Albania

Tax administration constantly monitors taxpayers through tax control to meet the legal obligations of the tax field. The main purpose of this function is to advise taxpayers and maintain operational control through continuous monitoring. Motivated by the importance of tax control, this paper aims to provide an empirical contribution to the analysis of tax control’s effects on the level of tax revenues. The database obtained in the analysis is both quantitative and qualitative according to the evidence of direct operational controls performed on businesses. The variables analysed are total tax revenues from value added tax (VAT), profit tax, personal income tax (PIT), withholding tax, etc.; tax control variables and macroeconomic variables. The methodology used in this paper is based on linear models with many variables as well as statistical tests to find the potential levels and equilibrium, elasticity and structural estimation of tax revenues. The findings of this paper provide a focused contribution on current issues for tax control policymakers, as well as other public entities, and they make an academic contribution to the legal and economic interpretation of the importance of tax control.

POINT AND INTERVAL FORECAST OF GROSS CROP PRODUCT OUTPUT IN THE REPUBLIC OF KAZAKHSTAN

Purpose of the research is to develop an interval forecast of changes in the indicators of gross crop production from the volume of sown area based on the construction of a paired linear regression model and analysis of changes in the total output of crop production depending on the volume of sown areas of the Republic of Kazakhstan for the period 2000-2021.Methodology. In this work, we used methods for constructing and analyzing a paired linear regression model, methods for constructing precise and interval forecasts using a paired regression model.Originality / value of the research lies in the possibility of using predictive calculations of the gross production of crop production from the volume of sown area while improving the state policy of restructuring agricultural land for the effective use of the potential of land resources and increasing the volume of crop production in the Republic of Kazakhstan. The results of the study contribute to the development of methodological foundations for calculating the volume of crop production in the Republic of Kazakhstan in various categories of farms.Findings. This paper analyzes the change in the gross output of crop production and sown areas of the Republic of Kazakhstan for the period 2000-2021 based on the construction of a paired linear regression model. The quality of the model was assessed, the interval for the lower and upper limits of the forecast of changes in the gross output of crop production from the volume of the sown area was calculated. An economic interpretation of the calculated data obtained as a result of building a linear pair regression model is given. The research confirms the importance of a reasonable approach to the development of a rational structure of sown areas, based on the strategic task of ensuring food security in the Republic of Kazakhstan.

Nowcasting growth using Google Trends data: A Bayesian Structural Time Series model

This paper investigates the benefits of internet search data in the form of Google Trends for nowcasting real U.S. GDP growth in real time through the lens of mixed frequency Bayesian Structural Time Series (BSTS) models. We augment and enhance both model and methodology to make these better amenable to nowcasting with large number of potential covariates. Specifically, we allow shrinking state variances towards zero to avoid overfitting, extend the SSVS (spike and slab variable selection) prior to the more flexible normal-inverse-gamma prior which stays agnostic about the underlying model size, as well as adapt the horseshoe prior to the BSTS. The application to nowcasting GDP growth as well as a simulation study demonstrate that the horseshoe prior BSTS improves markedly upon the SSVS and the original BSTS model with the largest gains in dense data-generating-processes. Our application also shows that a large dimensional set of search terms is able to improve nowcasts early in a specific quarter before other macroeconomic data become available. Search terms with high inclusion probability have good economic interpretation, reflecting leading signals of economic anxiety and wealth effects.

Writing Across the Curriculum (WAC) Assignment in Macroeconomics

This article shares an assignment that has been successfully implemented in Writing Across the Curriculum (WAC) macroeconomic courses available to major and non-major undergraduate students enrolled in the City University of New York (CUNY) Kingsborough Community College. While the outcome at the end of the semester is a paper of about three pages, the steps designed to assist students with completing it are important because they provide a detailed research and investigation guide. The assignment is composed of a series of scaffolded tasks that engage students in data collection, data analysis, and interpretation using economic theory of the subject area, presentation of the actual findings compared to predictions of economic theory, and investigation and interpretation for convergence and/or divergence from the economic theory. This assignment is based on prior research on the benefits of assigning writing in economics courses and aims to achieve the outcomes described by the structure of cognitive process dimension of the revised Bloom’s taxonomy (Bloom et al., 1956; Krathwohl, 2002).

Indigenous Characters and Their Nation: A Socio-Political Analysis of Selected Nepali Plays

The rise of modern Nepali intellectuals especially in Kathmandu during the 1930s inspired many writers and political leaders to articulate new narratives of the nation. For instance, Balkrishna Sama’s Mukunda Indira, Bhimnidhi Tiwari’s Sahanshila Sushila (Permissive Sushila) present characters from various strata of Nepali society. In the plays, indigenous communities speak about the psycho-social realities of the time. The indigenous characters of the plays are humble and hardworking. But in the play Simma written by Rayan right before the 1980 referendum, the time the Panchayat regime became stronger and kept denying the people’s democratic rights the indigenous characters in plays become politically vocal. They question the polity based on modern social and political theories. However, the indigenous characters of Mayadevika Sapana (Dreams of Mayadevi) written by Abhi Subedi and staged in 2004 and later years speak for the universal peace and brotherhood. By drawing upon Ludwig Stiller and Mahesh Chandra Regmi’s social, economic and political interpretation of Nepal’s history, particularly of the nineteenth century, the article concludes that while presenting the indigenous characters, the playwrights directly and indirectly address the social and political ills of the Nepal society. These indigenous characters' attitude towards their masters and the representatives of the state around reflects the political and historical courses that Nepal has gone through over the centuries and the rise of a force that might free them from such lines of control.

Tourist accommodation pricing through peer-to-peer platform: evidence from Seville (Spain)

The expansion of holiday rentals’ worldwide makes it relevant to confirm what are the determinants of these accommodations’ daily rates. This research aims to compare two models on estimating holiday rentals’ daily rate through variables that influence it; using artificial neural networks and hedonic pricing method, with the same cross-sectional dataset and variables with data obtained from Booking.com listings from Seville (Spain), a ‘cultural tourism’ large European city. Artificial neural networks estimations adapt better than the hedonic pricing method due to non-linear relations involved, although hedonic estimators have a clearer economic interpretation. Variables related to size, location and amenities appear as the most relevant in the models, including also seasonal and special events factors. The models presented, not only help to clarify these variables but also allow estimating a rental price congruent with the characteristics of the dwelling and season, being useful as an objective valuation method for the main agents of the accommodation sector: Owners, clients and peer-to-peer platforms. This study wants to highlight the convenience of using Booking.com listings as the main data source, as two variables presented as relevant for the models (size and location) are not available in other peer-to-peer platforms like Airbnb.

Characteristics of Earthquake Cycles: A Cross-Dimensional Comparison of 0D to 3D Numerical Models.

High‐resolution computer simulations of earthquake sequences in three or even two dimensions pose great demands on time and energy, making lower‐cost simplifications a competitive alternative. We systematically study the advantages and limitations of simplifications that eliminate spatial dimensions in quasi‐dynamic earthquake sequence models, from 3D models with a 2D fault plane down to 0D or 1D models with a 0D fault point. We demonstrate that, when 2D or 3D models produce quasi‐periodic characteristic earthquakes, their behavior is qualitatively similar to lower‐dimension models. Certain coseismic characteristics like stress drop and fracture energy are largely controlled by frictional parameters and are thus largely comparable. However, other observations are quantitatively clearly affected by dimension reduction. We find corresponding increases in recurrence interval, coseismic slip, peak slip velocity, and rupture speed. These changes are to a large extent explained by the elimination of velocity‐strengthening patches that transmit tectonic loading onto the velocity‐weakening fault patch, thereby reducing the interseismic stress rate and enhancing the slip deficit. This explanation is supported by a concise theoretical framework, which explains some of these findings quantitatively and effectively estimates recurrence interval and slip. Through accounting for an equivalent stressing rate at the nucleation size h* into 2D and 3D models, 0D or 1D models can also effectively simulate these earthquake cycle parameters. Given the computational efficiency of lower‐dimensional models that run more than a million times faster, this paper aims to provide qualitative and quantitative guidance on economical model design and interpretation of modeling studies.

An officer and an activist: Futuring, precarity and life after exile in Namibia

This article explores the life histories of two Namibians who grew up in SWAPO's exile camps in Angola and their ‘futuring’ trajectories once they returned home to Namibia after independence. Presenting these actors’ life histories of navigating Namibian society helps challenge a one‐sided economic interpretation of precariousness. More critical than asserting dichotomies between ‘elite’ and ‘precariat’ are the stratagems and choices shaping lived experiences.

Residuals from two‐step research designs

AbstractA number of studies have begun to question the appropriateness of the widespread and pervasive usage of regressions in two‐step research designs in the accounting literature to obtain variables. The use of residuals from a first‐step model as a dependent variable in a second step has been used in contexts such as earnings management and unexpected audit fees. In this paper, I provide a discussion of the issues within the use of residuals from a first‐step model in a second step. Taking the case of discretionary accruals models, I demonstrate some of the model specification issues explicitly and implicitly considered within these criticisms. I then add a discussion over some concerns regarding the economic interpretation in the use of first‐step residuals.

Problems and possibilities of applying the theory of antagonistic games in the analysis of economic systems for various purposes

In organizational and economic tasks related to decision-making at various levels of the hierarchy in various economic systems, conflict situations often arise. A distinctive feature of any conflict is that the interests of its parties are mutually opposed, that is, the economic result (winning) of one participant in the conflict is equal to the loss of the other participant. With the help of conflict situations, one can describe the opposition of competitors to each other in the oligopoly market, the struggle for resources between various interested parties, the relationship of tax authorities with unscrupulous taxpayers, and some other situations. The article discusses the practical application of the theory of antagonistic games to the problems of choosing effective solutions in the economy, analyzes the methodological features of this theory, formulates the main problems that arise when using antagonistic games in organizational and economic problems, analyzes some practical examples in which the use of this theory can be appropriate. Special attention is paid to the solution of computational problems, the economic interpretation of such game theory terms as strategy, win, efficiency criterion. As the main result of the work, it should be noted that: 1. Despite the fact that the theory of antagonistic games is currently developed mainly as a purely mathematical model, it may well find application in solving practical economic problems, in particular, for the oligopoly market. 2. Using the methods of the theory of antagonistic games to select optimal solutions in conflict situations encounters a number of difficulties, among which the most important are:
 determination of the set of strategies of the participants in the conflict;
 the correct choice of the criterion on the basis of which the conflict situation is analyzed;
 establishing the relationship between the optimality criterion and the strategies of the participants;
 formation of an efficiency matrix based on the values of this criterion for each combination of strategies of the participants in the conflict;
 search for equilibrium situations;
 study of the possibility of a multi-criteria choice in the context of a conflict of interest.
 
 The most widely used when choosing effective solutions in a conflict of interest is the principle of a guaranteed result, which is the easiest way to determine the equilibrium strategies of the participants.

Model of functioning of the centralized wireless information ecosystem focused on multimedia streaming

The article's highlight is the Markov model of functioning of the centralized wireless information ecosystem focused on multimedia streaming. The model describes the stochastic process of joint service by the base transmission station (BTS) of independent streams of multimedia transfer and text data transfer. To assess the effectiveness of the fulfilment of its purpose by the studied ecosystem, a metric of quality parameters is proposed, in particular: - the percentage of lost requests for multimedia transfer; - the percentage of lost requests for text data transfer; - the average share of the resource of the BTS communication channel involved in the service of multimedia transfers; - the average share of the BTS communication channel involved in the service of text data transfer; - the percentage of censored operating time of the studied system, when the incoming request for multimedia transfer was rejected due to lack of the required share of free resource of the communication channel; - the ratio of the number of lost multimedia transfer requests to the potential number of transfer sessions. The first four parameters are indicators of the reliability of the studied system, and the last two qualitative parameters have a direct economic interpretation. For the studied ecosystem to realize its purpose in conditions of moderate and high load, the model introduced a self-limiting function. This feature allows us to flexibly balance the servicing of transfer sessions of both types, balancing the values of the first two quality indicators. The adequacy of the proposed mathematical apparatus is proved empirically.