Dynamic Economic Systems Research Articles

A Study of the Complexity of Markets and the Diversity of Economic Embodiments

This research investigates the social context of the variety of economic systems and the intricacy of markets. It looks at how markets and economic systems have developed and operated globally, taking into account historical, cultural, and social influences. The analysis and comprehension of the diversity of economic systems and the intricacy of markets are the main goals of this thesis. It investigates the functioning and interactions of various economic systems, including capitalism, socialism, and mixed economies, in various social contexts. The intricacies of markets and their influences on inequality, economic growth, and general social welfare are examined. The goal of this research is to offer a grasp of the composition and dynamics of economic systems and marketplaces. It outlines the main forces at work in them, such as supply and demand, market forces, and governmental involvement. This paper also studies how various economic systems affect social mobility, income distribution, and economic stability. This paper uses analytical data, analysis of literature, case studies and comparative analysis to analyze the various economic systems and their results. This paper finds that economic policies must be tailored to the specific needs of diverse and dynamic markets in order to support inclusive and sustainable growth.

MODELING INFLATION DYNAMICS USING THE LOGISTIC MODEL: INSIGHTS AND FINDINGS

This paper examines applying the logistic model, frequently used in biology, to analyze inflation patterns in dynamic economic systems. The primary objective is to simulate and analyze the complex dynamics of inflation, thus providing new insights into the stability of financial institutions. Numerical methods such as Euler's Method, Runge-Kutta Method (RK4), and Adams-Bashforth-Moulton's method were used to simulate inflation patterns by discretizing the logistic equation. The data utilized in this research were obtained from INSTAT, BoA, MoF, and Eurostat, with quarterly results from 1995 to 2023. The simulation results indicated that the RK4 and Adams-Bashforth-Moulton methods yielded more precise and reliable inflation forecasts than Euler's. The logistic model represented the non-linear aspects of inflation dynamics well, emphasizing the necessity of using suitable numerical approaches. The study's findings highlight the effectiveness of the logistic model in economic analysis, specifically in forecasting inflation trends. Enhanced closure approaches have proven their effectiveness in analyzing intricate economic data, providing crucial insights into the stability of inflation, and informing policy formulation. This study utilizes the logistic model to analyze inflation dynamics, offering a unique methodology for comprehending and forecasting inflation in economic systems. An analysis of several closure techniques reveals a novel aspect of financial modeling tools. The findings indicate that incorporating advanced numerical methods can significantly improve the precision of economic models. These findings significantly impact economic research and policy formulation, especially in devising measures to manage inflation and ensure financial stability.

Food Price Inflation in the United States as a Complex Dynamic Economic System

Abstract The issue of volatile food prices is a consistent problem for American consumers, as rising prices make it challenging to afford nutritious food that meets dietary standards. Various complex factors influence this price volatility, including economic conditions, weather patterns, global trade, energy prices, and more. Notably, the impact of food price increases is not equal for everyone. Low-income individuals and those in rural areas are disproportionately affected. A comprehensive understanding of the driving factors is essential to tackle this issue effectively. We employ advanced time-series techniques such as Vector Error Correction Models (VECM) and modern causal inference methods such as probabilistic graphical models implemented via machine learning and artificial intelligence approaches on monthly data from 2000 to 2021 to investigate the U.S. food price inflation issue. These methods help unravel the intricate dynamics among key variables driving food price inflation. The study aims to achieve several objectives. It intends to (1) clarify how factors influencing food price inflation in the U.S. change over time using VECM models, (2) establish causal relationships among interconnected variables to develop probabilistic graphical models using innovative search algorithms, and (3) create and validate forecasts related to U.S. food price inflation. The end goal is to provide actionable insights for policy design. Results show that food price inflation is heavily tied to commodity pricing and pricing for medical services. Additionally, historical decompositions for COVID-19 show ties between food price inflation and energy inflation.

Time Series Analysis and Algorithm for Fluctuation Pattern Recognition and Forecasting of Economic Indicators

This study examines the use of artificial neural network (ANN) algorithms in machine learning for recognizing fluctuation patterns and forecasting economic indicators in the field of political economy. In today's changing global economic scene, economic forecasting is critical for informing policy decisions, directing strategic planning, and managing risks. Traditional statistical approaches and time series analysis have long been used for this purpose, but the advent of ANN algorithms provides a new way to capture the intricate dynamics of economic systems. Using ANNs' intrinsic flexibility and nonlinear modelling capabilities, this study analyzes their ability to effectively forecast future swings in economic indices. This work intends to understand the strengths, limits, and practical consequences of ANN-based forecasting models by conducting a complete assessment of literature, methodological methods, and empirical studies. This study adds to the continuing discussion of economic forecasting approaches by diving into theoretical frameworks, methodological concerns, and empirical data. Finally, incorporating ANN algorithms into machine learning offers promising opportunities for improving the understanding of economic processes and supporting informed decision-making in the political economy.

Estimating the loss of economic predictability from aggregating firm-level production networks.

To estimate the reaction of economies to political interventions or external disturbances, input-output (IO) tables-constructed by aggregating data into industrial sectors-are extensively used. However, economic growth, robustness, and resilience crucially depend on the detailed structure of nonaggregated firm-level production networks (FPNs). Due to nonavailability of data, little is known about how much aggregated sector-based and detailed firm-level-based model predictions differ. Using a nearly complete nationwide FPN, containing 243,399 Hungarian firms with 1,104,141 supplier-buyer relations, we self-consistently compare production losses on the aggregated industry-level production network (IPN) and the granular FPN. For this, we model the propagation of shocks of the same size on both, the IPN and FPN, where the latter captures relevant heterogeneities within industries. In a COVID-19 inspired scenario, we model the shock based on detailed firm-level data during the early pandemic. We find that using IPNs instead of FPNs leads to an underestimation of economic losses of up to 37%, demonstrating a natural limitation of industry-level IO models in predicting economic outcomes. We ascribe the large discrepancy to the significant heterogeneity of firms within industries: we find that firms within one sector only sell 23.5% to and buy 19.3% from the same industries on average, emphasizing the strong limitations of industrial sectors for representing the firms they include. Similar error levels are expected when estimating economic growth, CO2 emissions, and the impact of policy interventions with industry-level IO models. Granular data are key for reasonable predictions of dynamical economic systems.

Possibilities and limits of modelling of long-range economic consequences of air pollution – A case study

Air pollution is the biggest environmental problem in modern societies, causing considerable health damage and requiring substantial financial resources for health care. The goal of the study is to demonstrate the adverse economic consequences of air pollution on example of a small, open Central European country, Hungary, and to provide quantified financial arguments for macroeconomic decision-making for the development of a long-term energy strategy. On the basis of the Cobb-Douglas production function and Solow-Swann model of dynamic economic systems a simple and robust model was constructed to estimate and predict economic losses, caused by the pollution. On base of results it is obvious, that on base of macroeconomic theory and combination of various, publicly available, quality-controlled statistical resources quantifiable models can be constructed to characterise the economic consequences of air pollution, but it should be taken into consideration, that the reliability of economic models considerably depends on their initial parameters and practical validity of assumptions, based on which the underlying economic theories were built. The most important economic burden of air pollution is caused by the loss of working–age population, resulting in a decrease of 4.1–9.4 % a year in Gross Domestic Product (GDP) in the next fifty years. The additional burden of health care costs amounts to 0.1 % of GDP. Reducing air pollution is not only a quality of life improvement but also an investment into the economic development. Notwithstanding of statistical biases it could be proven the importance of combination health economic and econometric methods in preparation of more efficient environmental-related socio-economic decisions.

Dynamics of Economic Systems - A Physicist's Perspective

Dynamics of Economic Systems - A Physicist's Perspective

Variation Approach and Principle of Maximum in Theory of Dynamic Systems

The article shows dynamics of value figures on market of digital finance assets. The research studies methods of the sensitivity theory in tasks of optimal management of non-linear systems for automated monitoring and controlling the portfolio of digital finance assets and crypto-currencies. The authors study process modeling in economic systems, set the task of optimal management by the system of non-linear differential equations and target functionality, describe the variation method of task resolving, the principle of invariability of non-linear systems and possibilities to model economic systems provided by the solution. The approach to investigating dynamics of economic systems based on the principle of maximum was analyzed. The article shows possible application of the approach for resolving optimization tasks and for methods of management with split and continuous character in conditions of uncertainty typical of economic systems. Functions of non-linear sensitivity are identified. The use of the sensitivity theory for tasks of optimal management of non-linear systems was studied, illustrated by estimating the vector of unknown parameters of dynamic system. The authors analyze the condition in tasks of economic modeling with regard to uncertainty caused by social and psychological reasons. The material provided in the article shows possibilities of using the method of sensitivity analysis for tasks of system decomposition and related transformations in systems of differential equations.

Retracted: Tracking Control of the Dynamic Input-Output Economic System Based on Data Fusion

Retracted: Tracking Control of the Dynamic Input-Output Economic System Based on Data Fusion

In Search of Sustainable Economy Definition: A Qatari Perspective

This paper aims to assess Sustainable Economy (SE) features and validate them by using sustainability experts residing in Qatar to suggest an expanded and improved definition of SE. Fifteen features of SE have been identified via a comparative literature review and validated by sustainability experts in Qatar. The study significantly strengthens and validates the features of SE and provides analysis of some of these features by the authors. The paper suggests that SE should be defined as “a value-based, dynamic, and balanced economic system that meets the needs of all living species today while remaining within ecological and social boundaries, without compromising the system’s capacity to meet all future needs of all living species”. This is the only paper that uses Qatari experts to research SE features. The limitation of the research is the inclusion of a small sample size of experts within Qatar due to the limited number of experts in the field of sustainability and their willingness to participate.

A Relational Model of Economic Organization: Relations Within, Between, and Among Economic Scales

We propose a relational theoretical model of economic organization that offers new insight into the organizing dynamics of economic systems. Neoclassical and complexity economics are, in their Western cultural origins, based on an assumption of the primacy of the discrete individual. Collectivist economic traditions are based on the principle of collective interest rather than self-interest. We attempt a rapprochement of individualist (especially free market) and collectivist (especially centrally planned) economic cultures and traditions by modelling economic organization as arising from individual and collective dynamics and the relationships between them. Structure, process, function, and content are four fundamental inter-related properties of our model of economic organization. We posit the existence of micro, meso, macro scales of economic organization in all of structure, process, function, and contents. To operationalize our relational model, the conventional bottom-up process of self-organization is reconceived to involve relationships within micro-, meso-, and macro-economic organization. In turn, the new concept of socio-cultural organization is construed to involve relationships between and among economic organization, across micro, meso, and macro scales. Our model of relations provides a structure for complex-realist exploration, making cross-scale inter-relationships explicit and by providing a structured language for description of these relationships.

Influence of information systems on the structure of the labor market of the transport industry

In the context of sustainable development and the digital economy, it is difficult to find labor resources for the transport industry that are guided by modern trends. That is why it is necessary to analyze the labor market and determine the indicators of personnel efficiency for the transport industry. Readiness for employment and self-employment occur in a scientific and psychological concept reflecting the motives and determination to accept professional activity tasks in a specific life situation. However, at present, the phenomenon of readiness requires diagnosis, correction and development of the qualitative characteristics included in it. Obviously, modern paradigms of sustainable development and the digital economy significantly complicate their adaptation in a dynamic economic system under the influence of the pandemic caused by the COVID-19 virus. The labour market and self-employment are also drifting in a crisis. On the one hand, there is a shortage of labour resources, on the other hand, there is a fairly high unemployment rate.

A predator-prey economic system of tax evasion and corrupt behavior

The goal of this research is to study an economic system characterized by the coexistence of tax evading citizens with corrupt auditors (public officials), that is a system of predators-preys, i.e. corrupts and not, evaders and not. We show that citizens choose non-corrupt behavior when their utility exceeds a threshold level with respect to an optimal progressive tax rate. On the other hand, auditors choose non-corrupt behavior if their utility is higher than a certain threshold level depending on the fines and probabilities of being sanctioned. Being aware of this situation, a government or central authority must study a dynamic evolutionary economic system (a generalized predator-prey model) by analyzing all possible steady states of this economic system. The stability of the steady states depends on the crucial parameters of the model, namely: i) a socially negative impact exerted by corrupt public officials or auditors on the evolution of the economic society, ii) the impact of the social weight of the citizens who pay taxes on corrupt auditors, iii) the behavior of imitation of the agents when perceiving the possibilities of being sanctioned or not, and iv) the inertia and feedback of the corrupt system (dishonest behavior and tax evasion). We conclude by highlighting the importance of bifurcations or qualitative changes in the parameters of this economic system to fight corruption and evasion.

Диалектика обращения капитала в контексте эволюционной динамики экономических систем

Introduction: the article reflects the author’s vision of solving an urgent problem for modern social sciences – a systematic representation of the dialectics of capital circulation in the context of the evolutionary dynamics of economic systems. Aims: to research and systematize the main provisions of capital circulation dialectics in the context of the evolutionary dynamics of economic systems in different phase states of their existence. The set aim makes it possible to present the ontology of the research object, and to prevent distortion towards solving local scientific problems, without considering causal connections during development. Methods: the article is written in a descriptive key, relying on the cognitive potential of the dialectical system-historical method, supplemented by individual elements of the formation approach and the theory of capital circulation. Results: the work presents a system of arguments proving that to derive the process of capital circulation in relation to various phases of the evolutionary dynamics of the capitalist system is possible using the cognitive potential of the dialectical system-historical method, supplemented by certain elements of the method of ascent from the abstract to the concrete. Specific features of capital circulation process within the framework of the phase dynamics of the capitalist system evolution have been highlighted. It is argued that capitalism, as a system, has a limited resource of its being, and develops in the form of a logical chain: “the genesis of the system – the development of the system based on the deepening division of labor – the growth of individual risks – the expansion of markets – the single global market – the halt of development – the decline of the system”. Conclusions: the results systematized in this article in the future may become the scientific and methodological basis for future research works devoted to the systematic representation of the dialectic of capital in the context of the evolutionary dynamics of economic systems.

Justification of the identification of threats and problematic components of sustainable regional development in the security dimension

The issue of substantiation of the problematic components of sustainable development in the security dimension and threat identification methodology is investigated. The methodology consists of directly combining the identification of threats with the need to observe the limits of the safe existence of dynamic economic systems, which connects the problem of sustainable development with the problem of security. The explanation of the extended homeostatic plateau, which explains the conditions for the transition to a higher technological system, or the complication of functioning and the loss of the main functions of the existing technological system, has gained further development. A theoretical substantiation of the limits of secure existence in terms of security gradations is proposed: critical, threshold, and optimal on both sides of the “extended homeostatic plateau”. Quantitative values of security gradations are associated with the extension of the “t-criterion” method for the formal determination of bifurcation points for characteristic types of distribution, that is, threats. The identification, classification, and analysis of problematic components and critical threats at the level of components and indicators were carried out, which made it possible to identify only four strategic directions of institutional measures that allow covering almost all indicators of sustainable development at the regional level.

A note on Medieval Mediterranean trade networks: first observations on the possible evidence of Sicilian amphorae of the 8th-9th century in Crete and the Aegean

Nearly a quarter of a century has gone by since scholars working on the Medieval Mediterranean were wondering if Byzantium was dead or alive during the 8th-9th centuries. Indeed, until recently, it was still quite a prevailing view that this period marked the ‘Dark Ages’ for the Byzantine Empire, in all the facets of its administrative, economic, and sociocultural life. Scholarly debate of the last years has zealously challenged this view, depicting a smoother and less pessimistic picture of this period. For instance, leaving aside historical and artistic aspects, and focusing on the theme of this report – that is Medieval amphorae – already in the mid-2010s it was clear that the Mediterranean remained a dynamic economic system throughout the 8th-9th century. This argument, which was mostly drawn on the evidence of the so-called Aegean globular amphorae, was further embodied and enhanced in 2018, during a thematic conference of the AIECM3 group, which was entirely dedicated to Medieval Mediterranean amphorae from the 8th to 12th centuries. Among the main and most valuable contributions, Cacciaguerra’s article shed light on the Mediterranean patterns of distribution of a specific type of amphora of the 8th-9th century produced in Sicily. Back then, amphorae of this kind were known outside Sicily, mostly along the Adriatic, but were utterly unknown eastward of the Otranto Straight. The aim of this short report is twofold: 1. to elaborate on this mainstream study-theme of Medieval Mediterranean amphorae and trade networks; 2. to expand on the current record of extra-regional evidence of Sicilian amphorae of the 8th-9th century by discussing the evidence of possible specimens documented in Crete and into the Aegean.

Системные принципы структурной организации агропродовольственного комплекса

The article substantiates the methodology of multidimensional structuring of the agro-food complex (AFC), based on the basic principles of a systematic approach. The agro-food complex is considered as a complex, dynamic and multi-level socio-ecological and economic system of interconnected elements and diverse ordered links between them. The author made an attempt to get a holistic view of the structural organization of the agro-food complex using three system projections: spatio-temporal type of the system, functional-structural term, stage of the reproduction cycle. For this, an analysis of the structural organization and functioning of the agro-food complex (functional-sectoral, product, organizational, social structures) was carried out. The substantiation of the set of direct and feedback links between the elements of the agro-food system is given. Using the typology of socio-economic systems proposed by G.B. Kleiner, spatio-temporal characteristics of the agro-food complex are given. The integration interaction of various types of system elements of the AFC is considered through the prism of the stages of the reproduction process: production, distribution, exchange and consumption. It is substantiated that such a methodological technique will allow for the most complete account of the interconnections of the elements of the agro-food system, and will also contribute to the choice of the optimal type of management, in relation to a certain type of subsystem and its components.

Tracking Control of the Dynamic Input-Output Economic System Based on Data Fusion

In recent years, under the background of stable economic operation, people's research on economic systems has become increasingly popular. The dynamic input-output model reflects the change and development process of the input-output relationship of the economic system over a period of time. The main purpose of tracking control is to design a suitable controller so that the output of the control system can track the output of the reference system as much as possible. In the economic system, data is an important factor. Based on this, this paper mainly studies the tracking control of dynamic input-output economic system based on data fusion. This research takes the data fusion of the dynamic input-output economic system as the starting point and takes the optimal control and tracking of the economic system as the research object of this research. Based on data fusion technology, a new dynamic input-output economic system tracking and control is proposed. This paper studies the finite-time optimal tracking control of linear systems. Through numerical examples, comparing the finite-time and infinite-time optimal control simulation results, it is proved that the algorithm can achieve good tracking control. Experimental data shows that the optimal and suboptimal performance indicators for a limited time are 0.7729412 and 1.5687310, respectively. Therefore, compared with the infinite-time optimal control, the performance loss and the final tracking error of the suboptimal control proposed in this study are reduced.

Development of Organizational and Economic Mechanism of Functioning High-Tech Enterprises in the Introduction of Digital Technologies

Scientists believe that an innovation-oriented enterprise is a specific type that is characterized by active innovation, creation, production, and sale of innovative products or products. In this study, the functioning of an innovation-oriented enterprise is based on the production of economic activity as the basis of its existence, and the use of innovation is the source and activator of its development. It is reasonable to consider innovation-oriented development as an ideology, a manifestation, and a way of development driven by or directed at innovations. The functioning of enterprises based on innovative productions ensures their self-development. The source of self-development is considered the enterprise's internal activity, and the tools are innovations, innovative changes, knowledge, and experience. For the implementation of self-development, the economic system makes the transition to a new level of functioning in the case of activation of the processes of change, the availability of the ability and interaction with the ecosystem of functioning, and the reproductive mechanism with maximum efficiency innovation. A feature of innovation-oriented enterprises in the production of self-development in functioning is the use of innovations in the development of potential, in updating and applying economic resources to form the ability to develop innovatively. In other words, it is reasonable to consider such an enterprise as a dynamic economic system that develops itself by operating in the process of functioning through innovative production in economic activity. The studied enterprises should have a high degree of functionality. At the same time, we consider a dynamic economic system to be a functional, innovation-oriented enterprise that can develop in the process of functioning and ensure the development of other economic systems along with meso-level institutions, transforming the results of their development for its further economic evolution.

ДИНАМІЧНА МОДЕЛЬ ОЦІНЮВАННЯ СТРАТЕГІЇ РОЗВИТКУ ЕКОНОМІЧНОГО КЛАСТЕРА З УРАХУВАННЯМ ТРАНСПОРТНОЇ СКЛАДОВОЇ

Анотація. Представлено підхід до оцінювання стратегії економічного розвитку кластера, що включає динамічну економіко-математичну модель та інструментарій адаптивного моделювання, зокрема формування узагальнених коефіцієнтів моделі на базі нейронечіткої моделі. Цей механізм отримання оцінок узагальнених коефіцієнтів динамічної моделі, який впливає на вибір сценарію розвитку досліджуваних кластерів і спрогнозовані межі можливих змін економічних показників. Проведено комп’ютерні експерименти вибору стратегії економічного розвитку кластерів (на прикладі Київської області та м. Києва, Дніпропетровської та Одеської областей) і здійснений аналіз альтернативних сценаріїв їхнього розвитку. Дослідження ґрунтується на застосуванні методів системного аналізу, а також апарату математичної статистики й економіко-математичного, адаптивного, зокрема імітаційного та нейронечіткого моделювання тощо. За результатами дослідження виявлено, що поєднання нелінійної динамічної моделі з нейронечіткою моделлю дає змогу знайти такі сценарії економічного розвитку кластера, що забезпечить постійне і збалансоване зростання показників досліджуваного кластера, забезпечить цілеспрямоване підвищення рішення економічного зростання на мікро- або макрорівні та своєчасне попередження економічного спаду. Ключові слова: динамічна економічна система, кластер, теорія нечітких множин; комп’ютерне моделювання; альтернативні сценарії розвитку. Формул: 2; рис.: 8; табл.: 2; бібл.: 17.