Advances in Mathematical Methods in Economics

A special issue of Axioms (ISSN 2075-1680). This special issue belongs to the section "Mathematical Analysis".

Deadline for manuscript submissions: closed (20 March 2024) | Viewed by 8893

Special Issue Editor


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Guest Editor
Department of Mathematical Methods in Economics, Plekhanov Russian University of Economics, 117997 Moscow, Russia
Interests: regression analysis; econometric modeling; machine learning; social statistics; time-series forecasting; panel data analysis; optimization

Special Issue Information

Dear Colleagues,

In the era of Big Data, abundant statistics and unprecedented computer power, we are still facing numerous problems concerning data processing, model specification, model selection, algorithm efficiency, etc., when trying to make predictions or understand the nature of certain economic or social processes. Such classes of datasets often have time-varying parameters, making it difficult to build adequate models, even if the datasets are large.

The purpose of this Special Issue is to contribute to the elaboration of new methods and statistical tools that would help researchers model economic and social environments more efficiently. Therefore, we are looking for articles that propose novel mathematical tools and methods that can adequately describe and provide insight into the core of socioeconomic processes.

The articles are expected to cover a wide range of topics, such as social statistics, financial modeling, statistics in marketing, macroeconomic time-series forecasting, panel data, cross-country economic modeling and regional econometrics.

Prof. Dr. Nikita Moiseev
Guest Editor

Manuscript Submission Information

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Keywords

  • regression analysis
  • econometric modelling
  • machine learning
  • social statistics
  • time-series forecasting
  • panel data analysis
  • optimization

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Published Papers (6 papers)

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Research

14 pages, 430 KiB  
Article
Coincidence Point of Edelstein Type Mappings in Fuzzy Metric Spaces and Application to the Stability of Dynamic Markets
by Satish Shukla, Nikita Dubey, Rahul Shukla and Ivan Mezník
Axioms 2023, 12(9), 854; https://doi.org/10.3390/axioms12090854 - 1 Sep 2023
Cited by 4 | Viewed by 726
Abstract
In this paper, we prove a coincidence point result for a pair of mappings satisfying Edelstein-type contractive condition on fuzzy metric spaces. We describe the equilibrium of a simple demand–supply model of a dynamic market by the coincidence point of demand and supply [...] Read more.
In this paper, we prove a coincidence point result for a pair of mappings satisfying Edelstein-type contractive condition on fuzzy metric spaces. We describe the equilibrium of a simple demand–supply model of a dynamic market by the coincidence point of demand and supply functions. With the help of the coincidence point theorem in fuzzy metric spaces, it is showed that a dynamic market of a supply-sensitive nature (or demand-sensitive nature) always tends towards its equilibrium. Full article
(This article belongs to the Special Issue Advances in Mathematical Methods in Economics)
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12 pages, 2883 KiB  
Article
Research on the Dynamic Mechanism of Technological Innovation Diffusion in Enterprise Communities Based on a Predation Diffusion Model
by Jingfei Chen and Gang Tian
Axioms 2023, 12(9), 847; https://doi.org/10.3390/axioms12090847 - 30 Aug 2023
Viewed by 769
Abstract
In order to study the dynamic mechanism of the impact of technological innovation diffusion on enterprise population networks, a corresponding relationship between enterprise population networks and predatory models was established based on a predatory model. Without considering the impact of technological innovation diffusion, [...] Read more.
In order to study the dynamic mechanism of the impact of technological innovation diffusion on enterprise population networks, a corresponding relationship between enterprise population networks and predatory models was established based on a predatory model. Without considering the impact of technological innovation diffusion, the stability of the enterprise population network was analyzed, and the results showed that it has the characteristic of local asymptotic stability at a positive equilibrium point. Considering the influence of technological innovation diffusion, the stability of the enterprise population network becomes complex, and its stability at the positive equilibrium point is also affected by the eigenvalue of the Laplacian matrix and technological innovation diffusion coefficient. The simulation experimental results indicate that in addition to the influence of technological innovation diffusion coefficient, the connection probability density of enterprise population networks has an important impact on stability. Only when the connection probability density is very small can the enterprise population network resist the impact of technological innovation diffusion and maintain stability. Full article
(This article belongs to the Special Issue Advances in Mathematical Methods in Economics)
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20 pages, 712 KiB  
Article
Assessing the Macroeconomic Consequences of External Financial Upheavals on China: A Caution of a Silicon Valley Bank’s Collapse
by Jingnan Wang and Yugang He
Axioms 2023, 12(8), 755; https://doi.org/10.3390/axioms12080755 - 1 Aug 2023
Cited by 3 | Viewed by 1679
Abstract
In the context of an increasingly interconnected global economy, deciphering the complex ripple effects of external financial disruptions on national economies is a task of utmost significance. This article dives deep into the intricate repercussions of such disturbances on the macroeconomic dynamics of [...] Read more.
In the context of an increasingly interconnected global economy, deciphering the complex ripple effects of external financial disruptions on national economies is a task of utmost significance. This article dives deep into the intricate repercussions of such disturbances on the macroeconomic dynamics of China using the example of the potential insolvency of a Silicon Valley bank. Grounded in empirical scrutiny, we leverage data spanning from Q1 2000 to Q1 2022 and the analytical utility of the impulse response function to illuminate our findings. We find that external financial tumult triggers a global recession, adversely impacting China’s export-driven economy while simultaneously unsettling aggregate output, employment levels, and wage stability. Simultaneously, these disruptions induce variability in consumption tendencies, investment trajectories, and import volumes and inject instability into interest rate paradigms. We also acknowledge the potential for currency depreciation and bank insolvency incidents to induce inflationary stresses, primarily by escalating the costs of imports. However, these inflationary tendencies may be offset by the concomitant economic slowdown and diminished demand inherent to global recessions. Importantly, the tightening of global credit conditions, coupled with existing financial ambiguities, may obstruct investment initiatives, curtail imports, and exert influence on both risk-free and lending interest rates. Our investigation also probes into the response of the Chinese government’s monetary policy to these external financial shocks. Despite the vital role of monetary policy in alleviating the impacts of these shocks, the potential secondary effects on China’s domestic economy warrant attention. Our study underscores the imperative of proper policy design rooted in a profound understanding of the intricate economic interdependencies for effective management and mitigation of the potentially detrimental consequences of such financial upheavals on China’s macroeconomic resilience within the tapestry of a tightly knit global financial ecosystem. Full article
(This article belongs to the Special Issue Advances in Mathematical Methods in Economics)
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19 pages, 1647 KiB  
Article
The Impacts of Digital Economy on Balanced and Sufficient Development in China: A Regression and Spatial Panel Data Approach
by Xiangyu Ge, Zunrong Zhou, Xia Zhu, Yonghong Wu and Yanli Zhou
Axioms 2023, 12(2), 113; https://doi.org/10.3390/axioms12020113 - 21 Jan 2023
Cited by 4 | Viewed by 1449
Abstract
The digital economy can change the proportions and types of production factors, gradually replace traditional backward production factors, reconstruct the division of labor and cooperation system, and improve productivity, which is an important basis for balanced and sufficient development. This paper measures the [...] Read more.
The digital economy can change the proportions and types of production factors, gradually replace traditional backward production factors, reconstruct the division of labor and cooperation system, and improve productivity, which is an important basis for balanced and sufficient development. This paper measures the comprehensive level of the digital economy and balanced and sufficient development, by using Chinese provincial panel data from 2013 to 2021, and uses the panel fixed effect model, mediation effect model, and spatial econometric model to examine the digital economy’s effect on balanced and sufficient development as well as the digital economy’s mechanism. The results show that the digital economy has significantly promoted balanced and sufficient development, though there are obvious regional heterogeneity and spatial spillover effects, and the relevant conclusions are still valid after an endogenous treatment and a robustness test. The total factor productivity is an important mechanism for the digital economy to affect balanced and sufficient development. Full article
(This article belongs to the Special Issue Advances in Mathematical Methods in Economics)
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16 pages, 644 KiB  
Article
Forecasting High-Dimensional Covariance Matrices Using High-Dimensional Principal Component Analysis
by Hideto Shigemoto and Takayuki Morimoto
Axioms 2022, 11(12), 692; https://doi.org/10.3390/axioms11120692 - 3 Dec 2022
Cited by 2 | Viewed by 1624
Abstract
We modify the recently proposed forecasting model of high-dimensional covariance matrices (HDCM) of asset returns using high-dimensional principal component analysis (PCA). It is well-known that when the sample size is smaller than the dimension, eigenvalues estimated by classical PCA have a bias. In [...] Read more.
We modify the recently proposed forecasting model of high-dimensional covariance matrices (HDCM) of asset returns using high-dimensional principal component analysis (PCA). It is well-known that when the sample size is smaller than the dimension, eigenvalues estimated by classical PCA have a bias. In particular, a very small number of eigenvalues are extremely large and they are called spiked eigenvalues. High-dimensional PCA gives eigenvalues which correct the biases of the spiked eigenvalues. This situation also happens in the financial field, especially in situations where high-frequency and high-dimensional data are handled. The research aims to estimate the HDCM of asset returns using high-dimensional PCA for the realized covariance matrix using the Nikkei 225 data, it estimates 5- and 10-min intraday asset-returns intervals. We construct time-series models for eigenvalues which are estimated by each PCA, and forecast HDCM. Our simulation analysis shows that the high-dimensional PCA has better estimation performance than classical PCA for the estimating integrated covariance matrix. In our empirical analysis, we show that we will be able to improve the forecasting performance using the high-dimensional PCA and make a portfolio with smaller variance. Full article
(This article belongs to the Special Issue Advances in Mathematical Methods in Economics)
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16 pages, 964 KiB  
Article
Strategic Alliances for Sustainable Development: An Application of DEA and Grey Theory Models in the Coal Mining Sector
by Chia-Nan Wang, Hoang-Phu Nguyen, Yen-Hui Wang and Nhat-Luong Nhieu
Axioms 2022, 11(11), 599; https://doi.org/10.3390/axioms11110599 - 28 Oct 2022
Cited by 1 | Viewed by 1615
Abstract
Sustainable development is a global trend and an economic priority for many governments. Although new energies can be considered good investments in green growth, they may lead to financial barriers to developing countries. The purpose of the study concentrates on an alternative solution [...] Read more.
Sustainable development is a global trend and an economic priority for many governments. Although new energies can be considered good investments in green growth, they may lead to financial barriers to developing countries. The purpose of the study concentrates on an alternative solution that increases the efficiency performance of current fossil energy industries. The study has combined two models of Data Envelopment Analysis (DEA) and Grey Theory in determining inefficient units to propose potential strategic alliances for sustainable development in the Vietnam Coal industry. Besides considering inputs and outputs in the models, the location of coal mines is also a key indicator in recommending good alliances. The results show that the collaborations between the Cao Son coal mine and the Coc Sau coal mine, and between the Nui Beo coal mine and the Vang Danh coal mine, bring the best improvement for sustainable development. The study suggests detailed strategies in action that enterprises and policymakers can refer to, to apply in practice. Full article
(This article belongs to the Special Issue Advances in Mathematical Methods in Economics)
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