Discrete Dynamics in Nature and Society
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Acceptance rate13%
Submission to final decision127 days
Acceptance to publication23 days
CiteScore2.000
Journal Citation Indicator0.410
Impact Factor1.4

Competition, Survival Issue, and Performance Constraints of Banks: Evidence from Ethiopian Private Commercial Banks

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Discrete Dynamics in Nature and Society publishes research that links basic and applied research relating to discrete dynamics of complex systems encountered in the natural and social sciences.

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Chief Editor, Dr Renna, is an associate professor at the University of Basilicata, Italy. His research interests include manufacturing systems, production planning and enterprise networks. 

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We currently have a number of Special Issues open for submission. Special Issues highlight emerging areas of research within a field, or provide a venue for a deeper investigation into an existing research area.

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Research Article

Carbon Market Efficiency and Economic Policy Uncertainty: Evidence from a TVP-VAR Model

This paper examines the dynamic linkages among economic policy uncertainty (EPU), the green bond market, the carbon market, and the macroeconomy using the time-varying parameter vector autoregressive (TVP-VAR) model with monthly data spanning from January 2016 to December 2021. Additionally, it assesses the robustness and accuracy of the empirical results through the Bayesian vector autoregressive (BVAR) model. The findings indicate that EPU negatively affects the green bond market in the short term but has a positive impact in the medium and long term. Conversely, EPU has a positive impact on the carbon market in the short term but a negative impact in the medium and long term. Furthermore, the green bond market negatively influences the carbon market in both the short and medium to long term. These results suggest that emerging markets, such as the green bond and carbon markets, are influenced by EPU. The adverse impact of the green bond market on the carbon market, however, contributes to expediting China’s attainment of its low-carbon objectives. Appropriate economic policies can play a vital role in accelerating the transition to a low-carbon economy. The study also reveals that the US-China trade war has expedited the development of green capital markets in China, despite its impact on the green economic transition in the country. These findings provide insights for the government and investors to formulate suitable strategies for risk mitigation.

Research Article

Global Flow of Foreign Aid and Change in Recipients’ Local Labor Institutions

How does foreign aid affect recipient countries’ labor institutions? Extant empirical evidence is sparse due to ambiguous theoretical predictions and potential endogeneity issues. This study uses data detailing aid flow and institutional functions to mitigate such inconclusiveness and displays originality by constructing a concise theoretical framework in which foreign aid contributes to the improvement of the labor institutions in recipient countries through two mechanisms—economic growth purpose and expected aid attraction. The findings indicate that only aid to enhance local economic growth provides incentives to change domestic labor markets. Such effects have a more crucial influence on labor institutions of minimum wage, collective bargaining rights, and working hours than those related to hiring and firing regulations, mandated costs for worker dismissal, and conscription. For comparison with the actual aid level, we construct forecasted proxies to capture exogenous fluctuations in aid, determining that domestic labor markets can also change via a novel mechanism, as the recipient voluntarily mimics the funder’s labor policies in anticipation of receiving future aid, with exact amounts derived from the noninstitutional characteristics of pairs of bilateral recipient and giver economies. Therefore, we provide policy implications for the aid giver on how to secure a continued and increased aid flow and for the aid receivers on which aspects of reforming measures are most effective in enhancing the labor market regulations.

Research Article

A Model for the Propagation and Control of Pulmonary Tuberculosis Disease in Kenya

Pulmonary tuberculosis is among the leading infectious diseases causing mortality worldwide. Therefore, scaling up intervention strategies to reduce the spread of infections in the population is imperative. In this paper, a population-based compartmental approach has been employed to formulate a mathematical model of pulmonary tuberculosis that incorporates an asymptomatic infectious population. The model includes asymptomatic infectious individuals since they spread infections incessantly to susceptible populations without being noticed, thus contributing to the high rate of infection transmission. Qualitative and numerical analyses were performed to determine the impact of various intervention strategies on controlling infection transmission in the population. Sensitivity and numerical results indicate that increasing screening of latently infected and asymptomatic infectious individuals reduces infection transmission to the susceptible population. Numerical results demonstrate that the combination of vaccination, screening, and treatment of all forms of pulmonary tuberculosis is the most effective intervention in decreasing infection transmission. Furthermore, a combination of screening and treatment of all forms of pulmonary tuberculosis proves more effective than a combination of vaccination and treatment of symptomatic infectious individuals alone. Treating the symptomatic infectious population alone is identified as the least effective intervention for curtailing infection transmission in the susceptible population. These study findings will guide healthcare officials in making decisions regarding the screening of latently infected and asymptomatic infectious pulmonary tuberculosis patients, thereby aiding in the fight against epidemics of this disease.

Research Article

Price-Volume Relationship in Bitcoin Futures ETF Market: An Information Perspective

Bitcoin futures exchange-traded funds (ETFs) are recent innovations in cryptocurrency investment. This article studies the price-volume relationship in this market from an information perspective. We first propose effective mutual information which has better estimation accuracy to analyze the contemporaneous relationship. Using half-hourly trading data of the world’s largest Bitcoin futures ETF, we find that trading volume changes and returns contain information about each other and are contemporaneously dependent. Then, we employ effective transfer entropy to examine the intertemporal relationship. The results show that there exists information transfer from volume changes to returns in most of our sample period, suggesting the presence of return predictability and market inefficiency. However, information transfer in the opposite direction occurs much less frequently, and the amount is typically smaller.

Research Article

Bézier Cubics and Neural Network Agreement along a Moderate Geomagnetic Storm

The discussion models the IRI-2012 TEC map over a moderate geomagnetic storm period (5 days) in February 2015 and compares the yield of the models. The models are constructed with the help of cubic Bézier curves and machine learning. In a sense, the comparison of a classical and mechanical approach with a modern and computer-based one is a considerable experience for the paper. The parametric curve approach governs models of piecewise continuous Bézier cubics, while the models employ only the TEC map. The design is separated into curve components at every five-hour curvature point, and each component is handled independently. Instead of the traditional least squares method for finding control points of cubics, it utilizes the mean of every five-hour of the piecewise curves of the TEC data. Accordingly, the prediction error can be controlled at a rate that can compete with the modern network approach. In the network model, 120 hours of the solar wind parameters and the TEC map of the storm are processed. The reliability of the network model is assessed by the (R) correlation coefficient and mean square error. In modeling the TEC map with the classical approach, the mean absolute error is 0.0901% and the correlation coefficient (R) score is 99.9%. The R score of the network model is 99.6%, and the mean square error is 0.71958 (TECU) (at epoch 47). The results agree with the literature.

Research Article

Dynamic Analysis of a Simple Cournot Duopoly Model Based on a Computed Cost

The paper is organized to study some mathematical properties and dynamics of a simple Cournot duopoly game based on a computed quadratic cost. The time evolution of this game is described by a two-dimensional noninvertible discrete time map using the bounded rationality mechanism. For this map, some dynamic characteristics such as multistability and synchronization are investigated. Its equilibrium points are obtained for the asymmetric case, and their conditions of stability are obtained. Our results investigate that the Nash equilibrium point may be unstable due to flip bifurcation and under certain parameter values, and Neimark–Sacker bifurcation is born after the period-4 cycle. Through some restrictions, the coordinate axes of the map construct an invariant manifold, and therefore, their dynamics can be analyzed by using a one-dimensional map. In the symmetric case, both firms behave identically, and this implies that the diagonal set forms an invariant manifold, and hence the synchronization phenomena take place. Furthermore, the global bifurcation of the map is confirmed through contact between critical curves and the boundaries of infeasible domains.

Discrete Dynamics in Nature and Society
 Journal metrics
See full report
Acceptance rate13%
Submission to final decision127 days
Acceptance to publication23 days
CiteScore2.000
Journal Citation Indicator0.410
Impact Factor1.4
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