Dynamic Threshold Approach Research Articles

A Threshold Effect of Financial Development on Natural Resource Rents-Sustainable Human Development Nexus: Empirical Evidence from Sub-Saharan Africa

Sub-Saharan African (SSA) nations are falling behind in human development when compared to other regions globally, despite their abundant natural resources. Several Sub-Saharan African states have an underdeveloped financial structure, leading to underutilization of natural resource profits for human development. This research examines how the level of financial development impacts the relationship between natural resource rents and sustainable human development in 40 SSA countries from 2005 to 2019. This research used the dynamic panel threshold (DPT) approach, an advanced econometric methodology designed to address concerns often seen in panel data such as endogeneity, cross-sectional dependence, and heterogeneity. The cointegration findings showed a long-term association among the variables. The dynamic panel threshold analysis showed that natural resource rent had a detrimental influence on human capital development when financial development was below a certain threshold. Conversely, the outcomes were different when financial development exceeded the threshold. Financial system progress in Sub-Saharan African states considerably uses resource windfalls to improve sustainable human development. This research conducted robustness tests by using alternative estimates excluding outlier sample countries and extra proxies. The conclusions remained unchanged. Policy suggestions were introduced to enhance the financial sector and improve institutional quality in order to ensure sustainable growth in the SSA area.

The effect of housing prices on tourism employment: Evidence from China

This study highlights the importance of the relationship between housing prices and tourism labour mobility. This study uses dynamic panel threshold approach to examine the nonlinear effect of housing prices on tourism labour mobility in Chinese mainland during the years 2000-2021. The empirical results show that rising housing prices are positively associated with tourism and its subsectors’ employment across different levels of housing prices. At the regional level, there exists regional heterogeneity of housing price affecting labour mobility within tourism industry and its subsectors in Eastern, Central and Western regions. Lastly, further discussion and policy suggestion are provided.

Foreign aid, institutional quality, and income inequality in Africa: A dynamic panel threshold approach

This study examines the impact of foreign aid and institutions on income inequality in 23 African countries during the period from 2005 to 2017. The study used a newly proposed novel dynamic panel threshold technique. The results of the study found an institutional quality threshold value of 1.622. Below the threshold, foreign aid was found to positively and significantly influence income inequality. However, above the threshold, the coefficient of foreign aid was negative with statistical significance. This implies that foreign aid tends to diminish income inequality in the presence of quality institutions. The study also used the quantile regression method to check for robustness. It showed that the conclusion between aid and inequality is the same in most of the quantiles (0.1 and 0.2). The findings can be worthwhile for sketching proper aid policies to lessen inequality. Policymakers in Africa should prioritize establishing high-quality institutions and developing measures to improve existing ones. Thus, aid could potentially reduce income inequality. This study suggests that it is important to note that aid programs can be effective when tailored to the particular needs and circumstances of each beneficiary country, as one-size-fits-all methods may not produce the anticipated outcomes.

Monetary Policy and Deleveraging of Microfinance Institutions in China: A Dynamic Threshold Approach

Monetary Policy and Deleveraging of Microfinance Institutions in China: A Dynamic Threshold Approach

Does the Impact of Artificial Intelligence on Unemployment among People with Disabilities Differ by Educational Level? A Dynamic Panel Threshold Approach

Does the Impact of Artificial Intelligence on Unemployment among People with Disabilities Differ by Educational Level? A Dynamic Panel Threshold Approach

Testing the environmental Kuznets curve hypothesis in the transport sector for OECD countries: a dynamic panel threshold approach.

This study tests the environmental Kuznets curve (EKC) hypothesis in the transport sector for 28 OECD countries from 1990 to 2019. As a novelty, the relationship between gross domestic product (GDP) and carbon dioxide (CO2) emissions from the transport sector is investigated with the estimation of the dynamic panel threshold regression based on the generalized method of moments (GMM) estimator by Seo and Shin (Seo and Shin, J Econom 2:169-186, 2016). This approach enables us to test EKC and capture possible nonlinearities between variables. Along with the analysis of the EKC hypothesis, our study also investigates the effects of road petroleum products consumption, renewable energy consumption, and trade openness on transport CO2 emissions. The threshold regression results, where GDP per capita is employed as the transition variable, support the nonlinear relationship between CO2 emissions from the transportation sector and GDP by rejecting the null hypothesis of no threshold effect. This finding indicates the existence of two different regimes, i.e., the lower and upper regimes, based on the optimum value of the GDP per capita. Economic growth damages the environment in the lower regime, whereas it improves environmental quality in the upper regime. Therefore, the results indicate the presence of an inverted U-shaped relationship and support the EKC hypothesis in the OECD transportation sector. As a result, it is concluded that achieving sustainable economic growth is critical for investing in environmentally friendly technologies required to achieve the goal of reducing transportation-related CO2.

Energy consumption auditing based on a generative adversarial network for anomaly detection of robotic manipulators

This paper presents a generative adversarial network (GAN)-based energy auditing and anomaly detection framework for the health and security monitoring of robotic manipulators. The system features two key components: a side-channel measurement of the energy consumption and a GAN model to learn the data patterns during normal operations only. Anomalies in energy consumption during online testing are then discovered as outliers to the normal data by scrutinizing the anomaly score produced by the discriminator of the GAN model. This semi-supervised network circumvents the need for vast data labeling and exploits the overfitting during the training stage, hence magnifying the difference between the normal patterns learned in training and the unobserved abnormal energy profiles in testing. Moreover, considering the physical aspects of the robotic manipulator, a modified GAN architecture containing multiple discriminators to account for distinct contributions from individual joints/motors. A dynamic thresholding approach that continuously updates the statistical characteristics of the anomaly score is also developed to detect outliers and mitigate the effect of environmental variations during system operation. The proposed framework is tested on the custom dataset for performance evaluation. The results demonstrate the feasibility of the proposed method, especially for detecting physical attacks, which achieves an accuracy of approximately 0.93 in instant-level detection and over 0.84 in event-level detection.

Enabling financial development: linking innovation and CO2 emissions through equity and credit financing.

Over the past decade, financial development has been a prominent debate for stakeholders and policymakers alike. Financial development are prerequisites for innovation and CO2 emissions, followed by the Paris Climate Summit (COP21). In the wake of the global economic recession, financial development continues to address CO2 emissions efforts. However, scant attention is paid to the role of financial development in innovation and CO2 emissions relationship, especially in the context of developing countries. The current study explores the relationship between innovation and CO2 emissions through moderating role of financial development, especially in the context of developing countries. Utilizing a dynamic panel threshold approach, the current study utilizes data from 26 countries between 1990 and 2014. Our findings reveal that innovation positively impacts the reduction of carbon emissions when the stock market value-to-private credit ratio is below 1.71, while an opposite effect is observed when the ratio exceeds this threshold. We believe that the findings broaden the debate on financial development in developing countries. The results revealed that developing countries should allocate their domestic resources to financial development and poverty reduction, rather than solely addressing environmental concerns. In addition, a more sustainable balance between innovation and CO2 emissions could benefit through financial development and the impact may be the result in terms of achieving sustainable development.

A new star detection approach for a satellite-onboard star tracker

Static thresholding-based or filtering and windowing-based star detection algorithms are the most commonly ones implemented on satellite-onboard star trackers. In this investigation, a new star detection algorithm is proposed. It segments stellar images using an adaptive dynamic thresholding approach, instead of a static one. Therefore, it allows the elimination of the non-uniform random noise in stellar images, and thus facilities and improves the detection of stars in such considered data. Another advantage of the proposed algorithm is that the processing is carried out on-line, which results in a reduced processing time. The performance of the designed algorithm is evaluated by means of established criterion, and obtained results are compared to those achieved by some tested literature approaches. For such a purpose, a set of stellar images is generated. This one deals with numerous types of random noise and different scenarios that can be encountered in space. The obtained results show that the proposed algorithm is more robust, faster and has a better ability to detect stars, compared to the tested literature methods.

International tourism and income inequality: The role of economic and financial development

The effect of tourism growth on tourism destinations’ income inequality is an important question for policymakers. In this study, we explore if this relationship is affected by economic and financial development and their interactions. We find that tourism growth affects a country’s income inequality differently. Post-redistribution, tourism growth eases income inequality in the lower economic development regime but may worsen income inequality in the upper economic development regime. However, tourism growth helps to alleviate income inequality in the lower financial development regime but may also lessen income inequality in the upper financial development regime. We also find some evidence that improving opportunities to access finance does a better job of helping to utilise the effect of tourism growth on easing income inequality in more developed nations rather than their counterparts. In line with these, our results also indicate that inflation tends to have different effects on income inequality, subject to the selection of thresholds. Our results are drawn from a dynamic panel threshold approach across 71 developed and developing countries during 1996–2016.

Non-linear Impacts of Public Debt on Growth, Investment and Credit: A Dynamic Panel Threshold Approach

This paper examines the effects of public debt on the growth rate, investment and domestic credit provided to private sector using the dynamic panel threshold regression method for a large number of developing countries, namely 53 (48) economies for growth and invest-ment (credit) regressions. Our results suggest that public debt does not have a significant impact on the economic growth rate. Despite a strong negative effect of public debt on the total investment, our results do not support the existence of a (strong) threshold effect of public debt on total (private) investment. On the other hand, we present evidence for a threshold effect of public debt on public investment and credit. More precisely, public debt leads to a reduction in public investment and credit when the public debt exceeds the estimated threshold levels. Since public debt matters for investment and credit, it is important to ensure fiscal discipline and prudence in the long term.

EXPORT DIVERSIFICATION AND THE GREEN ECONOMY: THE KEY ROLE OF ECONOMIC RISK

As countries propose to develop their green economy strategies to achieve sustainable development goals, many researchers and practitioners have analyzed the various factors affecting this special economy and how export diversification impacts the environment. However, there is limited knowledge about the link between export diversification and the green economy. Thus, this research study explored the impact of such diversification on the green economy by considering the role of economic risk. A new dynamic panel threshold approach was applied to the global panel data of 112 countries from 1995 to 2014. The results support the U-shaped correlation between export diversification and the green economy with an increase in economic risk. Export diversification tends to weaken the green economy when economic risk is at lower levels, but it improves the economy after reaching a certain level of economic risk. We also found that the green economy has a persistent effect over time. Under all economic risk levels, the previous level of green economy development promotes current green economy development. These findings thus provide policymakers with crucial implications.

Toward TR-PCB Bubble Detection via an Efficient Attention Segmentation Network and Dynamic Threshold

The detection of bubbles in images of TR-PCBs is a difficult task due to the need for precise subregional detection, fast processing speed, and high accuracy. The uneven illumination of the images further complicates the process of bubble segmentation. To address these issues, a TR-PCB bubble segmentation framework, the ECSA-EFA-DT framework, is proposed, which has two stages. In the first stage, an efficient channel and spatial attention (ECSA) module is designed to analyze complex background features by employing the complementary advantages of the channel and spatial position features. Then, an efficient feature-fused autoencoder (EFA) is proposed for region segmentation in TR-PCB images. In the second stage, a dynamic threshold (DT) approach based on maximizing the interclass variance and a sliding window is proposed to eliminate severe shadows and issues with uneven illumination in TR-PCB images. The DT approach segments the bubbles in each region and calculates the bubble rate more accurately than previous methods. The experimental results show that the proposed framework achieves superior performance in several quantitative metrics and is suitable for industrial applications, obtaining an average Dice score of 87.5% and an IoU score of 77.8% on the region segmentation test set, and a 0.312 ME value on the bubble segmentation test set.

Natural resource and entrepreneurship: Economic freedom matters

This paper sheds new light on the relationship between resource rents and entrepreneurship, conditional on economic freedom. In a sample of 101 countries, we demonstrate that resource rents encourage people to engage in counterproductive activities by lowering new business density when economic freedom is low. The findings hold up well to a variety of measures as well as forms of resource rents and economic freedom indicators. Additionally, in an effort to establish a threshold for economic freedom, a robustness test using the dynamic panel threshold approach shows that resource rents have asymmetric impacts on entrepreneurship both below and above a value of 7. Therefore, when economic freedom is low, resource rents enhance the incentive to choose rent-seeking activities (bribery, theft, and lobbying) over productive ones, leading to a diversion from the best use of resources and a lack of entrepreneurial spirit.

The Impact of Urbanization on CO2 Emissions in China: The Key Role of Foreign Direct Investment

ABSTRACT By adopting the dynamic panel threshold approach, this study assesses how foreign direct investment (FDI) shapes the causality between urbanization and CO2 emissions in China from 1996–2018. The results suggest that a rise in the pace of urbanization increases CO2 emissions, but this harmful effect becomes weaker after achieving a certain level of foreign capital. We also find that the more developed the technology, financial and government sectors, the more it can promote urbanization to reduce CO2 emissions. These results offer policy implications for China’s urban planning and environmental policy.

Renyi Joint Entropy-Based Dynamic Threshold Approach to Detect DDoS Attacks against SDN Controller with Various Traffic Rates

The increasing incidence of distributed denial-of-service (DDoS) attacks has made software-defined networking (SDN) more vulnerable to the depletion of controller resources. DDoS attacks prevent the SDN controller from processing all incoming data efficiently, potentially disrupting a network or denying legitimate users access to network services. Thus, the protection of the SDN controller is crucial, especially from the ones that exploit the SDN characteristics. In this paper, the authors propose an efficient detection approach for low- and high-rate DDoS attacks on the controller with a high detection rate and a low false positive rate by adapting a dynamic threshold algorithm rather than a static one and proposing a new rule-based detection mechanism. In addition, the proposed approach was evaluated using eight simulation scenarios representing all potential attacks against the SDN controller in terms of attack traffic rates (low or high), sources (either single or multiple hosts), and targets (single or multiple victims). The experiment results show that the proposed approach is more effective than the existing approaches based on attack detection and false positive rates.

A Dynamic Threshold Approach for Tarnished Plant Bug (Hemiptera: Miridae) Management in the Midsouthern U.S. Cotton.

One of the most economically important pests of cotton, Gossypium hirsutum L., in the midsouth region of the United States is the tarnished plant bug, Lygus lineolaris (Palisot de Beauvois, Hemiptera: Miridae). Tarnished plant bug populations across the region have exhibited widespread resistance to numerous insecticide classes. To minimize late season resistance development, reducing unwarranted applications during the late flowering period can aid in resistance management and potentially reduce input costs. Trials were conducted during 2019 and 2020 to evaluate the impacts of tarnished plant bug populations in the later flowering period of cotton by modifying or terminating threshold regimes during the later weeks of bloom. Results showed that dynamic thresholds altered at the fourth week of bloom or later can reduce the number of late season applications made with no penalty to yield. Additionally, when utilizing a week of bloom termination approach, no significant yield losses were seen when terminating applications after the fourth week of bloom. These data may offer an alternative method to managing tarnished plant bug populations during the later flowering period of midsouth cotton.

Task allocation in multi-robot system using resource sharing with dynamic threshold approach.

Task allocation is a fundamental requirement for multi-robot systems working in dynamic environments. An efficient task allocation algorithm allows the robots to adjust their behavior in response to environmental changes such as fault occurrences, or other robots’ actions to increase overall system performance. To address these challenges, this paper presents a Task Allocation technique based on a threshold level which is an accumulative value aggregated by a centralized unit using the Task-Robot ratio and the number of the available resource in the system. The threshold level serves as a reference for task acceptance and the task acceptance occurs despite resource shortage. The deficient resources for the accepted task are acquired through an auction process using objective minimization. Despite resource shortage, task acceptance occurs. The threshold approach and the objective minimization in the auction process reduce the overall completion time and increase the system’s resource utilization up to 96%, which is demonstrated theoretically and validated through simulations and real experimentation.

The impact of energy security on income inequality: The key role of economic development

While the literature has studied various factors affecting income inequality and the influence of energy security on the economy, knowledge is rather limited regarding the linkage between energy security and income inequality. Based on six indicators that capture four aspects of energy security including availability, accessibility, develop-ability, and acceptability, this research applies the dynamic panel threshold approach to explore whether they affect income distribution via global panel data of 68 countries over 2001–2018. The results support inverted U-shape impacts of energy security on income inequality with an improvement of economic development. Specifically, energy security tends to deteriorate income distribution in the early stages of economic development, while it improves income distribution upon reaching a certain level of development. Evidence also reveals that income inequality has a persistence effect over time. Previous income inequality enhances current inequality in a regime with low economic development, while this effect runs opposite in a regime with high development. These findings thus provide valuable implications to policymakers.

Inflation and financial development in sub-Saharan Africa

This paper analyses the relationship between inflation and financial development in sub-Saharan Africa. This issue is important because the level beyond which the inflation rate affects financial development in sub-Saharan Africa is not known, despite the underdeveloped financial system in the region. This paper presents a model in which inflation is endogenously determined, and uses a dynamic panel threshold approach which takes this factor into consideration to ensure improved results. The pure cross-section method and non-dynamic panel threshold approaches were also utilised. Strong evidence of a negative impact of inflation on financial development is obtained, which increases with a rise in inflation. An average inflation threshold of about 5% is established, below which a positive impact on financial development is found. There is, however, a negative relationship beyond the observed threshold. The paper provides policy recommendations as to how authorities should contain inflation to facilitate financial sector development in the region.