Traditional Panel Research Articles

Navigating the green growth spectrum: Exploring the synergy between geopolitical risk, environmental policy stringency, and green production practices

The deepening understanding of the environment has heightened our perception of the causes of environmental damage, promoting a shift from combating pollution to preventing it with a core emphasis on environmental protection. Academicians and governance authorities have shifted their focus from traditional production practices to green production practices (GPP). The current body of literature has explored the impact of GPP on environmental quality. Whereas, the implications of geopolitical risk (GPR) and environmental policy stringency (EPS) on GPP are still unexplored. Keeping in view these gaps in existing research, this research is the earliest endeavor to examine the impact of GPR and EPS on GPP for the group of seven (G-7) countries from 1990 to 2020. In this regard, we have applied panel quantile regression (PQR) which allows for a more flexible treatment of heterogeneity and is robust to deal with outliers and skewed distributions compared to traditional panel data techniques. The empirical findings reveal that GPR has a significant destructive impact on GPP whereas, the EPS upsurge the GPP in G-7 countries. Founded on the factual outcomes, we recommend policy recommendations to achieve the objectives of SDG 07 (affordable and clean energy), SDG 08 (exports for decent economic growth), SDG 09 (industry innovation and infrastructure), SDG 11 (sustainable cities and societies), SDG 12 (responsible consumption and production), SDG 13 (environmental policies for climate action), and SDG 16 (conflict, peace, and justice strong institutions).

The 2023 Magruder-Newman Prizes

ABSTRACT The Magruder-Newman Prizes are new awards to recognize student work presented at the annual meeting of the PHA. Each prize carries an award of $125 plus a one-year membership in the Association. One prize will go to the best student work presented at the Student Research Session, and the other will be awarded to the best student work presented at a traditional panel. The award has been endowed by Dr. Paul Douglas Newman, a PHA member since 1993, Council Member, and prior Editor of Pennsylvania History in honor of his parents Margaret L. Magruder-Newman and F. Douglas Newman. The first awards were presented October 27, 2023, at the PHA annual meeting in Harrisburg.

Ranking-based second stage in data envelopment analysis: An application to research efficiency in higher education

An alternative approach for the panel second stage of data envelopment analysis (DEA) is presented in this paper. Instead of efficiency scores, we propose to model rankings in the second stage using a dynamic ranking model in the score-driven framework. We argue that this approach is suitable to complement traditional panel regression as a robustness check. To demonstrate the proposed approach, we determine research efficiency of higher education systems at country level by examining scientific publications and analyze its relation to good governance. The proposed approach confirms positive relation to the Voice and Accountability indicator, as found by the standard panel linear regression, while suggesting caution regarding the Government Effectiveness indicator.

Political Stability, Corruption, and Economic Development : Evidence frim WAMZ Countries

The paper has analyzed the political stability, corruption and economic development in the West African Monetary Zone (WAMZ) countries for the period of 2000 to 2020. The common properties of the panel data were first checked to avoid mis-specification bias and hence biased statistical results. Firstly, the CD test revealed no evidence/absence of cross sectional dependence among the countries which validates the use of traditional panel unit root that does not take account of cross-sectional dependence. The results of panel unit root test proposed by Levin et al (2002) revealed that the variables are integrated of order zero i.e. I (0). Based on this, the paper explores within the panel VAR framework. Evidence from impulse response functions revealed that, political stability and rule of low are economic development promoters while corruption hampers economic development in the region. The results from variance decomposition indicate that the variables under study contribute or hinder economic development in the WAMZ countries. Based on the results the paper recommends that, transparency and accountability at all level of government affairs as well as respecting the constitution in these nations should be preserved in order to overcome all social and political injustice among the countries under study.

Thermal-Aeroelastic Investigation of a Hypersonic Panel Vibration Based on a Developed MMC Method

Hypersonic vehicles or engines usually employ complex thermal protecting shells. This sometimes brings multi-physics difficulties, e.g., thermal-aeroelastic problems like panel flutter etc. This paper aims to propose a novel optimization method versus thermal dynamic influence on panel vibration. A traditional panel structure was modelled and analyzed. After analyzing its dynamic characteristics of panel flutter, thermal effects were also included to propose thermal-aeroelastic analysis results of the present hypersonic panel. Then, a MMC (Moving Morphable Component) method was proposed to suggest dynamic optimization for such panel structures. The proposed method can provide arbitrary frequency control result in order to suggest a newly generated panel structure. Based on the optimal structures, dynamic analysis was presented again to verify the effectiveness of the optimization method. So aero-thermo-dynamic characteristics of the optimal panel structures could be investigated. It can be seen that the computational results presented significantly improved panel flutter results. The proposed dynamic optimization method can be employed for the design of panel structures versus high combustion temperatures or hypersonic aerodynamics.

Relationship between the terminal built environment and airport retail revenue

Non-aeronautical business, including airport retail, is an essential source of airport revenue. The locations of retail stores in an airport terminal building significantly impact their revenue. Based on the retail store-level data from Dalian Zhoushuizi International Airport (DLC), the traditional panel data regression and machine learning methods were employed to explore the relationships between the terminal built environment and airport retail revenue. The results indicate the following: (1) non-linear relationships exist between airport retail store revenue and the terminal built environment. (2) Airport passenger traffic is still the principal factor in retail store revenue. (3) Variables including area, function halls, and per capita spending have different impacts on the revenue of food and beverage (F&B) and specialty retail (SR) stores. The optimal location sites for retail stores are as far away from the nearest washroom as possible while being as close to gates as possible.

LIFE CYCLE ASSESSMENT OF LOW CARBON SANDWICH PANELS WITH WOOD FIBRE CORE

AbstractWood is a popular material in civil engineering due to its renewability and ability to store carbon during the growing in forests. However, the LCA of wood‐based materials is currently based on the balance of carbon without considering the dynamic changes of forests over time and the effects of climate change, like wildfires, on this balance. Hence, this paper is the first step towards the development of a dynamic LCA of forests considering climate change effects on the carbon balance of forests. The paper focusses on the life cycle analysis of sandwich panels with a core made of wood fibers, based on current databases, and aims to illustrate the importance of biogenic carbon in the whole life cycle of such panels, particularly when compared with other traditional panels.

The attenuating effect of green finance on environmental quality and its mechanism: Spatial modified PTRM model

The traditional Panel Threshold Regression Model (PTRM) neglects spatial factors, causing model bias in prior research on green finance's environmental impact. To address this shortcoming, a Spatial Modified PTRM Model is constructed to investigate green finance's spatial threshold effects on the environment. Moreover, this study analyzes temporal and regional heterogeneities and explores the influence mechanisms underlying the observed attenuating in environmental effects. Results show that: (1) The "more developed, less effective" phenomenon in green finance's environmental impact is confirmed, instead of cumulative enhancement, as green finance intensity surpasses thresholds around −0.48 to −0.61, its effects decrease by approximately 66.3%–156.1% units. (2) Temporal and regional heterogeneities in the attenuating phenomenon are explored, in 2015, the attenuation phenomenon initiates, transitioning from statistical ''insignificance'' to ''significance'', from ''rapid development'' to ''plateau'', and from ''single high-value peak'' to ''single low-value peak'', also, developed green finance regions experience the most significant attenuation, up to 76.0% more pronounced than less developed regions. (3) The unbalanced regional distribution and the free-riding phenomenon are confirmed as two factors contributing to the attenuation, with the ellipse center shifting southward and the index deviating since around 2015, meanwhile, the free-riding intensity has increased over time, surging from around 0.10 in the early stages to approximately 0.40 in 2021.

ICT and Environmental Quality: A South Asian Perspective

Purpose: The contributions of ICT—and how it either improves or worsens environmental quality, or has no effect at all—have drawn significant scholarly attention in recent decades in an effort to address the current environmental concerns. The aim of this study is to examine the empirical correlate in South Asia between ICT & quality of the environment., exploring the environmental impacts of ICT and developing a conceptual framework to understand how ICT influences environmental conditions.
 Design/Methodology/Approach: The empirical framework for this research is designed by constructing two separate indexes for ICT and Environmental Quality by using Principal Component Analysis. The estimation methodology is followed by applying traditional Panel data approach i.e. POLS, FEM, REM, Driscoll and Kraay standard error for precision.
 Findings: The outcomes show a substantial relationship between environmental quality and ICT usage. As per the findings, ICT reduces GHG emissions and enhances Environmental Quality. Whereas, Economic Growth and Financial Development deteriorates the Environmental Quality by increasing GHG emissions.
 Implications/Originality/Value: This study specifies the analysis that ICT usage contribute positively to Environmental Quality by lowering GHG emissions, if and only if productively used by endorsing ICT-driven sustainable development for economic success with minimal environmental impacts.

Environmental evaluation of experimental heat-treated oriented strand board

The use of wood-based panels such as Oriented Strand Board has grown in civil construction. This follows the contemporary trend towards low environmental impact materials. However, there is a lack of relevant information about their life cycle assessment, appearing as a current and relevant research topic. Experimental panels made with Eucalyptus wood and castor oil-based polyurethane adhesive already demonstrated great physical-mechanical performance. Therefore, this study aimed to continue the evaluation of this innovative product, estimating their potential environmental impacts using life cycle assessment from a cradle-to-gate perspective and comparing the results with traditional panels and literature data. System boundaries, environmental impacts and environmental hotspots were identified using the ReCiPe H method in terms of ten impact categories. Comparing experimental (heat-treated) and traditional panels, the experimental versions performed better in most categories and showed safer behavior in categories related to human health in addition to not using paraffin, termiticide, and other organic chemicals presented in the traditional panels. Though made of different types of adhesives, the adhesive was the main environmental hotspot for both types.

European equity markets volatility spillover: Destabilizing energy risk is the new normal

AbstractWhile energy risk is increasingly recognized as a systemic risk, there is limited comprehensive analysis of the risk propagation in regional contexts. In this study, we examine oil and natural gas price changes and shocks in relation to equity market returns and volatility for 24 European Economic Area (EEA) countries. In addition to traditional panel regressions, we also deploy the Diebold‐Yilmaz (2014) spillover index for a closed network analysis. We differentiate in the cross‐section across the core EU block, PIIGS countries, EU enlargement countries joining after 2004, and other non‐EU countries, to provide insights into the ongoing debates on the European energy market stability. While we find evidence of the manifestation of energy risk throughout the sample period, we find that until 2019 the primary sources of volatility spillover in the EEA economic network arose from economic or political uncertainty. Energy risks, measured by large crude oil and natural gas price shocks also significantly contributed to equity market volatility, with increasing volatility risk arising from natural gas, a green labelled energy source after 2019. Last, we show that CEEC equity markets are more sensitive to oil and natural gas price shocks when domestic currencies depreciate against the Euro.

A Comparative Regression Analysis between Principal Component and Partial Least Squares Methods for Flight Load Calculation

This study investigates and compares various multivariate regression methods, including principal component regression (PCR) and partial least squares regression (PLSR), for flight load analysis and demonstrates their high learning efficiency and strong generalization capabilities, making them highly suitable for this purpose. The flight load data of a civil aircraft use altitude, Mach number and load factors as input parameters, which are used as sample data to establish regression models for predicting wing loads under different flight conditions. The accuracy of all regressions are confirmed through evaluation, with PLSR being the most efficient. In the comparison of computational times, it was found that the computational efficiency of regression methods was significantly superior to traditional panel methods. The flight load calculation shows that PCR and PLSR can significantly improve analysis efficiency and provide new insights into efficient flight load analysis.

A Study on OLED Cell Simulation and Detection Phases Based on the A2G Algorithm for Artificial Intelligence Application

In this study, we demonstrate the viability of applying artificial intelligence (AI) techniques to conduct inspections at the OLED cell level using simulated data. The implementation of AI technologies necessitates training data, which we addressed by generating an OLED dataset via our proprietary A2G algorithm, integrating the finite element method among concerns over data security. Our A2G algorithm is designed to produce time-dependent datasets and establish threshold conditions for the expansion of dark spots based on OLED parameters and predicted lifespan. We explored the potential integration of AI in the inspection phase, performing cell-based evaluations using three distinct convolutional neural network models. The test results yielded a promising 95% recognition rate when classifying OLED data into pass and fail categories, demonstrating the practical effectiveness of this approach. Through this research, we not only confirmed the feasibility of using simulated OLED data in place of actual data but also highlighted the potential for the automation of manual inspection processes. Furthermore, by introducing OLED defect detection models at the cell level, as opposed to the traditional panel level during inspections, we anticipate higher classification rates and improved yield. This forward-thinking approach underscores significant advancement in OLED inspection processes, indicating a potential shift in industry standards.

Again, the Personal is Political and Psychoanalytic: Sue Grand and Jill Salberg in Conversation with Masha Borovikova Armyn

ABSTRACT In the papers by Sue Grand and Jill Salberg that form the panel, When the Personal Helps Us Write the Political, both authors use autobiography to activate the text as they explore ever more elusive dimensions of whiteness. In lieu of the traditional panel discussion, a more personal approach seemed fitting. In conversation with interviewer Masha Borovikova Armyn, the stakes involved in exposing personal and political struggles on the written page are examined both as acts of storytelling and, at a more granular level, in marks of a social unconscious that peeks out of the text in decisions such as how to spell racialized terms.

Thermal performance and condensation analysis of insulated concrete panels using a thermal-meta structure

Sandwich panels are widely employed in warehouses and factories due to their cost-effectiveness and workability. However, recent major fires in Korea, caused by the combustion of sandwich panels, have necessitated the development of limited combustible panels wgyith comparable thermal performance. In this study, we introduce an innovative panel that satisfies both fire resistance and insulation performance requirements. The panel comprises a fire-resistant concrete-based material and a honeycomb insulation material for enhanced insulation. The experimental results demonstrate that the developed honeycomb-meta precast concrete panel exhibits excellent insulation and fire resistance, outperforming traditional panels with an 18% higher flame retardancy. The panel effectively mitigates common issues typically encountered in prefabricated panels, such as decreased insulation performance and condensation at connection points. These findings highlight the potential of the developed panel in various construction applications, particularly in buildings requiring superior fire resistance and insulation performance.

Research on Panel Flutter Considering the Effect of Convective Active Cooling

The aeroelastic characteristics of the panel under the action of coolant are obviously different from the flutter characteristics of the traditional panel. In order to solve this problem, the dynamics model of the panel flutter was established in this paper based on von Karman’s large deformation theory and the Kirchhoff–Love hypothesis. The panel dynamics equations were discretized into constant differential equations with finite degrees of freedom by Galerkin’s method, and solved by the fourth Runge–Kutta method in the time domain. The nonlinear modified piston theory was used to predict the unsteady aerodynamic loads, and the accuracy of the flutter analysis model was verified. On this basis, the effects of the head-panel pressure of coolant, the pressure drop ratio, the coolant injection direction, and the inertial resistance and viscous resistance on panel stability and flight stability were investigated, respectively. The results showed that reducing the pressure drop ratio, and reducing or increasing the head-panel pressure (valuing away from the freestream pressure) can improve the critical dynamic pressure when bifurcation occurs. At M∞=5.0, the pressure drop ratio causes a 22.1% increment in the critical dynamic pressure. The influence of the coolant injection direction on the panel bifurcation is mainly influenced by the head-panel pressure. The inertial resistance slows down the convergence process of the panel response, increases the limit cycle amplitude, and reduces the critical dynamic pressure of the panel, while the viscous resistance plays the opposite role. Based on these conclusions, this paper finally proposes the suppression method of panel fluttering from head-panel pressure, inertial resistance, viscous resistance, etc.

Enhancement of Grid and Face Element Amendment in Aeroelasticity Analysis by Advanced Self-Adaptive Computing Method

This research presents a novel approach for enhancing the accuracy and efficiency of aeroelasticity analysis through the combination of grid optimization and face element amendment techniques. The study focuses on improving the precision of a low order panel method by performing piecewise linear amendment based on Computational Fluid Dynamics (CFD) aerodynamic loads data under varying angles of attack. Additionally, the distribution of face element calculating grid is optimized using visual evoked potential estimation. The proposed method addresses the limitations of traditional panel methods that heavily rely on grid distribution and offers a more robust and accurate solution. The optimized grid not only maintains the computational efficiency of the panel method but also ensures closer approximation of wing stresses to CFD data, thus enhancing the precision and efficiency of aeroelasticity optimized iterative design processes. The results obtained from this research demonstrate effective compensation for the shortcomings of the panel method and a significant improvement in the computational efficiency of aerodynamic loading in the presence of changing structural stiff parameters.

Stool biomarkers as measures of enteric pathogen infection in infants from Addis Ababa informal settlements.

Frequent enteric infections in children may be an important cause of growth faltering; however, we do not fully understand the mechanisms by which pathogen infections and the physiological responses to these infections result in poorer growth. Commonly used protein fecal biomarkers (anti-alpha trypsin, neopterin, and myeloperoxidase) provide broad immunological information on an inflammatory response; however, they do not provide information on non-immune processes (e.g., gut integrity) that may be important indicators of chronic end states such as environmental enteric dysfunction (EED). To explore how additional biomarkers will better inform which physiological pathways (both immune and non-immune) are impacted by pathogen exposure we added to the traditional panel of 3 protein fecal biomarkers 4 novel fecal mRNA transcript biomarkers (sucrase isomaltase, caudal homeobox 1, S100A8, and mucin 12) and analyzed stool samples from infants living in informal settlements in Addis Ababa, Ethiopia. To test how this expanded biomarker panel captures distinct pathogen exposure processes we used two different scoring systems. First, we used a theory-based approach to assign each biomarker to specific physiological attributes based on prior understanding of each biomarker. Second, we used data reduction methods to categorize biomarkers and then assign physiological attributes to those categories. We used linear models to examine the association between the derived biomarker scores (based on mRNA and protein levels) and stool pathogen gene counts to determine pathogen specific effects on gut physiology and immune responses. Inflammation scores were positively associated with Shigella and enteropathogenic E.Coli (EPEC) infection, while gut integrity scores were negatively associated with Shigella, EPEC and, shigatoxigenic E.coli (STEC) infection. Our expanded panel of biomarkers hold promise as tools to measure systemic outcomes of enteric pathogen infection. mRNA biomarkers complement established protein biomarkers by providing important cell-specific physiological and immunological consequences of pathogen carriage that can lead to chronic end states such as EED.

The Internal Determinants of Gender Diversity and Its Non-Linear Impact on Firms’ Performance: Evidence from the Listed Companies in Palestine Exchange

This study mainly aims to test the impact of gender diversity on a firm’s performance. Namely, the non-linear and the quantile impact on the listed companies in Palestine Exchange during the period 2010 to 2020. The study also aims to determine the impact of a firm’s internal characteristics on gender diversity. The study uses instrument analysis, traditional panel models, and quantile regression to fulfil the aims. The results demonstrate the existence of a critical mass for the impact of gender diversity on firms’ performance and that mass is about 30% for the ROA and 41% for the EPS.

Knowledge and Economic Growth: A Dynamic Panel Data Analysis for OECD Countries

This paper aims to investigate the role of knowledge in the economic growth convergence of the OECD member countries during the 1995-2011 period, by utilizing the production function approach. In our augmented production function framework, in addition to human capital, we consider other important channels of knowledge (R&D, trade and ICTs) to understand how knowledge contributes to the growth performance and growth convergence of the OECD countries. Furthermore, in contrast to most of the existing studies which used traditional panel data analysis, this study utilizes dynamic panel data techniques. This approach enables us to utilize the long-run information in the data and hence gives us the possibility to analyze the impact of knowledge indicators on economic growth by focusing on equilibrium relations over a longer time horizon. The empirical results suggest a positive impact of knowledge indicators on the economic growth performances of OECD countries and that there is convergence to a common long-run equilibrium in OECD.