Search results for: panel regression

Authors: Liaquat Ahmad, Muhammad Aslam, Muhammad Azam

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In this article, we propose a control chart based on repetitive group sampling scheme for the location parameter. This charting scheme is based on the regression estimator; an estimator that capitalize the relationship between the variables of interest to provide more sensitive control than the commonly used individual variables. The control limit coefficients have been estimated for different sample sizes for less and highly correlated variables. The monitoring of the production process is constructed by adopting the procedure of the Shewhart’s x-bar control chart. Its performance is verified by the average run length calculations when the shift occurs in the average value of the estimator. It has been observed that the less correlated variables have rapid false alarm rate.

Keywords: average run length, control charts, process shift, regression estimators, repetitive group sampling

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Authors: Jamel Boukhatem, Semia Rachid, Marmar Nasr

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Considering the differences between oil- and non-oil-producing countries, this paper aims to evaluate the impact of financial development (FD) and institutional quality (IQ) on CO2 emissions in 15 MENA (Middle East and North Africa) countries over the period 1996-2018 using the Panel ARDL approach. We found evidence to support an unconditional long run effect of FD on environmental conditions (EC), with quite significant differences between the two groups of countries. While FD leads to environmental degradation (ED) in non-oil-producing countries, it helps protect the environment in oil-producing ones. Regarding the effects of IQ on EC, they are not significant in both short- and long run for non-oil-producing countries, but they are significant for oil-producing ones only in the long run. In the short run, IQ indicators haven’t significant effects on EC for the two groups of countries.

Keywords: financial development, institutional quality, environmental conditions, Panel ARDL

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Authors: Gianna Zou

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Propensity score matching (PSM), introduced by Paul R. Rosenbaum and Donald Rubin in 1983, is a popular statistical matching technique which tries to estimate the treatment effects by taking into account covariates that could impact the efficacy of study medication in clinical trials. PSM can be used to reduce the bias due to confounding variables. However, PSM assumes that the response values are normally distributed. In some cases, this assumption may not be held. In this paper, a machine learning method - Bayesian Additive Regression Tree (BART), is used as a more robust method of matching. BART can work well when models are misspecified since it can be used to model heterogeneous treatment effects. Moreover, it has the capability to handle non-linear main effects and multiway interactions. In this research, a BART Matching Method (BMM) is proposed to provide a more reliable matching method over PSM. By comparing the analysis results from PSM and BMM, BMM can perform well and has better prediction capability when the response values are not normally distributed.

Keywords: BART, Bayesian, matching, regression

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Authors: Katarzyna Lubecka, Kirsty Flower, Megan Beetch, Lucinda Kurzava, Hannah Buvala, Samer Gawrieh, Suthat Liangpunsakul, Tracy Gonzalez, George McCabe, Naga Chalasani, James M. Flanagan, Barbara Stefanska

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Hepatocellular carcinoma (HCC), the most prevalent type of primary liver cancer, is the second leading cause of cancer death worldwide. Late onset of clinical symptoms in HCC results in late diagnosis and poor disease outcome. Approximately 85% of individuals with HCC have underlying liver cirrhosis. However, not all cirrhotic patients develop cancer. Reliable early detection biomarkers that can distinguish cirrhotic patients who will develop cancer from those who will not are urgently needed and could increase the cure rate from 5% to 80%. We used Illumina-450K microarray to test whether blood DNA, an easily accessible source of DNA, bear site-specific changes in DNA methylation in response to HCC before diagnosis with conventional tools (pre-diagnostic). Top 11 differentially methylated sites were selected for validation by pyrosequencing. The diagnostic potential of the 11 pyrosequenced probes was tested in blood samples from a prospective cohort of cirrhotic patients. We identified 971 differentially methylated CpG sites in pre-diagnostic HCC cases as compared with healthy controls (P < 0.05, paired Wilcoxon test, ICC ≥ 0.5). Nearly 76% of differentially methylated CpG sites showed lower levels of methylation in cases vs. controls (P = 2.973E-11, Wilcoxon test). Classification of the CpG sites according to their location relative to CpG islands and transcription start site revealed that those hypomethylated loci are located in regulatory regions important for gene transcription such as CpG island shores, promoters, and 5’UTR at higher frequency than hypermethylated sites. Among 735 CpG sites hypomethylated in cases vs. controls, 482 sites were assigned to gene coding regions whereas 236 hypermethylated sites corresponded to 160 genes. Bioinformatics analysis using GO, KEGG and DAVID knowledgebase indicate that differentially methylated CpG sites are located in genes associated with functions that are essential for gene transcription, cell adhesion, cell migration, and regulation of signal transduction pathways. Taking into account the magnitude of the difference, statistical significance, location, and consistency across the majority of matched pairs case-control, we selected 11 CpG loci corresponding to 10 genes for further validation by pyrosequencing. We established that methylation of CpG sites within 5 out of those 10 genes distinguish cirrhotic patients who subsequently developed HCC from those who stayed cancer free (cirrhotic controls), demonstrating potential as biomarkers of early detection in populations at risk. The best predictive value was detected for CpGs located within BARD1 (AUC=0.70, asymptotic significance ˂0.01). Using an additive logistic regression model, we further showed that 9 CpG loci within those 5 genes, that were covered in pyrosequenced probes, constitute a panel with high diagnostic accuracy (AUC=0.887; 95% CI:0.80-0.98). The panel was able to distinguish pre-diagnostic cases from cirrhotic controls free of cancer with 88% sensitivity at 70% specificity. Using blood as a minimally invasive material and pyrosequencing as a straightforward quantitative method, the established biomarker panel has high potential to be developed into a routine clinical test after validation in larger cohorts. This study was supported by Showalter Trust, American Cancer Society (IRG#14-190-56), and Purdue Center for Cancer Research (P30 CA023168) granted to BS.

Keywords: biomarker, DNA methylation, early detection, hepatocellular carcinoma

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Authors: Florin Leon, Silvia Curteanu

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Developing complete mechanistic models for polymerization reactors is not easy, because complex reactions occur simultaneously; there is a large number of kinetic parameters involved and sometimes the chemical and physical phenomena for mixtures involving polymers are poorly understood. To overcome these difficulties, empirical models based on sampled data can be used instead, namely regression methods typical of machine learning field. They have the ability to learn the trends of a process without any knowledge about its particular physical and chemical laws. Therefore, they are useful for modeling complex processes, such as the free radical polymerization of methyl methacrylate achieved in a batch bulk process. The goal is to generate accurate predictions of monomer conversion, numerical average molecular weight and gravimetrical average molecular weight. This process is associated with non-linear gel and glass effects. For this purpose, an adaptive sampling technique is presented, which can select more samples around the regions where the values have a higher variation. Several machine learning methods are used for the modeling and their performance is compared: support vector machines, k-nearest neighbor, k-nearest neighbor and random forest, as well as an original algorithm, large margin nearest neighbor regression. The suggested method provides very good results compared to the other well-known regression algorithms.

Keywords: batch bulk methyl methacrylate polymerization, adaptive sampling, machine learning, large margin nearest neighbor regression

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Authors: Hassan Taimoor, Piotr Krajewski, Piotr Gabrielzcak

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Being responsible for the largest source of energy-related emissions, the transportation sector is driven by more than half of global oil demand and total energy consumption, making it a crucial factor in tackling climate change and environmental degradation. The present study empirically tests the effectives of the energy-related tax (TXEN) in curbing transport-related carbon emissions (CO2TRANSP) in Organization for Economic Cooperation and Development (OECD) economies over the period of 1990-2020. Moreover, Green Finance (GF), Technology (TECH), and Gross domestic product (GDP) have also been added as explanatory factors which might affect CO2TRANSP emissions. The study employs the Method of Moment Quantile Regression (MMQR), an advance econometric technique to observe the variations along each quantile. Based on the results of the preliminary test, we confirm the presence of cross-sectional dependence and slope heterogeneity. Whereas the result of the panel unit root test report mixed order of variables’ integration. The findings reveal that rise in income level activates CO2TRANSP, confirming the first stage of Environmental Kuznet Hypothesis. Surprisingly, the present TXEN policies of OECD member states are not mature enough to tackle the CO2TRANSP emissions. However, the findings confirm that GF and TECH are solely responsible for the reduction in the CO2TRANSP. The outcomes of Bootstrap Quantile Regression (BSQR) further validate and support the earlier findings of MMQR. Based on the findings of this study, it is revealed that the current TXEN policies are too moderate, and an incremental and progressive rise in TXEN may help in a transition toward a cleaner and sustainable transportation sector in the study region.

Keywords: transport-related CO2 emissions, energy-related tax, green finance, technological development, oecd member states

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Authors: Xitong Liu, Yutong Huang, Shu-Ching Yang

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The phenomena of hypergamous and hypogamous marriages have become popular due to the imbalanced sex ratio caused by Chinese social preference for sons. Our research explores the spillover effect of husbands' lifestyles on their wives' marital satisfaction in China. Both personal and spouse lifestyle elements are utilized to develop regression models to study husbands' spillover effects on women's marital satisfaction. With data from China Family Panel Study and Stata for analysis, we tested our hypothesis that both smoking and substance use by a spouse will negatively impact women's marital satisfaction. Our empirical findings suggest that substance use has negative implications on marriage satisfaction. In particular, husbands' substance use is more critical to wives' marriage satisfaction than wives' behaviours. Conversely, another behavior indicating bad habits, the number of times the spouse drank alcohol, had no significant effect on the wife's marital satisfaction. We concluded our investigation and provided future implications for scholars in the family economics field.

Keywords: Asian/Pacific Islander families, family economics, housework/division of labor, spillover

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Authors: G. C. Surya Bahadur, Ranjana Kothari

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The paper attempts to analyze linkages between corporate governance and firm performance in India. The study employs a panel data of 50 Nifty companies from 2008 to 2012. Using LSDV panel data model and 2SLS model the study reveals that that good corporate governance practices adopted by companies is positively related with financial performance. Board independence, number of board committees and executive compensation are found to have positive relationship while ownership by promoters and financial leverage have negative relationship with performance. There is existence of bi-directional relationship between corporate governance and financial performance. Companies with sound financial performance are more likely to conform to corporate governance norms and standards and implement sound corporate governance system. The findings indicate that companies can enhance business performance and sustainability by embracing sound corporate governance practices.

Keywords: board structure, corporate governance, executive compensation, ownership structure

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Authors: E. Fredrick Rice

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Over the past three decades, a substantial body of academic literature has asserted that the pressure to maintain household income can negatively affect the personal well-being of breadwinners. Given that scholars have failed to thoroughly explore this phenomenon with breadwinners who are also business owners, theory has been underdeveloped in the entrepreneurial context. To identify the most appropriate theories to apply to entrepreneurs, the current paper utilized two approaches. First, a comprehensive bibliographic analysis was conducted focusing on works at the intersection of breadwinner status and well-being. Co-authorship and journal citation patterns highlighted relative resource theory as a boundary spanning approach with promising applications in the entrepreneurial space. To build upon this theory, regression analysis was performed using data from the Panel Study of Entrepreneurial Dynamics (PSED). Empirical results showed evidence for the effects of breadwinner status and household income on entrepreneurial well-being. Further, the findings suggest that it is not merely income or job status that predicts well-being, but one’s relative financial contribution compared to that of one’s non-breadwinning organizationally employed partner. This paper offers insight into how breadwinner status can be studied in relation to the entrepreneurial personality.

Keywords: breadwinner, entrepreneurship, household income, well-being.

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Authors: Mohammad Jamalabadi, Noemi Zabari, Lukasz Bratasz

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Panel paintings -complex multi-layer structures consisting of wood support and a paint layer composed of a preparatory layer of gesso, paints, and varnishes- are among the category of cultural objects most vulnerable to relative humidity fluctuations and frequently found in museum collections. The current environmental specifications in museums have been derived using the criterion of crack initiation in an undamaged, usually new gesso layer laid on wood. In reality, historical paintings exhibit complex crack patterns called craquelures. The present paper analyses the structural response of a paint layer with a virtual network of rectangular cracks under environmental loadings using a three-dimensional model of a panel painting. Two modes of loading are considered -one induced by one-dimensional moisture response of wood support, termed the tangential loading, and the other isotropic induced by drying shrinkage of the gesso layer. The superposition of the two modes is also analysed. The modelling showed that minimum distances between cracks parallel to the wood grain depended on the gesso stiffness under the tangential loading. In spite of a non-zero Poisson’s ratio, gesso cracks perpendicular to the wood grain could not be generated by the moisture response of wood support. The isotropic drying shrinkage of gesso produced cracks that were almost evenly spaced in both directions. The modelling results were cross-checked with crack patterns obtained on a mock-up of a panel painting exposed to a number of extreme environmental variations in an environmental chamber.

Keywords: fracture saturation, surface cracking, paintings on wood, wood panels

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Authors: Anand K. Vinu, Vaishnav Vimal, Sasi Gopalan

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All spacecraft components have a range of allowable temperatures that must be maintained to meet survival and operational requirements during all mission phases. Due to heat absorption, transfer, and emission on one side, the satellite surface presents an asymmetric temperature distribution and causes a change in momentum, which can manifest in spinning and non-spinning satellites in different manners. This problem can cause orbital decays in satellites which, if not corrected, will interfere with its primary objective. The thermal analysis of any satellite requires data from the power budget for each of the components used. This is because each of the components has different power requirements, and they are used at specific times in an orbit. There are three different cases that are run, one is the worst operational hot case, the other one is the worst non-operational cold case, and finally, the operational cold case. Sunlight is a major source of heating that takes place on the satellite. The way in which it affects the spacecraft depends on the distance from the Sun. Any part of a spacecraft or satellite facing the Sun will absorb heat (a net gain), and any facing away will radiate heat (a net loss). We can use the state-of-the-art foldable hybrid insulator/radiator panel. When the panels are opened, that particular side acts as a radiator for dissipating the heat. Here the insulator, in our case, the aerogel, is sandwiched with solar cells and radiator fins (solar cells outside and radiator fins inside). Each insulated side panel can be opened and closed using actuators depending on the telemetry data of the CubeSat. The opening and closing of the panels are dependent on the special code designed for this particular application, where the computer calculates where the Sun is relative to the satellites. According to the data obtained from the sensors, the computer decides which panel to open and by how many degrees. For example, if the panels open 180 degrees, the solar panels will directly face the Sun, in turn increasing the current generator of that particular panel. One example is when one of the corners of the CubeSat is facing or if more than one side is having a considerable amount of sun rays incident on it. Then the code will analyze the optimum opening angle for each panel and adjust accordingly. Another means of cooling is the passive way of cooling. It is the most suitable system for a CubeSat because of its limited power budget constraints, low mass requirements, and less complex design. Other than this fact, it also has other advantages in terms of reliability and cost. One of the passive means is to make the whole chase act as a heat sink. For this, we can make the entire chase out of heat pipes and connect the heat source to this chase with a thermal strap that transfers the heat to the chassis.

Keywords: passive cooling, CubeSat, efficiency, satellite, stationary satellite

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Authors: Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević

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This study considers the selection of the most suitable in silico molecular descriptors that could be used for s-triazine pesticides characterization. Suitable descriptors among topological, geometrical and physicochemical are used for quantitative structure-retention relationships (QSRR) model establishment. Established models were obtained using linear regression (LR) and multiple linear regression (MLR) analysis. In this paper, MLR models were established avoiding multicollinearity among the selected molecular descriptors. Statistical quality of established models was evaluated by standard and cross-validation statistical parameters. For detection of similarity or dissimilarity among investigated s-triazine pesticides and their classification, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used and gave similar grouping. This study is financially supported by COST action TD1305.

Keywords: chemometrics, classification analysis, molecular descriptors, pesticides, regression analysis

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Authors: Jelvin Tom Sebastian, Vinod Yeldho Baby

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In space, electronic devices are constantly attacked with radiation, which causes certain parts to fail or behave in unpredictable ways. To advance the thermal controllability for microsatellites, we need a new approach and thermal control system that is smaller than that on conventional satellites and that demand no electric power. Heat exchange inside the microsatellites is not that easy as conventional satellites due to the smaller size. With slight mass gain and no electric power, accommodating heat using phase change materials (PCMs) is a strong candidate for solving micro satellites' thermal difficulty. In other words, PCMs can absorb or produce heat in the form of latent heat, changing their phase and minimalizing the temperature fluctuation around the phase change point. The main restriction for these systems is thermal conductivity weakness of common PCMs. As PCM is having low thermal conductivity, it increases the melting and solidification time, which is not suitable for specific application like electronic cooling. In order to increase the thermal conductivity nanoparticles are introduced. Adding the nanoparticles in base PCM increases the thermal conductivity. Increase in weight concentration increases the thermal conductivity. This paper numerically investigates the thermal energy storage panel with nanoparticle enhanced phase change material. Silver nanostructure have increased the thermal properties of the base PCM, eicosane. Different weight concentration (1, 2, 3.5, 5, 6.5, 8, 10%) of silver enhanced phase change material was considered. Both steady state and transient analysis was performed to compare the characteristics of nanoparticle enhanced phase material at different heat loads. Results showed that in steady state, the temperature near the front panel reduced and temperature on NePCM panel increased as the weight concentration increased. With the increase in thermal conductivity more heat was absorbed into the NePCM panel. In transient analysis, it was found that the effect of nanoparticle concentration on maximum temperature of the system was reduced as the melting point of the material reduced with increase in weight concentration. But for the heat load of maximum 20W, the model with NePCM did not attain the melting point temperature. Therefore it showed that the model with NePCM is capable of holding more heat load. In order to study the heat load capacity double the load is given, maximum of 40W was given as first half of the cycle and the other is given constant OW. Higher temperature was obtained comparing the other heat load. The panel maintained a constant temperature for a long duration according to the NePCM melting point. In both the analysis, the uniformity of temperature of the TESP was shown. Using Ag-NePCM it allows maintaining a constant peak temperature near the melting point. Therefore, by altering the weight concentration of the Ag-NePCM it is possible to create an optimum operating temperature required for the effective working of the electronics components.

Keywords: carbon-fiber-reinforced polymer, micro/nano-satellite, nanoparticle phase change material, thermal energy storage

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Authors: N. H. Hamid, N. M. Mohamed, S. A. Anuar

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Precast residential houses are normally constructed in Malaysia using precast shear-key wall panel and precast wall panel are designed using BS8110 where there is no provision for earthquake. However, the safety of this house under moderate and strong earthquake is still questionable. Consequently, the full-scale of residential house are designed, constructed, tested and analyzed under in-plane lateral cyclic loading. Hysteresis loops are plotted based on the experimental work and compared with modeling of hysteresis loops using HYSTERES in RUAUMOKO 2D program. Modified Takeda hysteresis model is chosen to behave a similar pattern with experimental work. This program will display the earthquake excitations, spectral displacements, pseudo spectral acceleration, and deformation shape of the structure. It can be concluded that this building is suffering severe cracks and damage under moderate and severe earthquake.

Keywords: precast shear-key, hysteresis loops, spectral displacements, deformation shape

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Authors: Apollinaire Barme, Simon Tamayo, Arthur Gaudron

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This paper presents a statistical approach to identify explanatory variables linearly related to e-commerce sales. The proposed methodology allows specifying a regression model in order to quantify the relevance between openly available data (economic and demographic) and national e-commerce sales. The proposed methodology consists in collecting data, preselecting input variables, performing regressions for choosing variables and models, testing and validating. The usefulness of the proposed approach is twofold: on the one hand, it allows identifying the variables that influence e- commerce sales with an accessible approach. And on the other hand, it can be used to model future sales from the input variables. Results show that e-commerce is linearly dependent on 11 economic and demographic indicators.

Keywords: e-commerce, statistical modeling, regression, empirical research

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Authors: Usman Yakubu, Muktar Haruna

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The paper examines the impact of the audit committee on the earning quality of the listed consumer goods sector in Nigeria. The study used data collected from annual reports and accounts of the 13 sampled companies for the periods 2007 to 2018. Data were analyzed by means of descriptive statistics to provide summary statistics for the variables; also, correlation analysis was carried out using the Pearson correlation technique for the correlation between the dependent and independent variables. Regression was employed using the Generalized Least Square technique since the data has both time series and cross sectional attributes (panel data). It was found out that the audit committee had a positive and significant influence on the earning quality in the listed consumer goods companies in Nigeria. Thus, the study recommends that competency and personal integrity should be the worthwhile attributes to be considered while constituting the committee; this could enhance the quality of accounting information. In addition to that majority of the committee members should be independent directors in order to allow a high level of independency to be exercised.

Keywords: earning quality, corporate governance, audit committee, financial reporting

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Authors: Andreea Halunga, Chris D. Orme, Takashi Yamagata

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This paper proposes a heteroskedasticity-robust Breusch-Pagan test of the null hypothesis of zero cross-section (or contemporaneous) correlation in linear panel-data models, without necessarily assuming independence of the cross-sections. The procedure allows for either fixed, strictly exogenous and/or lagged dependent regressor variables, as well as quite general forms of both non-normality and heteroskedasticity in the error distribution. The asymptotic validity of the test procedure is predicated on the number of time series observations, T, being large relative to the number of cross-section units, N, in that: (i) either N is fixed as T→∞; or, (ii) N²/T→0, as both T and N diverge, jointly, to infinity. Given this, it is not expected that asymptotic theory would provide an adequate guide to finite sample performance when T/N is "small". Because of this, we also propose and establish asymptotic validity of, a number of wild bootstrap schemes designed to provide improved inference when T/N is small. Across a variety of experimental designs, a Monte Carlo study suggests that the predictions from asymptotic theory do, in fact, provide a good guide to the finite sample behaviour of the test when T is large relative to N. However, when T and N are of similar orders of magnitude, discrepancies between the nominal and empirical significance levels occur as predicted by the first-order asymptotic analysis. On the other hand, for all the experimental designs, the proposed wild bootstrap approximations do improve agreement between nominal and empirical significance levels, when T/N is small, with a recursive-design wild bootstrap scheme performing best, in general, and providing quite close agreement between the nominal and empirical significance levels of the test even when T and N are of similar size. Moreover, in comparison with the wild bootstrap "version" of the original Breusch-Pagan test our experiments indicate that the corresponding version of the heteroskedasticity-robust Breusch-Pagan test appears reliable. As an illustration, the proposed tests are applied to a dynamic growth model for a panel of 20 OECD countries.

Keywords: cross-section correlation, time-series heteroskedasticity, dynamic panel data, heteroskedasticity robust Breusch-Pagan test

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Authors: Ebrahim Mansoori, Datin Joriah Muhammad

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Recent studies in finance have focused on the effect of external variables on working capital management. This study investigates the effect of corruption indexes on firms' working capital management. A large data set that covers data from 2005 to 2013 from five ASEAN countries, namely, Malaysia, Indonesia, Singapore, Thailand, and the Philippines, was selected to investigate how the level of corruption in these countries affect working capital management. The results of panel data analysis include fixed effect estimations showed that a high level of countries' corruption indexes encourages managers to shorten the CCC length. Meanwhile, the managers reduce the level of investment in cash and cash equivalents when the levels of corruption indexes increase. Therefore, increasing the level of countries' corruption indexes encourages managers to select conservative working capital strategies by reducing the level of NLB.

Keywords: ASEAN, corruption indexes, panel data analysis, working capital management

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Authors: Nomakhosi Tshuma, Carley Chetty

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This study employed panel regression analysis to investigate the financial performance determinants of MTN and Vodacom’s rest of Africa businesses between 2012 to 2020. It used net profit margin, return on assets (ROA), and return on equity (ROE) as financial performance proxies. Financial performance determinants investigated were asset size, debt ratio, liquidity, number of subscribers, and exchange rate. Data relating to exchange rates were obtained from the World Bank website, while financial data and subscriber information were obtained from the companies’ audited financial statements. The study found statistically significant negative relationships between debt and both ROA and net profit, exchange rate and both ROA and net profit, and subscribers and ROE. It also found significant positive relationships between ROE and both asset size and exchange rate. The study recommends strategic options that optimise on the above findings, and these include infrastructure sharing to reduce infrastructure costs and the minimisation of foreign-denominated debt.

Keywords: financial performance, determinants of financial performance, business in Africa, telecommunications industry

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Authors: Anwar Hussain, Ahmed Imran, Farida Faisal, Fatima Sultana

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The present research evaluates a comparative assessment of dividend policy and share price across the South Asian countries including Pakistan, India and Sri-Lanka over the period of 2010 to 2014. Academic writers found that dividend policy and share price relationship is not same in south Asian market due to different reasons. Moreover, Panel Models used = for the evaluation of current study. In addition, Redundant fixed effect Likelihood and Hausman test used for determine of Common, Fixed and Random effect model. Therefore Indian market dividend policies play a fundamental role and significant impact on Market Share Prices. Although, present research found that different as compared to previous study that dividend policy have no impact on share price in Sri-Lanka and Pakistan.

Keywords: dividend policy, share price, South Asian countries, panel data analysis, theories and parameters of dividend

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Authors: Dileep Kumar Gupta, Rajendra Prasad, Pradeep Kumar, Varun Narayan Mishra, Ajeet Kumar Vishwakarma, Prashant K. Srivastava

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An approach was evaluated for the retrieval of soil moisture of bare soil surface using bistatic scatterometer data in the angular range of 200 to 700 at VV- and HH- polarization. The microwave data was acquired by specially designed X-band (10 GHz) bistatic scatterometer. The linear regression analysis was done between scattering coefficients and soil moisture content to select the suitable incidence angle for retrieval of soil moisture content. The 250 incidence angle was found more suitable. The support vector regression analysis was used to approximate the function described by the input-output relationship between the scattering coefficient and corresponding measured values of the soil moisture content. The performance of support vector regression algorithm was evaluated by comparing the observed and the estimated soil moisture content by statistical performance indices %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE). The values of %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were found 2.9451, 1.0986, and 0.9214, respectively at HH-polarization. At VV- polarization, the values of %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were found 3.6186, 0.9373, and 0.9428, respectively.

Keywords: bistatic scatterometer, soil moisture, support vector regression, RMSE, %Bias, NSE

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Authors: My Linh Hoang, Van Dung Hoang

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Environmental, Social, and Governance (ESG) factors have become a focus for companies globally, as businesses are now focusing on long-term sustainable goals rather than only operating for the goals of profit maximization. According to recent research, in several countries, companies have shown positive results in their financial performance by improving their ESG performance. The construction industry is one of the most crucial components of social and economic development; as a result, considerations for ESG factors are becoming more and more essential for companies in this sector. In Vietnam, the construction industry has been growing rapidly in recent years; however, it has yet to be discussed and studied extensively in Vietnam how ESG factors create impacts on corporate financial performance in general and construction corporations’ financial performance in particular. This research aims to examine the relationship between ESG factors and financial indicators in construction companies from 2011 to 2021 through panel data analysis of 75 listed construction companies in Vietnam and to provide insights into how these companies can better integrate ESG considerations into their operations to enhance their financial performance. The data was analyzed through 3 main methods: descriptive statistics, correlation coefficient analysis applied to all dependent, explanatory and control variables, and panel data analysis method. In panel data analysis, the study uses the fixed effects model (FEM) and random effects model (REM). The Hausman test will be used to select which model is suitable to be used. The findings indicate that maintaining a strong commitment to ESG principles can have a positive impact on financial performance. Finally, FGLS estimation will be performed when the problem of autocorrelation and variable variance appears in the model. This is significant for all parties involved, including investors, company managers, decision-makers, and industry regulators.

Keywords: ESG, financial performance, construction company, Vietnam

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Authors: Ekkehard Fehling, Paul Capewell

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In recent years, the importance of masonry glued by polyurethane adhesive has increased. In 2021, the Institute of Structural Engineering of the University of Kassel was commissioned to carry out quasi-static in-plane shear tests on prefabricated brick masonry panel systems with 2K PUR adhesive in order to investigate the load-bearing behavior during earthquakes. In addition to the usual measurement of deformations using displacement transducers, all tests were documented using an optical measuring system (“GOM”), which was used to determine the surface strains and deformations of the test walls. To compare the results with conventional mortar walls, additional reference tests were carried out on test specimens with thin-bed mortar joints. This article summarizes the results of the test program and provides a comparison between the load-bearing behavior of masonry bonded with polyurethane adhesive and thin bed mortar in order to enable realistic non-linear modeling.

Keywords: masonry, shear tests, in-plane, polyurethane adhesive

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Authors: Mina Adel Shokry Fahim, Jūratė Sužiedelytė Visockienė

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With the growing concern over air pollution (AP), it is clear that this has gained more prominence than ever before. The level of consciousness has increased and a sense of knowledge now has to be forwarded as a duty by those enlightened enough to disseminate it to others. This realisation often comes after an understanding of how poor air quality indices (AQI) damage human health. The study focuses on assessing air pollution prediction models specifically for Lithuania, addressing a substantial need for empirical research within the region. Concentrating on Vilnius, it specifically examines particulate matter concentrations 10 micrometers or less in diameter (PM10). Utilizing Gaussian Process Regression (GPR) and Regression Tree Ensemble, and Regression Tree methodologies, predictive forecasting models are validated and tested using hourly data from January 2020 to December 2022. The study explores the classification of AP data into anthropogenic and natural sources, the impact of AP on human health, and its connection to cardiovascular diseases. The study revealed varying levels of accuracy among the models, with GPR achieving the highest accuracy, indicated by an RMSE of 4.14 in validation and 3.89 in testing.

Keywords: air pollution, anthropogenic and natural sources, machine learning, Gaussian process regression, tree ensemble, forecasting models, particulate matter

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Authors: Jonathan Iworiso

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Forecasting the equity premium out-of-sample is a major concern to researchers in finance and emerging markets. The quest for a superior model that can forecast the equity premium with significant economic gains has resulted in several controversies on the choice of variables and suitable techniques among scholars. This research focuses mainly on the application of Regression Training (RT) techniques to forecast monthly equity premium out-of-sample recursively with an expanding window method. A broad category of sophisticated regression models involving model complexity was employed. The RT models include Ridge, Forward-Backward (FOBA) Ridge, Least Absolute Shrinkage and Selection Operator (LASSO), Relaxed LASSO, Elastic Net, and Least Angle Regression were trained and used to forecast the equity premium out-of-sample. In this study, the empirical investigation of the RT models demonstrates significant evidence of equity premium predictability both statistically and economically relative to the benchmark historical average, delivering significant utility gains. They seek to provide meaningful economic information on mean-variance portfolio investment for investors who are timing the market to earn future gains at minimal risk. Thus, the forecasting models appeared to guarantee an investor in a market setting who optimally reallocates a monthly portfolio between equities and risk-free treasury bills using equity premium forecasts at minimal risk.

Keywords: regression training, out-of-sample forecasts, expanding window, statistical predictability, economic significance, utility gains

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Authors: Leo Carlo B. Rondina

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Self-image is an important factor to improve the self-esteem of the personnel. The purpose of the study is to determine the self-image of the police. The respondents were the 503 policemen assigned in different Police Station in Davao City, and they were chosen with the used of random sampling. With the used of Exploratory Factor Analysis (EFA), latent construct variables of police image were identified as follows; professionalism, obedience, morality and justice and fairness. Further, ordinal regression indicates statistical characteristics on ages 21-40 which means the age of the respondent statistically improves self-image.

Keywords: police image, exploratory factor analysis, ordinal regression, Galatea effect

Procedia PDF Downloads 253

Authors: Jason Ting Jing Cheng, Lee Foo Wei, Yew Ming Kun, Mo Kim Hung, Yip Chun Chieh

Abstract:

This research delves into the structural characteristics of distinct construction material, rubberized lightweight foam concrete (RLFC) wall panels, which have been developed as a sustainable alternative for the construction industry. These panels are engineered with a RLFC core, possessing a density of 1150 kg/m3, which is specifically formulated to bear structural loads. The core is enveloped with high-strength fiber cement boards, selected for their superior load-bearing capabilities, and enhanced flexural strength when compared to conventional concrete. A thin bed adhesive, known as TPS, is employed to create a robust bond between the RLFC core and the fiber cement cladding. This study underscores the potential of RLFC wall panels as a viable and eco-friendly option for modern building construction, offering a combination of structural efficiency and environmental benefits.

Keywords: structural performance, rubberized concrete wall panel, fiber cement board, insulation performance

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Authors: Y. H. Mugahed Amran, Raizal S. M. Rashid, Farzad Hejazi, Nor Azizi Safiee, A. A. Abang Ali

Abstract:

Experimental and analytical studies were accomplished to examine the structural behavior of precast foamed concrete sandwich panel (PFCSP) under vertical in-plane shear load. PFCSP full-scale specimens with total number of six were developed with varying heights to study an important parameter slenderness ratio (H/t). The production technique of PFCSP and the procedure of test setup were described. The results obtained from the experimental tests were analysed in the context of in-plane shear strength capacity, load-deflection profile, load-strain relationship, slenderness ratio, shear cracking patterns and mode of failure. Analytical study of finite element analysis was implemented and the theoretical calculations of the ultimate in-plane shear strengths using the adopted ACI318 equation for reinforced concrete wall were determined aimed at predicting the in-plane shear strength of PFCSP. The decrease in slenderness ratio from 24 to 14 showed an increase of 26.51% and 21.91% on the ultimate in-plane shear strength capacity as obtained experimentally and in FEA models, respectively. The experimental test results, FEA models data and theoretical calculation values were compared and provided a significant agreement with high degree of accuracy. Therefore, on the basis of the results obtained, PFCSP wall has the potential use as an alternative to the conventional load-bearing wall system.

Keywords: deflection curves, foamed concrete (FC), load-strain relationships, precast foamed concrete sandwich panel (PFCSP), slenderness ratio, vertical in-plane shear strength capacity

Procedia PDF Downloads 182

Authors: Damien Gondre, Hatem Ben Maad, Abdelkrim Trabelsi, Frédéric Kuznik, Joseph Virgone

Abstract:

The use of a radiant cooling solution would enable to lower cooling needs which is of great interest when the demand is initially high (hot climate). But, radiant systems are not naturally compatibles with humid climates since a low-temperature surface leads to condensation risks as soon as the surface temperature is close to or lower than the dew point temperature. A radiant cooling system combined to a dehumidification system would enable to remove humidity for the space, thereby lowering the dew point temperature. The humidity removal needs to be especially effective near the cooled surface. This requirement could be fulfilled by a system using a single desiccant fluid for the removal of both excessive heat and moisture. This task aims at providing an estimation of the specification requirements of such system in terms of cooling power and dehumidification rate required to fulfill comfort issues and to prevent any condensation risk on the cool panel surface. The present paper develops a preliminary study on the specification requirements, performances and behavior of a combined dehumidifier/cooling ceiling panel for different operating conditions. This study has been carried using the TRNSYS software which allows nodal calculations of thermal systems. It consists of the dynamic modeling of heat and vapor balances of a 5m x 3m x 2.7m office space. In a first design estimation, this room is equipped with an ideal heating, cooling, humidification and dehumidification system so that the room temperature is always maintained in between 21^◦C and 25^◦C with a relative humidity in between 40% and 60%. The room is also equipped with a ventilation system that includes a heat recovery heat exchanger and another heat exchanger connected to a heat sink. Main results show that the system should be designed to meet a cooling power of 42W.m⁻² and a desiccant rate of 45 g_H2O.h⁻¹. In a second time, a parametric study of comfort issues and system performances has been achieved on a more realistic system (that includes a chilled ceiling) under different operating conditions. It enables an estimation of an acceptable range of operating conditions. This preliminary study is intended to provide useful information for the system design.

Keywords: dehumidification, nodal calculation, radiant cooling panel, system sizing

Procedia PDF Downloads 148

Authors: Mehdi Moeinaddini, Zohreh Asadi-Shekari, Muhammad Zaly Shah, Amran Hamzah

Abstract:

Currently, planners try to have more green travel options to decrease economic, social and environmental problems. Therefore, this study tries to find significant urban travel factors to be used to increase the usage of alternative urban travel modes. This paper attempts to identify the relationship between prominent urban mobility indicators and daily trips by public transport in 30 cities from various parts of the world. Different travel modes, infrastructures and cost indicators were evaluated in this research as mobility indicators. The results of multi-linear regression analysis indicate that there is a significant relationship between mobility indicators and the daily usage of public transport.

Keywords: green travel modes, urban travel indicators, daily trips by public transport, multi-linear regression analysis

Procedia PDF Downloads 522