Search results for: cointegration approach in panel data

Authors: Walid Cherif

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Data mining has, over recent years, seen big advances because of the spread of internet, which generates everyday a tremendous volume of data, and also the immense advances in technologies which facilitate the analysis of these data. In particular, classification techniques are a subdomain of Data Mining which determines in which group each data instance is related within a given dataset. It is used to classify data into different classes according to desired criteria. Generally, a classification technique is either statistical or machine learning. Each type of these techniques has its own limits. Nowadays, current data are becoming increasingly heterogeneous; consequently, current classification techniques are encountering many difficulties. This paper defines new measure functions to quantify the resemblance between instances and then combines them in a new approach which is different from actual algorithms by its reliability computations. Results of the proposed approach exceeded most common classification techniques with an f-measure exceeding 97% on the IRIS Dataset.

Keywords: data mining, knowledge discovery, machine learning, similarity measurement, supervised classification

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Authors: Zahid Ahmad, Samia Yousaf

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The main purpose of this study is to evaluate and assess the financial position, operating performance, and recent outlook of the companies. This study investigates the impact of capital structure, dividend policy and sustainability on the value of firms of textile spinning sector of Pakistan which is listed on Pakistan stock exchange. The panel data technique has been applied to this group of textile sector which is textile spinning. This study covers the last ten years of time period. All the data related to the variables have been collected from the annual reports and financial statements of the textile sector firms. There are differently related determinants to measure the capital structure which are fixed assets turnover ratio, debt ratio, equity ratio, debt to equity ratio, assets tangibility, and shareholder’s equity. Dividend policy is being measured by two determinants which are earning per share (EPS) and dividend payout ratio. Sustainability is being measured by three suitable factors which are sales growth, gross profit margin ratio and firm size. These are three independent variables and their determinants of this study. Value of firm is measured through the return on asset (ROA). Capital structure is at the top of the list among all the three variables. According to the results of this research work, somewhere all the three variables generates positive and significant effect on the firm’s performance and its growth.

Keywords: capital structure, dividend policy, panel data, sustainability

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Authors: Nikat Parveen, M. Ananthi

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Big data is one of the emerging technology, which collects the data from various sensors and those data will be used in many fields. Data retrieval is one of the major issue where there is a need to extract the exact data as per the need. In this paper, large amount of data set is processed by using the feature selection. Feature selection helps to choose the data which are actually needed to process and execute the task. The key value is the one which helps to point out exact data available in the storage space. Here the available data is streamed and R-Center is proposed to achieve this task.

Keywords: big data, key value, feature selection, retrieval, performance

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Authors: Ouzayr Rabhi, Ibtissam Arrassen

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To provide a complete analysis of the organization and to help decision-making, leaders need to have relevant data; Data Warehouses (DW) are designed to meet such needs. However, designing DW is not trivial and there is no formal method to derive a multidimensional schema from heterogeneous databases. In this article, we present a Model-Driven based approach concerning the design of data warehouses. We describe a multidimensional meta-model and also specify a set of transformations starting from a Unified Modeling Language (UML) metamodel. In this approach, the UML metamodel and the multidimensional one are both considered as a platform-independent model (PIM). The first meta-model is mapped into the second one through transformation rules carried out by the Query View Transformation (QVT) language. This proposal is validated through the application of our approach to generating a multidimensional schema of a Balanced Scorecard (BSC) DW. We are interested in the BSC perspectives, which are highly linked to the vision and the strategies of an organization.

Keywords: data warehouse, meta-model, model-driven architecture, transformation, UML

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Authors: Kay Fielden, Eelin Tan, Lan Nguyen

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In this research project, data was gathered at a Covid 19 Conference held in June 2021 from industry leaders who discussed the impact of the global pandemic on the status of the New Zealand hospitality industry. Panel discussions on financials, human resources, health and safety, and recovery were conducted. The themes explored for the finance panel were customer demographics, hospitality sectors, financial practices, government impact, and cost of compliance. The aim was to see how the hospitality industry has responded to the global pandemic and the steps that have been taken for the industry to recover or sustain their business. The main research question for this qualitative study is: What are the factors that have impacted on finance for the hospitality industry in New Zealand due to Covid 19? For financials, literature has been gathered to study global effects, and this is being compared with the data gathered from the discussion panel through the lens of resilience theory. Resilience theory applied to the hospitality industry suggests that the challenges imposed by Covid 19 have been the catalyst for government initiatives, technical innovation, engaging local communities, and boosting confidence. Transformation arising from these ground shifts have been a move towards sustainability, wellbeing, more awareness of climate change, and community engagement. Initial findings suggest that there has been a shift in customer base that has prompted regional accommodation providers to realign offers and to become more flexible to attract and maintain this realigned customer base. Dynamic pricing structures have been required to meet changing customer demographics. Flexible staffing arrangements include sharing staff between different accommodation providers, owners with multiple properties adopting different staffing arrangements, maintaining a good working relationship with the bank, and conserving cash. Uncertain times necessitate changing revenue strategies to cope with external factors. Financial support offered by the government has cushioned the financial downturn for many in the hospitality industry, and managed isolation and quarantine (MIQ) arrangements have offered immediate financial relief for those hotels involved. However, there is concern over the long-term effects. Compliance with mandated health and safety requirements has meant that the hospitality industry has streamlined its approach to meeting those requirements and has invested in customer relations to keep paying customers informed of the health measures in place. Initial findings from this study lie within the resilience theory framework and are consistent with findings from the literature.

Keywords: global pandemic, hospitality industry, new Zealand, resilience

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Authors: M. Saeedi, R. Wuchner, K.-U. Bletzinger

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In order to study the aerodynamic performance of a semi-flexible membrane wing, Fluid-Structure Interaction simulations have been performed. The fluid problem has been modeled using two different approaches which are the numerical solution of the Navier-Stokes equations and the vortex panel method. Nonlinear analysis of the structural problem is performed using the Finite Element Method. Comparison between the two fluid solvers has been made. Aerodynamic performance of the wing is discussed regarding its lift and drag coefficients and they are compared with those of the equivalent rigid wing.

Keywords: CFD, FSI, Membrane wing, Vortex panel method

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Authors: Innocent Pangapanga-Phiri, Eric Dada Mungatana

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This study estimates the effect of climate-induced rural-urban migrants (RUM) on maize productivity. It uses panel data gathered by the National Statistics Office and the World Bank to understand the effect of RUM on the technical efficiency of maize production in rural Malawi. The study runs the two-stage Tobit regression to isolate the real effect of rural-urban migration on the technical efficiency of maize production. The results show that RUM significantly reduces the technical efficiency of maize production. However, the interaction of RUM and climate-smart agriculture has a positive and significant influence on the technical efficiency of maize production, suggesting the need for re-investing migrants’ remittances in agricultural activities.

Keywords: climate-smart agriculture, farm productivity, rural-urban migration, panel stochastic frontier models, two-stage Tobit regression

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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: Abdoulahad Allamine

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The objective of this study is to assess the impact of climate variability on agriculture and food security in 43 countries of sub-Saharan Africa. We use for this purpose the data from BADC bases, UNCTAD, and WDI FAOSTAT to estimate a VAR model on panel data. The sample is divided into three (03) agro-climatic zones, more explicitly the equatorial zone, the Sahel region and the semi-arid zone. This allows to highlight the differential impacts sustained by countries and appropriate responses to each group of countries. The results show that the sharp fluctuations in the volume of rainfall negatively affect agriculture and food security of countries in the equatorial zone, with heavy rainfall and high temperatures in the Sahel region. However, countries with low temperatures and low rainfall are the least affected. The hedging policies against the risks of climate variability must be more active in the first two groups of countries. On this basis and in general, we recommend integration of agricultural policies between countries is done to reduce the effects of climate variability on agriculture and food security. It would be logical to encourage regional and international closer collaboration on the development and dissemination of improved varieties, ecological intensification, and management of biotic and abiotic stresses facing these climate variability to sustainably increase food production. Small farmers also need training in agricultural risk hedging techniques related to climate variations; this requires an increase in state budgets allocated to agriculture.

Keywords: agro-climatic zones, climate variability, food security, Sub-Saharan Africa, VAR on panel data

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Authors: Yasser A. Khalifa, Michael J. Tait, A. M. Asce, Wael W. El-Dakhakhni, M. Asce

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The quasi-static resistance functions for orthogonal corrugated core sandwich panels were determined experimentally. According to the American and Canadian codes for blast resistant designs of buildings UFC 3-340-02, ASCE/SEI 59-11, and CSA/ S850-12 the dynamic behavior is related to the static behavior under uniform loading. The target was to design a lightweight, relatively cheap, and quick sandwich panel to be employed as a sacrificial cladding for important buildings. For that an available corrugated cold formed steel sheet profile in North America was used as a core for the sandwich panel, in addition to using a quick, relatively low cost fabrication technique in the construction process. Six orthogonal corrugated core sandwich panels were tested and the influence of core sheet gauge on the behavior of the sandwich panels was explored using two different gauges. Failure modes, yield forces, ultimate forces, and corresponding deformations were determined and discussed.

Keywords: cold formed steel, lightweight structure, sandwich panel, sacrificial cladding, uniform loading

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Authors: Orhun Vural, Oguz Bayat, Rustu Akay, Osman N. Ucan

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This study presents a new parallel approach clustering of GPS data. Evaluation has been made by comparing execution time of various clustering algorithms on GPS data. This paper aims to propose a parallel based on neighborhood K-means algorithm to make it faster. The proposed parallelization approach assumes that each GPS data represents a vehicle and to communicate between vehicles close to each other after vehicles are clustered. This parallelization approach has been examined on different sized continuously changing GPS data and compared with serial K-means algorithm and other serial clustering algorithms. The results demonstrated that proposed parallel K-means algorithm has been shown to work much faster than other clustering algorithms.

Keywords: parallel k-means algorithm, parallel clustering, clustering algorithms, clustering on flowing data

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Authors: Reinhold Kosfeld, Andreas Gohs

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In the reduction of CO₂ emissions, the transition to environmentally friendly transport modes has a high significance. In Germany, the climate protection programme 2030 includes various measures for promoting electromobility. Although electric cars at present hold a market share of just over one percent, its stock more than doubled in the past two years. Special measures like tax incentives and a buyer’s premium have been put in place to promote the shift towards electric cars and boost their diffusion. Knowledge of the future expansion of electric cars is required for planning purposes and adaptation measures. With a view of these objectives, we particularly investigate the effect of spatial spillovers on forecasting performance. For this purpose, time series econometrics and panel econometric models are designed for pure electric cars and hybrid cars for Germany. Regional forecasting models with spatial interactions are consistently estimated by using spatial econometric techniques. Regional data on the stocks of electric cars and their determinants at the district level (NUTS 3 regions) are available from the Federal Motor Transport Authority (Kraftfahrt-Bundesamt) for the period 2017 - 2019. A comparative examination of aggregated regional and national predictions provides quantitative information on accuracy gains by allowing for spatial spillovers in forecasting electric mobility.

Keywords: electric mobility, forecasting market diffusion, regional panel data model, spatial interaction

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Authors: Atia Alam

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Growing liberalisation and intense market competition increase firm’s risk exposure and induce corporations to use derivatives extensively as a risk management instrument, which results in decrease in firm’s risk, and increase in value. Present study contributes towards existing literature by providing an in-depth analysis regarding the effect of extent of derivative usage on firm’s risk and value by using panel data models and seemingly unrelated regression technique. New evidence is established in current literature by dividing the sample data based on firm’s Exchange Rate (ER) and Interest Rate (IR) exposure. Analysis is performed for the effect of extent of derivative usage on firm’s risk and value and its variation with respect to the ER and IR exposure. Sample data consists of 166 Pakistani firms listed on Pakistan stock exchange for the period of 2004-2010. Results show that extensive usage of derivative instruments significantly increases firm value and reduces firm’s risk. Furthermore, comprehensive analysis depicts that Pakistani corporations having higher exchange rate exposure, with respect to foreign sales, and higher interest rate exposure, on the basis of industry adjusted leverage, have higher firm value and lower risk. Findings from seemingly unrelated regression also provide robustness to results obtained through panel data analysis. Study also highlights the role of derivative usage as a risk management instrument in high and low ER and IR risk and helps practitioners in understanding how value increasing effect of extent of derivative usage varies with the intensity of firm’s risk exposure.

Keywords: extent of derivative usage, firm value, risk, Pakistan, non-financial firms

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Authors: Gustavo Funes, Eduardo Peters, Jose Delpiano

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It is widely known that photovoltaic technology has been massively distributed over the last decade despite its low-efficiency ratio. Dust deposition reduces this efficiency even more, lowering the energy production and module lifespan. In this work, we developed an artificial vision algorithm based on CIELAB color space to identify dust over panels in an autonomous way. We performed several experiments photographing three different types of panels, 30W, 340W and 410W. Those panels were soiled artificially with uniform and non-uniform distributed dust. The algorithm proposed uses statistical tools to provide a simulation with a 100% soiled panel and then performs a comparison to get the percentage of dirt in the experimental data set. The simulation uses a seed that is obtained by taking a dust sample from the maximum amount of dust from the dataset. The final result is the dirt percentage and the possible distribution of dust over the panel. Dust deposition is a key factor for plant owners to determine cleaning cycles or identify nonuniform depositions that could lead to module failure and hot spots.

Keywords: dust detection, photovoltaic, artificial vision, soiling

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Authors: Raj C. Aparna

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In India, the mandatory clause on Corporate Social Responsibility (CSR) in Companies Act, 2013 has led to varying responses from the companies. From excessive spending to resistance, the private and the public stakeholders have been considering the law from different perspectives. This paper tends to study the characteristics of CSR spending in India with emphasis on the locations to which the funds are routed. This study examines the effects of CSR fund flow on regional development by considering the growth in Gross State Domestic Product (GSDP), agriculture, education and healthcare using panel data for the 29 States in the country. The results confirm that the CSR funds have been instrumental in improving the quality of teaching and healthcare in the areas around the industrial hubs. However, the study shows that the corporates mostly invest in regions which are easily accessible to them, by their physical presence, irrespective of whether the area is developed or not. Such a skewness is visible in the extensive spending in and around the metropolitan cities, the established centers, in the country to which large chunks of CSR funds are channeled. The results show that there is a variation from what the government had proposed while initiating the CSR law to promote social inclusion and equality in the rural and isolated areas in the country. The implication is that even though societal improvement is the aim of CSR, ease of access to the needy is an essential factor in corporate choices. As poverty and lack of facilities are found in the innermost parts, it is vital to have government policies for their aid as corporate help.

Keywords: corporate social responsibility, geographic spread, panel data analysis, strategic implementation

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Authors: Nikita Valluri, Vatcharaporn Esichaikul

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With the popularity of data-driven decision making on the rise, this study focuses on providing an alternative outlook towards the process of decision-making. Combining quantitative and qualitative methods rooted in the social sciences, an integrated framework is presented with a focus on delivering a much more robust and efficient approach towards the concept of data-driven decision-making with respect to not only Big data but also 'Thick data', a new form of qualitative data. In support of this, an example from the retail sector has been illustrated where the framework is put into action to yield insights and leverage business intelligence. An interpretive approach to analyze findings from both kinds of quantitative and qualitative data has been used to glean insights. Using traditional Point-of-sale data as well as an understanding of customer psychographics and preferences, techniques of data mining along with qualitative methods (such as grounded theory, ethnomethodology, etc.) are applied. This study’s final goal is to establish the framework as a basis for providing a holistic solution encompassing both the Big and Thick aspects of any business need. The proposed framework is a modified enhancement in lieu of traditional data-driven decision-making approach, which is mainly dependent on quantitative data for decision-making.

Keywords: big data, customer behavior, customer experience, data mining, qualitative methods, quantitative methods, thick data

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Authors: Farid Habibi Tanha, Mojtaba Jahanbazi, Morteza Foroutan, Rasidah Mohd Rashid

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This paper depicts the effects of asymmetric information in determining capital inflows to be captured through stock market microstructure. The model can explain several stylized facts regarding the capital immobility. The first phase of the research involves in collecting and refining 150,000,000 daily data of 11 stock markets over a period of one decade in an effort to minimize the impact of survivorship bias. Three micro techniques were used to measure information asymmetries. The final phase analyzes the model through panel data approach. As a unique contribution, this research will provide valuable information regarding negative effects of information asymmetries in stock markets on attracting foreign investments. The results of this study can be directly considered by policy makers to monitor and control changes of capital flow in order to keep market conditions in a healthy manner, by preventing and managing possible shocks to avoid sudden reversals and market failures.

Keywords: asymmetric information, capital inflow, market microstructure, investment

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Authors: Himayatullah Khan, Alena Fedorova

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The present paper analyses the income-consumption relationships in Pakistan using annual time series data from 1980-81 to 2010-1. The paper uses the Augmented Dickey-Fuller test to check the unit root and stationarity in these two time series. The paper finds that the two time series are nonstationary but stationary at their first difference levels. The Augmented Engle-Granger test and the Cointegrating Regression Durbin-Watson test imply that the two time series of consumption and income are cointegrated and that long-run marginal propensity to consume is 0.88 which is given by the estimated (static) equilibrium relation. The paper also used the error correction mechanism to find out to model dynamic relationship. The purpose of the ECM is to indicate the speed of adjustment from the short-run equilibrium to the long-run equilibrium state. The results show that MPC is equal to 0.93 and is highly significant. The coefficient of Engle-Granger residuals is negative but insignificant. Statistically, the equilibrium error term is zero, which suggests that consumption adjusts to changes in GDP in the same period. The short-run changes in GDP have a positive impact on short-run changes in consumption. The paper concludes that we may interpret 0.93 as the short-run MPC. The pair-wise Granger Causality test shows that both GDP and consumption Granger cause each other.

Keywords: cointegrating regression, Augmented Dickey Fuller test, Augmented Engle-Granger test, Granger causality, error correction mechanism

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Authors: Heba Abdelmotaal, Magdy Abdel-Kader

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Purpose: This study explores whether a firm’s effective political risk management is preventing real and accrual earnings management . Design/methodology/approach: Based on a sample of 130 firms operating in Egypt during the period 2008-2013, two hypotheses are tested using the panel data regression models. Findings: The empirical findings indicate a significant relation between real and accrual earnings management and political risk. Originality/value: This paper provides a statistically evidence on the effects of the political risk management failure on the mangers’ engagement in the real and accrual earnings management practices, and its impact on the firm’s performance.

Keywords: political risk, risk management failure, real activities manipulation, accrual earnings management

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Authors: Ayotunde Qudus Saka, Xin Zhang

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Purpose: The purpose of this study is to investigate how corporate governance traits affect the financial performance of banks in the sub-Saharan African region from 2008 to 2022. Methodology/Design/Approach: The performance of a few chosen banks in Sub-Saharan Africa is examined in relation to corporate governance using static panel regression analysis. The following variables were used to present corporate governance in the study: board size (BDS), board gender diversity (BGD), board independence (BDI), number of audit committee meetings (NAM), and number of foreign members on the board (SFM). Return on assets (ROA) was employed as the dependent variable. Fixed effect (FE), random effect (RE), and common effect (CE) estimators were used with static panel data. The model estimate procedure is based on the 'Log-Lin' specification. The estimation includes eleven (11) models, ten of which relate to the individual country and one that captures the SSA countries used in this study. Finding: The RE effect estimator seems to be more efficient than the FE estimator overall. Therefore, the selected estimator used for the overall country investigation is the random effect model adopted in evaluating the connection between financial success and corporate governance, and according to the all-country specification in assessing the study's goal, the fixed effect estimator is thus selected for most of the countries except for Malawi and Zambia that common effect model worked well for showing that the banks in the aforementioned countries have similar organisational cultures and management philosophies. Consequently, the selected estimators for every country were used to evaluate the connection between financial success and corporate governance. Originality/Value: Corporate governance and bank performance topics are well grounded in literature with evidence from developed countries. However, there is a darth in developing countries particularly in the sub-Saharan African region. This study presents multi-country empirical evidence within the SSAs which gives the study more samples, this study makes use of balanced data from 2008 to 2022 being the latest data coverage from SSA, and to the best knowledge of the authors, no prior research has examined the impact of corporate governance mechanisms on bank performance in the SSA region through the use of multi-country samples.

Keywords: bank performance, corporate governance, sub-Saharan African (SSA), gender diversity, foreign member of the board, multi-country

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Authors: Akalu Banbeta, Emmanuel Lesaffre, Reynaldo Martina, Joost Van Rosmalen

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Including data from previous studies (historical data) in the analysis of the current study may reduce the sample size requirement and/or increase the power of analysis. The most common example is incorporating historical control data in the analysis of a current clinical trial. However, this only applies when the historical control dataare similar enough to the current control data. Recently, several Bayesian approaches for incorporating historical data have been proposed, such as the meta-analytic-predictive (MAP) prior and the modified power prior (MPP) both for single control as well as for multiple historical control arms. Here, we examine the performance of the MAP and the MPP approaches for the analysis of (over-dispersed) count data. To this end, we propose a computational method for the MPP approach for the Poisson and the negative binomial models. We conducted an extensive simulation study to assess the performance of Bayesian approaches. Additionally, we illustrate our approaches on an overactive bladder data set. For similar data across the control arms, the MPP approach outperformed the MAP approach with respect to thestatistical power. When the means across the control arms are different, the MPP yielded a slightly inflated type I error (TIE) rate, whereas the MAP did not. In contrast, when the dispersion parameters are different, the MAP gave an inflated TIE rate, whereas the MPP did not.We conclude that the MPP approach is more promising than the MAP approach for incorporating historical count data.

Keywords: count data, meta-analytic prior, negative binomial, poisson

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Authors: Sheng-Hung Chen, Grace Mmametena Mahlangu, Hui-Cheng Wang

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This study aims to explore the trends of the Entrepreneurial Framework Conditions (EFCs) in the five African regions. The Global Entrepreneur Monitor (GEM) is the primary source of data. The data drawn were organized into a panel (2000-2021) and obtained from the National Expert Survey (NES) databases as harmonized by the (GEM). The Methodology used is descriptive and uses mainly charts and tables; this is in line with the approach used by the GEM. The GEM draws its data from the National Expert Survey (NES). The survey by the NES is administered to experts in each country. The GEM collects entrepreneurship data specific to each country. It provides information about entrepreneurial ecosystems and their impact on entrepreneurship. The secondary source is from the literature review. This study focuses on the following GEM indicators: Financing for Entrepreneurs, Government support and Policies, Taxes and Bureaucracy, Government programs, Basic School Entrepreneurial Education and Training, Post school Entrepreneurial Education and Training, R&D Transfer, Commercial And Professional Infrastructure, Internal Market Dynamics, Internal Market Openness, Physical and Service Infrastructure, and Cultural And Social Norms, based on GEM Report 2020/21. The limitation of the study is the lack of updated data from some countries. Countries have to fund their own regional studies; African countries do not regularly participate due to a lack of resources.

Keywords: trend analysis, entrepreneurial framework conditions (EFCs), African region, government programs

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Authors: Chen-Yin Kuo, Yung-Hsin Lee

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Previous studies applying residual income valuation (RIV) model generally use panel data and single-equation model to forecast stock prices. Unlike these, this paper uses Taiwan longitudinal data to estimate multi-equation time-series models such as Vector Autoregressive (VAR), Vector Error Correction Model (VECM), and conduct out-of-sample forecasting. Further, this work assesses their forecasting performance by two instruments. In favor of extant research, the major finding shows that VECM outperforms other three models in forecasting for three stock sectors over entire horizons. It implies that an error correction term containing long-run information contributes to improve forecasting accuracy. Moreover, the pattern of composite shows that at longer horizon, VECM produces the greater reduction in errors, and performs substantially better than VAR.

Keywords: residual income valuation model, vector error correction model, out of sample forecasting, forecasting accuracy

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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: Manasse Elusma, Thung-Hong Lin, Chun-yin Lee

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The relationship between hunger and war or conflict remains to be discussed. Do wars or conflicts cause hunger and food scarcity, or is the reverse relationship is true? As the world becomes more peaceful and wealthier, some countries are still suffered from hunger and food shortage. So, eradicating hunger calls for a more comprehensive understanding of the relationship between conflict and hunger. Several studies are carried out to detect the importance of conflict or war on food security. Most of these studies, however, perform only descriptive analysis and largely use food security indicators instead of the global hunger index. Few studies have employed cross-country panel data to explicitly analyze the association between conflict and chronic hunger, including hidden hunger. Herein, this study addresses this issue and the knowledge gap. We combine global datasets to build a new panel dataset including 143 countries from 1989 to 2020. This study examines the effect of conflict on hunger with fixed effect models, and the results show that the increase of conflict frequency deteriorates hunger. Peacebuilding efforts and war prevention initiative are required to eradicate global hunger.

Keywords: armed conflict, food scarcity, hidden hunger, hunger, malnutrition

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Authors: Arjun K., Arumugam Sankaran, Sanjay Kumar, Mousumi Das

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The paper analyses the existence of endogenous growth scenario emanating from the demographic dividend in India during the liberalization period starting from 1980. Demographic dividend creates a fertile ground for the cultivation of human and knowledge capitals contributing to technological progress which can be measured using total factor productivity. The relationship among total factor productivity, human and knowledge capitals are examined in an open endogenous framework for the period 1980-2016. The control variables such as foreign direct investment, trade openness, energy consumption are also employed. The data are sourced from Reserve Bank of India, World Bank, International Energy Agency and The National Science and Technology Management Information System. To understand the dynamic association among variables, ARDL bounds approach to cointegration followed by Toda-Yamamoto causality test are used. The results reveal a short run and long run relationship among the variables supported by the existence of causality. This calls for an integrated policy to build and augment human capital and research and development activities to sustain and pace up growth and development in the nation.

Keywords: demographic dividend, young population, open endogenous growth models, human and knowledge capital

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Authors: Avishek Chanda, Nam Kyeun Kim, Debes Bhattacharyya

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The use of renewable substitutes in various semi-structural and structural applications has experienced an increase since the last few decades. Sandwich panels have been used for many decades, although research on understanding the effects of the core structures on the panels’ fire-reaction properties is limited. The current work investigates the fire-performance of a corrugated sandwich panel made from renewable, biodegradable, and sustainable material, plywood. The bench-scale fire testing apparatus, cone-calorimeter, was employed to evaluate the required fire-reaction properties of the sandwich core in a panel configuration, with three corrugated layers glued together with face-sheets under a heat irradiance of 50 kW/m². The study helped in documenting a unique heat release trend associated with the fire performance of the 3-layered corrugated sandwich panels and in understanding the structural stability of the samples in the event of a fire. Furthermore, the total peak heat release rate was observed to be around 421 kW/m², which is significantly low compared to many polymeric materials in the literature. The total smoke production was also perceived to be very limited compared to other structural materials, and the total heat release was also nominal. The time to ignition of 21.7 s further outlined the advantages of using the plywood component since polymeric composites, even with flame-retardant additives, tend to ignite faster. Overall, the corrugated plywood sandwich panels had significant fire-reaction properties and could have important structural applications. The possible use of structural panels made from bio-degradable material opens a new avenue for the use of similar structures in sandwich panel preparation.

Keywords: corrugated sandwich panel, fire-reaction properties, plywood, renewable material

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Authors: Stepan Hysek, Premysl Sedivka, Petra Gajdacova

Abstract:

Currently, structural composite materials contain cellulose-based particles (wood chips, fibers) bonded with synthetic adhesives containing formaldehyde (urea-formaldehyde, melamine-formaldehyde adhesives and others). Formaldehyde is classified as a volatile substance with provable carcinogenic effects on live organisms, and an emphasis has been put on continual reduction of its content in products. One potential solution could be the development of an agglomerated material which does not contain adhesives releasing formaldehyde. A potential alternative to formaldehyde-based adhesives could be polyurethane adhesives containing no formaldehyde. Such adhesives have been increasingly used in applications where a few years ago formaldehyde-based adhesives were the only option. Advantages of polyurethane adhesive in comparison with others in the industry include the high elasticity of the joint, which is able to resist dynamic stress, and resistance to increased humidity and climatic effects. These properties predict polyurethane adhesives to be used in OSB/EPS panel production. The objective of this paper is to develop an adhesive for bonding of sandwich panels made of material based on wood and other materials, e.g. SIP) and optimization of input components in order to obtain an adhesive with required properties suitable for bonding of the given materials without involvement of formaldehyde. It was found that polyurethane recyclate as a filler is suitable modification of polyurethane adhesive and results have clearly revealed that modified adhesive can be used for OSB/EPS panel production.

Keywords: adhesive, polyurethane, recyclate, SIP

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Authors: Ayodele Ajayi, John Ajayi

Abstract:

This paper investigates the effect of corporate governance with a view to determining the relationship between board size and bank performance. Data for the study were obtained from the audited financial statements of five sampled banks listed on the Nigerian Stock Exchange. Panel data technique was adopted and analysis was carried out with the use of multiple regression and pooled ordinary least square. Results from the study show that the larger the board size, the greater the profit implying that corporate governance is positively correlated with bank performance.

Keywords: corporate governance, banks performance, board size, pooled data

Procedia PDF Downloads 361

Authors: Priscila A. Bernardes, Marcos E. Buzanskas, Luciana C. A. Regitano, Ricardo V. Ventura, Danisio P. Munari

Abstract:

Genotype imputation has been used to reduce genomic selections costs. In order to increase haplotype detection accuracy in methods that considers the linkage disequilibrium, another approach could be used, such as combined genotype data from different panels. Therefore, this study aimed to evaluate the linkage disequilibrium and haplotype blocks in two high-density panels before and after the imputation to a combined panel in Nelore beef cattle. A total of 814 animals were genotyped with the Illumina BovineHD BeadChip (IHD), wherein 93 animals (23 bulls and 70 progenies) were also genotyped with the Affymetrix Axion Genome-Wide BOS 1 Array Plate (AHD). After the quality control, 809 IHD animals (509,107 SNPs) and 93 AHD (427,875 SNPs) remained for analyses. The combined genotype panel (CP) was constructed by merging both panels after quality control, resulting in 880,336 SNPs. Imputation analysis was conducted using software FImpute v.2.2b. The reference (CP) and target (IHD) populations consisted of 23 bulls and 786 animals, respectively. The linkage disequilibrium and haplotype blocks studies were carried out for IHD, AHD, and imputed CP. Two linkage disequilibrium measures were considered; the correlation coefficient between alleles from two loci (r²) and the |D’|. Both measures were calculated using the software PLINK. The haplotypes' blocks were estimated using the software Haploview. The r² measurement presented different decay when compared to |D’|, wherein AHD and IHD had almost the same decay. For r², even with possible overestimation by the sample size for AHD (93 animals), the IHD presented higher values when compared to AHD for shorter distances, but with the increase of distance, both panels presented similar values. The r² measurement is influenced by the minor allele frequency of the pair of SNPs, which can cause the observed difference comparing the r² decay and |D’| decay. As a sum of the combinations between Illumina and Affymetrix panels, the CP presented a decay equivalent to a mean of these combinations. The estimated haplotype blocks detected for IHD, AHD, and CP were 84,529, 63,967, and 140,336, respectively. The IHD were composed by haplotype blocks with mean of 137.70 ± 219.05kb, the AHD with mean of 102.10kb ± 155.47, and the CP with mean of 107.10kb ± 169.14. The majority of the haplotype blocks of these three panels were composed by less than 10 SNPs, with only 3,882 (IHD), 193 (AHD) and 8,462 (CP) haplotype blocks composed by 10 SNPs or more. There was an increase in the number of chromosomes covered with long haplotypes when CP was used as well as an increase in haplotype coverage for short chromosomes (23-29), which can contribute for studies that explore haplotype blocks. In general, using CP could be an alternative to increase density and number of haplotype blocks, increasing the probability to obtain a marker close to a quantitative trait loci of interest.

Keywords: Bos taurus indicus, decay, genotype imputation, single nucleotide polymorphism

Procedia PDF Downloads 281