Method Of Moments Research Articles

3D-AMM: a 3D artificial moment method for path planning of manipulator in multiple obstacles scenario

Purpose In response to the issue of traditional algorithms often falling into local minima or failing to find feasible solutions in manipulator path planning. The purpose of this paper is to propose a 3D artificial moment method (3D-AMM) for obstacle avoidance for the robotic arm's end-effector. Design/methodology/approach A new method for constructing temporary attractive points in 3D has been introduced using the vector triple product approach, which generates the attractive moments that attract the end-effector to move toward it. Second, distance weight factorization and spatial projection methods are introduced to improve the solution of repulsive moments in multiobstacle scenarios. Third, a novel motion vector-solving mechanism is proposed to provide nonzero velocity for the end-effector to solve the problem of limiting the solution of the motion vector to a fixed coordinate plane due to dimensionality constraints. Findings A comparative analysis was conducted between the proposed algorithm and the existing methods, the improved artificial potential field method and the rapidly-random tree method under identical simulation conditions. The results indicate that the 3D-AMM method successfully plans paths with smoother trajectories and reduces the path length by 20.03% to 36.9%. Additionally, the experimental comparison outcomes affirm the feasibility and effectiveness of this method for obstacle avoidance in industrial scenarios. Originality/value This paper proposes a 3D-AMM algorithm for manipulator path planning in Cartesian space with multiple obstacles. This method effectively solves the problem of the artificial potential field method easily falling into local minimum points and the low path planning success rate of the rapidly-exploring random tree method.

Can financial inclusion enhance human development? Evidence from low- and middle-income countries

The purpose of this study is to determine if financial inclusion in low-, lower-middle-, and upper-middle-income nations promotes human development. Our aim was accomplished by employing an empirical technique of using the System Generalized Method of Moments (SGMM) and dynamic threshold panel (DTP) data on a sample of 79 nations between 2000 and 2017. Three sub-samples representing low-, lower-, and upper-middle-income nations were created from the entire sample. In general, lower- and upper-middle-income nations’ human development is positively impacted by financial inclusion, according to SGMM empirical studies. Furthermore, the DTP method’s results show that there is a threshold impact for both human development and financial inclusion. The degree of human development in upper-middle-income and lower-middle-income countries is greatly raised by financial inclusion, whether the threshold is met or beyond.

Determination of Insurance Premium Rates with Aggregation Claims at BPJS with Exponential and Gamma Distributions

Badan Penyelenggara Jaminan Sosial (BPJS) is a legal entity that has been provided by the government for the community with the aim of providing protection for all workers in Indonesia from certain socio-economic risks. National development, marked by planned and continuous strides, embodies a commitment to engage all societal, national, and state levels in fostering progress. Encompassing political, economic, socio-cultural, and defense and security realms, the development is meticulously designed to be comprehensive, targeted, integrated, gradual, and sustainable. The overarching objective is to catalyze an augmentation of national capabilities, align the standard of living for the Indonesian people with developed nations, and elevate overall welfare. To establish premium rates, a method involves multiplying the conditional expected value of claim frequency by the size of the claim, considering observed risk characteristics. A claim, in this context, constitutes a formal request to the insurance company, seeking payment in accordance with the terms of the agreement. The primary objective of this study is to establish the insurance premium rates applicable to policyholders (the insured) through the estimation of parameters in the distribution governing aggregate claims. This involves the distribution of both the number of claims and the size of the claims, and the estimation is performed using the moment method. Premium computations are executed based on two key principles: the pure premium principle and the expected value principle. This research produces the conclusion that the Poisson-Gamma aggregate claims distribution has a premium amount of 3.61 times greater than Poisson-Exponential due to the application of the anticipated value principle, namely IDR 4,403,542.94 per month and IDR 1,219,878.45 per month, respectively.  

Dynamic reliability analysis of angular contact ball bearing based on maximum entropy quadratic fourth moment method*

ABSTRACT Bearing failure occurs when the dynamic contact stress exceeds the yield strength of the bearing material during operation. To minimise the risk of bearing failure, a new reliability theory method is proposed based on the stress-strength model of bearings, incorporating random input variables to analyse the reliability of angular contact ball bearings (ACBBs) and quantify their dynamic performance. The maximum entropy quadratic fourth moment method is used to calculate the probability distribution of maximum orthogonal shear stress-strength of bearing, and the maximum entropy principle is used to obtain the approximation of the minimum human error factors. Additionally, reliability-based sensitivity indices are derived to investigate the parametric significance of random input variables. Using B218 bearing as an example, the engineering application of this method in dynamic reliability and reliability-based sensitivity analysis is illustrated. Monte Carlo simulation is performed to verify the accuracy and effectiveness of the method to provide benchmark results. The results show that the Poisson’s ratio have a greater influence on the dynamic reliability of ACBBs than other parameters. Improving parameters such as ball diameter, raceway groove curvature radius and contact angle can also improve the reliability of bearings to some extent.

225 Genomic diversity of Katahdin sheep and impacts on genomic prediction

Abstract In the late 1950s, Katahdin hair sheep were developed as a composite breed of medium size and moderate prolificacy, with potential to express resistance to gastrointestinal nematodes. With its increasing popularity and the recent adoption of genomic prediction in the Katahdin breeding program, evaluating the genetic diversity in this breed is necessary. Prediction accuracies rely on the strength of genetic relationships. That strength often increases with selection using genomically-enhanced estimated breeding values; however, it carries the risk of decreasing diversity. We aim to characterize the genetic diversity present in the breed and the subsequent impact on the accuracies of genomic predictions. Genotypes on Katahdin sheep from member flocks in the National Sheep Improvement Program were used. Data from two medium density 50k bead chips and one high density 600k bead chip were merged and limited to shared autosomal single nucleotide polymorphisms (SNP). After quality control, there were 9,705 animals and 31,984 SNP remaining. Only for analyses of inbreeding and heterozygosity, linkage disequilibrium (LD) pruning was performed; variants with an LD score exceeding 0.8 were removed with 29,904 SNP remaining. To determine the extent of population structure, principal component (PC) analysis was conducted with PC one and PC two explaining 4.9% and 3.8% of the variation in the population, respectively. When examining subpopulations, a single ancestral population explained 99.9% of the genetic variation among animals. When clustered by identity-by-state, all animals were placed in a single cluster. Inbreeding coefficients were estimated with four methods: method of moments, variance-standardized relationship minus one, excess homozygosity, and correlation between uniting gametes. Across methods, average inbreeding coefficients ranged from 1.14% to 1.20% with Pearson and Spearman correlations ranging from -0.51 to 0.91 (Table 1). Historical effective population sizes (Ne) were estimated for earlier generations, and a linear regression fit to predict more recent Ne. At the founding of the breed, historical Ne was estimated to be 310, and the current Ne was estimated to be 150. Effects of Ne on the accuracy of genomic predictions were examined for reference population sizes ranging from 1k to 25k for traits of low (0.1), moderate (0.3), and high (0.5) heritabilities. The corresponding number of effective chromosomal segments were 2NeL, where L was the length of the genome in morgans (26M). Accuracies of genomic predictions increased as the reference population size grew, with only marginal gains once the population exceeded 15k. Overall, there were no detectable genetic subpopulations in the Katahdin breed. Current levels of inbreeding were low. With a small Ne the breed can achieve high accuracy for genomic predictions by aiming for a reference population of 15k animals. Negative impacts on genetic diversity due to genomic selection are not of immediate concern.

Informal Institutions and Audit Pricing: Cross-Country Evidence of National Culture and Audit Fees

Synopsis The research problem In this study, we examined the effect of an important informal institution, namely, national culture, on audit fees in an international context. Motivation In recent years, extant literature has increasingly focused on country-level differences in the audit environment, as these might have a significant influence on how financial statement audits are conducted across the globe. We contribute to this stream of literature by investigating the impact of national culture on audit fees. The test hypotheses Based on the demand- and supply-side perspectives of audit fees, we hypothesized that national culture dimensions — namely, uncertainty avoidance, power distance, individualism versus collectivism, and masculinity versus femininity — affect audit fees. Target population We used a sample of 27,670 firm-year observations across 22 countries over the 2002–2019 period. Adopted methodology We used ordinary least squares (OLS) regressions as baseline technique and entropy-balanced method (EBM) and system-generalized method of moments (GMM) to address endogeneity concerns. Analyses We examined the impact of Hofstede’s four national culture dimensions — uncertainty avoidance, power distance, individualism versus collectivism, and masculinity versus femininity — on audit fees. We also tested the robustness of results using alternative measures of national culture, subsample analyses, and additional firm-level factors. Findings Consistent with our hypotheses, we find that audit fees are higher (lower) in countries with higher uncertainty avoidance, individualism, and masculinity (power distance) scores. Our further analyses reveal that earnings management proxied by abnormal accruals does not impact the relationship; however, country-level creditor rights influence audit fees in high power distance and masculine cultures. We also note that national culture influences auditor choice and audit opinion. Our main findings are robust to alternate proxies and subsample analysis, as well as to address potential endogeneity concerns. Overall, our findings offer important implications for firms operating in global markets and for the audit profession.

Foreign direct investment, information and communication technology, and economic growth: The case of North African Countries

This paper examines the role of information and communication technology (ICT) in modulating the effects of foreign direct investment (FDI) on economic growth in North Africa (Morocco, Algeria, Tunisia, and Egypt) over the period 1995 to 2021. Using advanced quantitative methods, including quantile regression, and comparing with Two-Stage Least Squares (2SLS) regression and Generalized Method of Moments (GMM), the study assesses the impact of FDI and ICT on growth, controlling for country fixed effects. The results indicate that FDI has a significant positive impact on growth, particularly when interacting with transmission channels, notably the telephone (mobile and fixed). However, the interaction with the internet varies according to quantile levels, showing positive effects at low quantiles and negative effects at high quantiles. The study highlights the importance of investment policies, digital inclusion, and research to optimize the benefits of FDI in the region.

Turbulent Periods, Earnings Management and the Role of Auditors

The present study attempts to test the impact of audit, non-­audit fees, auditor tenure, auditor size, and financial distress on earnings management during turbulent periods for the five largest Eurozone countries. The motivation of the current study is to provide fresh evidence on these relationships during global financial crisis and sovereign debt crisis. We use the generalized methods of moments and ordinary least squares method for a sample of listed firms across the five largest Eurozone countries. We found that auditor tenure and auditor size carry no significant effect on earnings management during the financial crisis and sovereign debt crisis period as compared to the pre-crisis period for both cases. However, audit, non-audit fees and financial distress affect earnings management during the Eurozone crises periods. The results imply that stricter accounting regulation is needed during turbulent periods and investors should be careful with their investments.

Do Cross-Border Mergers and Acquisitions by Emerging Market Enterprises Enhance Long-Term Productivity? The Host Country Market Size Effect Moderated by Technological Absorption Efforts

The purpose of this study was to establish a spatial structural framework to explore how cross-border mergers and acquisitions (M&As) in emerging markets can enhance long-term productivity and select the appropriate host country market structures. Utilizing cross-border M&A data from Chinese companies from 2008 to 2016, we developed a moderated U-shaped mediation model. Employing Two-Stage Least Squares and the Generalized Method of Moments for endogeneity analysis, we offer robust empirical insights. Our findings illustrate that enterprise productivity progression from cross-border M&As is significantly influenced by a U-shaped mediation of the host country’s market size effect, which is further moderated by the technological distance between the home and host countries. A high technological distance intensifies the U-shaped mediation of market size effects on enterprise productivity, while low technological distances result in an inverted U-shaped curve, indicating that such markets may boost short-term productivity but limit long-term growth. Conversely, larger markets with greater technological distances better support sustained productivity increases, even requiring persistent technological absorption efforts. This study underscores the necessity of selecting appropriate host country market structures and effectively managing the acquisition timeline to positively impact both short- and long-term productivity. By conceptualizing firm-level technological absorption efforts as the technological gap between the home and host countries, this study highlights the crucial moderating role that the technological gap plays in influencing long-term productivity at the macro level, providing new insights into the economic geographic strategic decisions and spatial planning for emerging market enterprises in cross-border acquisitions.

Effect of an inclined magnetic field on dispersion of solute in a pulsatile flow through a channel of absorptive porous walls

The present investigation gives an insight to comprehend the complex mechanism of species transport through porous walls, which has applications for crude oil refining, oil reservoir engineering, and separation of metal from fluids. The paper analyzes the impact of an inclined magnetic field on mass transport phenomena of solute through an unsteady, viscous, incompressible, and electrically conducting fluid flowing between two parallel plates. Both plates are permeable, and the flow is driven by a periodic pressure gradient. At both channel walls, the first order boundary reaction is applied. The governing time depending advection and diffusion equation is solved numerically based on Aris's method of moments. To determine the axial mean concentration distribution of solute, the first four central moments are used in a Hermite polynomial representation. It is significant to note that the dispersion of tracer is more significant for the low frequencies rather than the high frequencies. The behavior of the dispersion process of the tracer is studied for various flow parameters such as the angle of inclination of the magnetic field (α), Hartmann number (M), absorption parameter (β), suction Reynolds number (R), injection Reynolds number (R′), Womersley number (ω), and dispersion time (t) for both purely oscillatory and combined flows. It is significant to note that with the increment of R, α, and M, the amplitude of the dispersion coefficient of the solute reduces. On the other hand, an opposite phenomenon is observed for R′. It is seen that the transport coefficient moves cyclically with a double frequency period for all values of R and R′. Also, it is found that the peak of the mean concentration distribution enhances with the increment of α and M because the flow velocity decreases.

Optimal Control of Chromate Removal via Enhanced Modeling Using the Method of Moments

Optimal Control of Chromate Removal via Enhanced Modeling Using the Method of Moments

A parametric bootstrap approach for computing confidence intervals for genetic correlations with application to genetically-determined protein-protein networks.

Genetic correlation refers to the correlation between genetic determinants of a pair of traits. When using individual-level data, it is typically estimated based on a bivariate model specification where the correlation between the two variables is identifiable and can be estimated from a covariance model that incorporates the genetic relationship between individuals, e.g., using a pre-specified kinship matrix. Inference relying on asymptotic normality of the genetic correlation parameter estimates may be inaccurate when the sample size is low, when the genetic correlation is close to the boundary of the parameter space, and when the heritability of at least one of the traits is low. We address this problem by developing a parametric bootstrap procedure to construct confidence intervals for genetic correlation estimates. The procedure simulates paired traits under a range of heritability and genetic correlation parameters, and it uses the population structure encapsulated by the kinship matrix. Heritabilities and genetic correlations are estimated using the close-form, method of moment, Haseman-Elston regression estimators. The proposed parametric bootstrap procedure is especially useful when genetic correlations are computed on pairs of thousands of traits measured on the same exact set of individuals. We demonstrate the parametric bootstrap approach on a proteomics dataset from the Jackson Heart Study.

A machine learning and quantile analysis of FINTECH and resource efficiency in achieving sustainable development in OECD countries

This study aims to examine the impact of fintech investments and resource efficiency on sustainable development in OECD countries between 2010 and 2019. Various estimation techniques, including the Method of Moments Quantile Regression (MMQREG), machine learning-based Kernel Regularized Least Squares (KRLS), and Generalized Method of Moments (GMM), have been utilized in this study. MMQREG and KRLS are both estimators that examine the relationship between variables in several qunatiles, increasing the reliability of the findings. The research results indicate that fintech investments and resource efficiency support sustainable development. Additionally, institutional quality, environmentally friendly technologies, and foreign trade are found to have a positive impact on sustainable development. These findings suggest that financial technology and resource management can play a significant role in promoting both economic and environmental sustainability.

Incorporating historical flood events in type-based statistics

Flood statistics form the basis of many hydrologic designs. However, short observation periods can lead to a high degree of uncertainty in the quantile estimates, especially for extreme floods. One way to expand the information used in the statistics and, in particular, to include other exceptional floods in the sample is to take historical floods into account. The use of these floods, which are usually reconstructed from chronicles or flood marks, has long been established for classic flood frequency analysis. However, the fact that historical floods can also have different origins and are therefore not statistically identically distributed has so far been ignored. To avoid this violation of the statistical assumptions, we show how historical floods, subdivided according to their genesis, can be taken into account in type-based flood statistics. For this purpose, the classical partial probability weighted moment (PPWM) method is extended for the type-based mixture model of partial duration series (TMPS). The result is compared to a Markov chain Monte Carlo method in order to compare the differences between the two methods. Type-based statistics can also be used to attribute the different influences of historical floods on the quantile estimate. An example shows that floods associated with long-lasting precipitation in particular are overestimated in short samples, while heavy rainfall floods are comparatively well represented. The results show that the consideration of historical events in type-based statistics not only allows a more balanced view of extreme floods, but also enables the influences of these to be attributed.

Market power, human capital efficiency and bank performance in Kenya

PurposeThe study evaluates the influence of human capital efficiency (HCE) and market power on bank performance.Design/methodology/approachThe study employs two measures of bank performance: profitability and stability. Unbalanced panel data of 35 banks operating in Kenya for 2005–2020 collected from published financial statements is utilized. The study employs the feasible generalized least squares (FGLS) method in the analysis and the two-step system generalized method of moments (GMM) for robustness check.FindingsThe study affirms an inverted U-shaped relationship between market power and bank performance. The effect of market power on bank profitability is enhanced when a bank has highly efficient human capital. Further, HCE significantly impacts bank stability for banks with low HCE. Interestingly, a further increase in HCE narrows the net interest margins for banks with high HCE, conferring welfare benefits to customers as interest rate spreads shrink.Practical implicationsThis study provides important insights into the role of human capital in bank performance. First, banks ought to invest in promoting HCE through training and development. As regulators root for bank consolidation, attention to HCE is imperative for fostering profitability and stability.Originality/valueThe study fills an essential gap in the literature by evaluating the effect of firm-level market power on bank performance in an emerging market. We adopt a novel stochastic frontier estimator to generate the Lerner index. Further, this is the first study known to the authors to evaluate the effect of market power on bank performance in the context of human capital efficiency variations.

Exploring the Nexus of Decent Work, Financial Inclusion, and Economic Growth: A Study Aligned with SDG 8

We investigate the potential influence of fair employment practices and financial inclusion on economic growth, focusing on aligning our analysis with the United Nations Sustainable Development Goal 8 (SDG 8). Our study encompasses various countries, including 26 low-income, 20 middle-income, and 15 high-income nations. Utilizing a dynamic fixed-effect panel data approach and employing the Generalized Method of Moments from 2010 to 2021, our findings reveal that conducive environments for decent work and enhanced access to digital financial services positively impact economic growth. This synergistic effect of SDG 8 components is particularly pronounced in high-income countries, suggesting the potential for accelerated economic growth rates. Conversely, our analysis finds no discernible impact on the economic growth of low-income countries. For middle-income countries, nuanced coefficient outcomes provide a more intricate understanding of their economic dynamics. Through extensive impulse-response analysis using a Panel Vector Autoregression model, we illustrate the distinct effects of shocks related to decent work and financial inclusion across various income categories. Our results are robust to multiple sensitivity tests, underscoring their reliability and signaling significant policy implications for acknowledging the critical role of decent work and financial inclusion in fostering economic growth.

Human Capital Efficiency and Firm Performance of Quality-Certified Firms from EFQM Excellence Model: A Dynamic Panel Data Study

Abstract Purpose The study’s main purpose is to investigate the impacts of human capital efficiency (HCE) on the firm performance of non-certified and quality-certified firms from the European Foundation for Quality Management (EFQM) Excellence Model. The study also examines the relationship between firm performance and quality-certificates from the European Foundation. Design/methodology/approach By using a sample of 282 non-certified and 22 quality-certified firms from 2017 to 2021, the current study employed a two-step system generalized method of moments (GMM) estimation to analyse the empirical data. The dummy variable is used to examine the relationship between quality-certificates and firm performance. The dummy interaction term is employed to quantify the impacts of HCE on the firm’s performance for quality-certified firms. Findings The results revealed that quality-certificates and firm performance have a positive relationship. Quality-certified firms perform better and earn more profits than non-certified firms. HCE has a positive impact on firm performance for both types of firms. Moreover, the quality-certified firms utilize HCE in an efficient way to earn more profits compared to the non-certified firms. Originality This is the first study to use a comprehensive analysis to emphasize the HCE for non-certified and quality-certified firms separately. The effects of quality-certificates on firm performance in the context of HCE are also being highlighted for the first time in this research. Practical implications The current study’s findings are fruitful for academics, managers, researchers, policymakers, and other firm management. The findings will encourage the management of the firms to implement the total quality management (TQM) approach within their firms.

Sustainable accounting quality and its impact on financial success aligned with SDGs

Purpose Financial and nonfinancial disclosures (sustainable accounting) are crucial in the annual financial reports of many firms. This study aims to explore the dynamic relationship between sustainability disclosure quality (SDQ) and financial performance (FP) within mandatory disclosure frameworks. SDQ is evaluated across six dimensions, encompassing both the quality and quantity of disclosures, aiming to understand their reciprocal influence. Design/methodology/approach Using the generalized method of moments (GMM), this research analyzes data from 2013 to 2019, focusing on 99 listed Indian firms within the S&P Bombay stock exchange (BSE) 500 index. The study uses rigorous measurement criteria to assess SDQ and uses statistical methods to unveil the causal link between SDQ and FP. Findings The results show a positive causal connection between SDQ and FP, where organizations with good FP make relatively higher disclosures across FP proxies than their counterparts. Additionally, the study investigates the impact of research and development (R&D) expenditure and dividend payments (DIVD) on SDQ. Notably, lower R&D spending is associated with higher quality SDs, and companies with superior SDQ exhibit increased DIVD. Practical implications The findings advocate for strengthened regulatory compliance, incentivized sustainable practices and heightened reporting standards for a transparent business environment and achieving the relevant United Nations Sustainable Development Goals. Originality/value This research contributes original insights by uncovering the intricate relationship between SDQ and FP, shedding light on the impact of R&D expenditure and DIVD on SDQ. These findings contribute to a nuanced understanding of the interplay between FP and sustainability reporting within the context of mandatory disclosure frameworks.

Quality of Urban Infrastructural Service Accessibility and Human Well-being in Sub-Saharan Africa

Urban infrastructure critically influences how urban people carry their lives and mediates how services central to human well-being are accessed. Therefore, the main of this study is twofold: One, the study interrogates how the quality of urban infrastructural service accessibility influences human well-being, and two, how governance interactively with urban infrastructural services affects human well-being using balanced panel data from 2000 to 2020 from 22 Sub-Saharan African countries. Applying the Driscoll-Kraay and Two-Step Instrumental Variable Generalized Method of Moments (2SIV-GMM) in panel dynamic model setup, we uncover that increasing the quality of accessing urban infrastructural services results in enhanced human well-being. Interrogating the role of governance on human well-being, the findings depict a significant detrimental interactive effect between governance and urban infrastructural services on human well-being. Accounting for rapid urbanization in the Sub-Saharan African region, the results illustrate significant negative control effects of urbanization rate and aftermath urban agglomeration on human well-being. Conclusively, effective government policies that influence higher levels of human well-being in regions with large urban agglomerations are paramount. Thus, effective government investments in urban infrastructural services in Sub-Saharan Africa remain a vital sustainability policy agenda.

Politically connected independent supervisory boards and corporate performance during COVID‐19: Evidence from Indonesia

This study aims to examine the relationship between the political connections of companies' independent supervisory boards (PC‐ISB) to these firms' performance during the COVID‐19 pandemic in Indonesia. This study used 1515 observations of companies listed on the Indonesian Stock Exchange (IDX) for the years 2018–2021. The test was carried out using moderated regression analysis. Additional tests were also conducted, such as market performance tests and endogeneity tests using the System Generalized Method of Moments (the System GMM) and the difference‐in‐difference (DID) regression analysis. Results confirm that PC‐ISB has a significant positive effect on company performance. Then, during the COVID‐19 pandemic, the company's performance got worse. However, we did not find that pandemic conditions moderated the relationship between PC‐ISB and company performance. Our results remained consistent after testing using the System GMM and the DID to address the issue of endogeneity.