Squares Method For Estimation Research Articles

Validating Tools to Measure Life Skills Among Adolescents in India

Life skill education is critical for developing various competencies among the adolescent population, especially in India, given the recent shift in policy focus. This article examines the reliability, factor structure, and the validity of scales measuring gender attitudes, perceived self-efficacy, resilience, and problem-solving developed to assess the effectiveness of a life skill program among Indian adolescents. Baseline data, before a life skill intervention program by Magic Bus India Foundation, were collected from over 16000 Indian adolescents between 11 and 15 years on different measures. Results from principal component analyses with promax rotation indicated a one-factor solution for all the scales. Further, confirmatory factor analyses indicated an excellent model fit using the diagonally weighted least squares method of estimation for the above-mentioned scales. The models for each scale were gender invariant, indicating that gender attitudes, perceived self-efficacy, resilience, and problem solving were assessed similarly between boys and girls. Additionally, correlation analysis indicated a positive relationship between gender attitudes and self-efficacy, a negative relation between gender attitudes and resilience, and a negative association between self-efficacy and resilience. Implications are discussed.

Economic Complexity and Renewable Energy Effects on Carbon Dioxide Emissions: a Panel Data Analysis of Middle East and North Africa Countries

AbstractWith the rising economic complexity of the world economy, applied research has been focusing on the economic complexity-environmental quality nexus. Many of the Middle East and North Africa (MENA) countries and Turkey show relatively low economic complexity with undiversified product spaces. The present study is thereby motivated to investigate the economic complexity-environmental quality relation for the MENA countries and Turkey. Using panel data for eighteen MENA countries and Turkey over the period 1990–2020, the fully modified ordinary least squares method of estimation is employed in two separate models, and Granger causality tests are performed. Each model includes the relation of economic complexity to carbon dioxide (CO2) emissions, one form of energy (renewable or non-renewable), population density and variables to validate the environmental Kuznets curve (EKC) hypothesis. In model (1), a negative and statistically significant renewable energy consumption has a mitigating effect on CO2 emissions, though economic complexity and its interaction with renewable energy consumption are not statistically significant. In model (2), a positive and statistically significant non-renewable energy indicates that increased fossil fuel reliance increases CO2 emissions (deteriorating environmental quality), while a negative and statistically significant economic complexity and population density reduce CO2 emissions (improving environmental quality), respectively. The EKC hypothesis is validated for the MENA countries and Turkey in both models (1) and (2), and Granger causality test results are given. Among the key policy implications are that the MENA countries and Turkey must recognize that increasing GDP and industrialization must be coupled with moving from less- to more-knowledge-based structures.

A new least squares method for estimation and prediction based on the cumulative Hazard function

<abstract><p>In this paper, the cumulative hazard function is used to solve estimation and prediction problems for generalized ordered statistics (defined in a general setup) based on any continuous distribution. The suggested method makes use of Rényi representation. The method can be used with type Ⅱ right-censored data as well as complete data. Extensive simulation experiments are implemented to assess the efficiency of the proposed procedures. Some comparisons with the maximum likelihood (ML) and ordinary weighted least squares (WLS) methods are performed. The comparisons are based on both the root mean squared error (RMSE) and Pitman's measure of closeness (PMC). Finally, two real data sets are considered to investigate the applicability of the presented methods.</p></abstract>

Parametric inference of generalized process capability index Cpyk for the power Lindley distribution

ABSTRACT In this article, to estimate the generalized process capability index (GPCI) Cpyk when the process follows the power Lindley distribution, we have used five methods of estimation, namely, maximum likelihood method of estimation, ordinary and weighted least squares method of estimation, the maximum product of spacings method of estimation, and Bayesian method of estimation. The Bayesian estimation is studied with respect to both symmetric (squared error) and asymmetric (linear-exponential) loss functions with the help of the Metropolis-Hastings algorithm and importance sampling method. The confidence intervals for the GPCI Cpyk is constructed based on three bootstrap methods and Bayesian methods. Besides, asymptotic confidence intervals based on maximum likelihood method is also constructed. We studied the performances of these estimators based on their corresponding biases and MSEs for the point estimates of GPCI Cpyk, and coverage probabilities (CPs), and average width (AW) for interval estimates. It is found that the Bayes estimates performed better than the considered classical estimates in terms of their corresponding MSEs. Further, the Bayes estimates based on linear-exponential loss function are more efficient than the squared error loss function under informative prior. To illustrate the performance of the proposed methods, two real data sets are analyzed.In this article, to estimate the generalized process capability index (GPCI) when the process follows the power Lindley distribution, we have used five methods of estimation, namely, maximum likelihood method of estimation, ordinary and weighted least squares method of estimation, the maximum product of spacings method of estimation, and Bayesian method of estimation. The Bayesian estimation is studied with respect to both symmetric (squared error) and asymmetric (linear-exponential) loss functions with the help of the Metropolis-Hastings algorithm and importance sampling method. The confidence intervals for the GPCI is constructed based on three bootstrap methods and Bayesian methods. Besides, asymptotic confidence intervals based on maximum likelihood method is also constructed. We studied the performances of these estimators based on their corresponding biases and MSEs for the point estimates of GPCI , and coverage probabilities (CPs), and average width (AW) Abbreviations: AW : Average width; : Bias-corrected percentile bootstrap; BCI : Bootstrap confidence interval; CDF : Cumulative distribution function; CI : Confidence interval; CK : Coefficient of kurtosis; CP : Coverage probability; CS : Coefficient of skewness; GGD : Generalized gamma distribution; GPCI : Generalized process capability index; GLD : Generalized lindley distribution; SWCI : Shortest width credible interval; IS : Importance sampling; K-S : Kolmogorov-Smirnov; : Lower specification limi; LD : Lindley distribution; LDL : Lower desired limitLLF : Linex loss function; MCMC : Markov Chain Monte Carlo; MH : Metropolis-Hastings; MPSE : Maximum product of spacings estimator; MLE : Maximum likelihood estimator; MSE : Mean squared error; OLSE : Ordinary least squares estimator; : Percentile bootstrap; PDF : Probability density function; PCI : Process capability index; PLD : Power Lindley distribution; : -th quartile; SD : Standard deviation; : Standard bootstrap; SELF : Squared error loss function; : Target value; : Upper specification limit; : Upper desired limit; WD : Weibull distribution; WLSE : Weighted least squares estimator

Financial Resource Mobilisation Strategies and Sustainability of Non-Governmental Organisations (NGOs): Evidence from Nigeria

Abstract Background The challenge facing NGOs in most developing countries is the need to emerge as valuable forces that affect development in order to improve the living conditions of the people in several communities. Funding is necessary for the survival and development of these NGOs. Research aims: This study, therefore, sought to find out the efect of financial resource mobilisation strategies on the sustainability of NGOs in Nigeria, with particular reference to the Minna metropolis. Research aims The purposive sampling technique was used to select 118 staf from 50 NGOs as a sample size for the study. Three alternative hypotheses were raised to be tested at P<.05 and a structured questionnaire was adopted for data collection. The data were analysed using descriptive statistics, Pearson Correlation, and the Ordinary Least Square method of estimation. Methodology The result revealed the existence of a statistically significant and positive relationship between private contributions and the sustainability of NGOs, a positive but insignificant relationship between commercial activities and sustainability of NGOs, and an inverse relationship between government funding and sustainability of NGOs. Findings The study established that private contributions affect the sustainability of NGOs to a very large extent; government funding does not improve the sustainability of NGOs, and commercial activities do not have a significant impact on the sustainability of NGOs. Consequently, the study recommended that management and staf of NGOs should create more awareness about their operations in order to attract better contributions from private individuals and organisations.

Financial Management and Organizational Culture as a Hybrid for SMEs' Performance in Nigeria

Purpose: This study jointly examines the impact of financial management and organizational culture on the performance of SMEs in Nigeria with particular reference to Oyo State.
 Methods Purposive sampling techniques were employed to select a total of 658 SME operators/managers engaging in trading, manufacturing, services, Agro-allied, and construction. Mean, and least square method of estimation was used to analyze the data.
 Results: The result reveals that financial management and organizational culture jointly and independently influence SMEs’ performance. The study further reveals that SMEs are ready to imbibe financial management culture if adequate training on financial skills is provided for the sector by the government, accounting professional bodies, and the tertiary institution of learning, which will foster the growth of entrepreneurship and prudently manage their finances. Implications: The implication of this study is that for the sector to swimming in prosperity, SMEDAN should make the certificate in financial management culture as of the prerequisites for the registration. Also, the Federal Ministry of Education should introduce financial management culture into curricula for all tertiary institutions of learning as well as accounting professional bodies in Nigeria.

Does Research and Development Expenditure Incite Quality of Economic Growth? Evidence from China

A recent economic and political history has extensively shown that high growth alone does not necessarily lead to better social outcomes. Quality of growth has, therefore, become a popular lemma over the past few years. Most countries are now concentrating on how to improve the quality of growth rather than the quantity. This study, therefore, aimed at assessing the impact of innovation on the quality of economic growth in China, using Research and Development Expenditure as an indicator for innovation, and Human Development Index as an indicator for quality of economic growth. A time series data covering a period from 2000 to 2019, and the Ordinary Least Square method of estimation were used in the regression analysis. The results of the study provide evidence that research and development expenditure is a vital factor for ensuring quality of economic growth. The findings of the study is very essential for policymakers in China, as China in its 14th Five-Year plan, intends to increase its spending on research and development to enhance innovation activities. This provides adequate evidence for the government of China, as well as other emerging economies, that as a country increases its investment in research and development, it stands a better chance for enhancing its quality of growth, and also achieving its Sustainable Development Goals. The study also adds new empirical evidence to the existing literature on innovation and economic growth.

Strategic Agility and Small and Medium Enterprises’ Performance: Evidence from Osun State, Nigeria

The study examines the influence of strategic agility on small and medium enterprises’ (SMEs) performance with specific reference to SMEs operating in Osogbo metropolis, Osun State. Purposive sampling technique was employed to select SMEs engaging in manufacturing, trading, and service and agro-allied in Osogbo metropolis, Osun State, Nigeria, while snowball sampling technique was used to select 50 operators/managers each from the four sub-sectors totaling 200 respondents. A structured questionnaire was used to solicit information from the respondents. Data analysis was performed with the aid of Mean, Chi-Square, Pearson Correlation, and Ordinary Least Square method of estimation. The result reveals that strategic sensitivity, strategic response, leadership unit and resource fluidity independently have a significant influence on SMEs’ performance. Consequently, the study recommends that SME operators should have to increase their interest in all strategic agility dimensions due to their great role in achieving organizational performance excellence in the midst of a cut-throat competitive environment. Also, employees should be encouraged to participate in the strategic planning process and be creative.

Capturing spatiotemporal dynamics of Alaskan groundfish catch using signed-rank estimation for varying coefficient models

ABSTRACT Varying coefficient models (VCMs) are commonly used for their high degree of flexibility in modeling complex systems. Many applications in fisheries utilize VCMs to capture spatial variation in populations of marine fishes. All of these applications use the penalized least squares method for estimation. However, this approach is known to be sensitive to non-normal distributions and outliers, a common feature of ecological data. Robust estimation methods are more appropriate for handling noisy and non-normal data. We present the application of a signed-rank-based procedure for obtaining robust estimates in VCMs on a fisheries dataset from the North Pacific Ocean. We demonstrates that the signed-rank-based estimation method provides better fit and improved prediction in comparison to the classical likelihood VCM fits in both simulations and the real data application, particularly when the distributions are non-normal and may be misspecified. Rank-based estimation of VCMs is therefore valuable for modeling ecological data and obtaining useful inferences where non-normality and outliers are common.

Adoption of the National Health Insurance Scheme and Its Influence on Organizational Commitment

Purpose: The study examines the influence of the adoption of the National Health Insurance Scheme on organizational commitment with particular reference to Kwara State, Nigeria. 
 Method: A cross-sectional descriptive study was adopted for the study. A purposive sampling technique was employed to select 350 civil servants from the Ministry of Health in Ilorin. Data were analyzed with the assistance of mean and ordinary least square method of estimation. 
 Result: The results reveal that the adoption of the National Health Insurance Scheme (NHIS) has a significant influence on organizational commitment. This indicates that the “modus operandi” of the scheme is a strong predictor of organizational commitment in Nigeria. 
 Implication: Deduction to be made from this result is that the “modus operandi” of the scheme is a strong predictor of organizational commitment. This indicates that the sustainability of the NHIS is a guarantee in the country. This will pave the way to achieve Sustainable Development Goals (SDGs) of ‘universal health coverage, such as financial risk protection, access to quality essential health care services, and access to safe, effective, quality, and affordable essential medicines and vaccines for all by 2030.

Financial Literacy and Women Entrepreneurs’ Performance in Lagos State, Nigeria

Purpose: The study seeks to examine the influence of financial literacy on women entrepreneurs’ performance with particular reference to Lagos State, Nigeria. 
 Methods: A survey research design was employed for this study and a judgmental sampling technique was used to select 250 women entrepreneurs engaging in trading, teaching, fashion design, and agro-allied businesses. Mean, frequency, simple percentage, and least square method of estimation were used to analyze the data. 
 Results: The study establishes that financial literacy is a major determinant of women entrepreneurs’ performance. 
 Implications: The implication of this study is that if women entrepreneurs are equipped with an array of financial skills on income statement preparation, cash flow statement and cash budget preparation, the opening of a separate account for business, bookkeeping, internal control on cash, and daily cash reconciliation, they will be able to expand their businesses.

Does Trade Credit Spur Firm Performance? A Case Study in Vietnam

Purpose: The paper aims to examine the impacts of trade credit on firm performance in Vietnam, representing a small transition economy with high openness environment. Design/Methodology/Aproach: Generalized least squares method of estimation was used to test the hypotheses on a sample of 279 companies listed on Ho Chi Minh City Stock Exchange (HOSE) during the 2012-2018 period, after the global financial crisis. Findings: The research findings support the positive influences of trade credit on firm performance of large businesses through both accounts receivable and trade payables and reversal effects on small business. These results show the advantages of large-scale companies own over the smaller ones in acquiring financing resources and imposing market power on their business partners, which help them optimize the benefits of trade credit. Practical implications: Research results indicate that corporates should increase their business scale to capitalize on the benefits of trade credit, and small-scale businesses should control the cost of trade credit. Originality/Value: The paper contributes to the literature in three main ways. Firstly, our exclusive offers new insights into understanding the behavior of Vietnamese firms, and this would give implications for transition economies in the world. Secondly, the study was carried out in the post-crisis period, with regulatory changes in banking management. Thirdly, this research compensates for the lack of empirical evidence in this field of research.

Response of Nigerian Construction Industry to Economic Growth

The study assessed response of Nigerian Construction Industry to economic growth of Nigeria. The research was conducted using secondary data. The secondary data used was the National Account Dataset from 1981 to 2018 as 2010 constant price year. This was gotten from the Central Bank of Nigeria (CBN) publication reports. The response was evaluated through Impact propensity (IP), Finite Distributed Lag (FDL) and the Long Run Propensity (LRP). These parameters were calculated from the time series regression analysis using ordinary Least Square Method of estimation. The results show that the impact propensity of economic growth on construction is weak with correlation coefficient of -0.012. Delayed impact of economic growth on construction was observed with finite distributed lag of two year cycle. Maximum correlation coefficient of 1.265 with the economics of the preceding year (t-1) was observed. Long run propensity of 1.333 establishes a high growth propensity for construction industry given a one percent permanent GDP growth. Therefore, the study concluded that a consistent economic growth is desirable so as to achieve improved construction industry contribution to GDP.

Estimation of Informal Sector of the Nigerian Construction Industry

The study estimated the output of informal sector of the Nigerian Cement Industry through the consumption of cement by the Nigerian Construction industry. The research was conducted using secondary data. The study adopted the statistical model of informal sector estimation, Nigeria construction industry being cement intensive, cement consumption approach was used for the estimation of the informal sector of the industry by using annual cement consumption as an independent variable against the annual construction output in a time series regression analysis, treating the informal sector output as an omitted variable in the ordinary least square method of estimation. Annual value added tax (VAT) pool data set was chosen as an instrumental variable. Using the instrumental variable method of estimation, the informal sector proportion of the Nigeria construction industry was therefore estimated. The study concluded that the informal sector of the Nigerian construction industry is 4.07 percent of the industry's output.

Strategic Planning and Performance of Small Medium Enterprises: Evidence From Lagos State, Nigeria

This study examines the strategic planning and its effect on small and medium enterprises performance in Lagos state, Nigeria. Specifically, the study evaluates the level of SMEs operators’ involvement in strategic planning, determines the factors influencing SMEs to adopt strategic planning in their operations, examines the perceived contributions of strategic planning in SMEs Performance, identifies the challenges facing the implementation of strategic plan in SMEs and also examines the effect of strategic planning on SMEs performance. A survey of four hundred and seventy (470) Small and Medium Enterprises (SMEs) were randomly selected from one thousand nine hundred and sixty- five (1,965) that registered with the Ministry of Commerce and Industry in Lagos State. Data were sourced via a structured questionnaire, while analysis of data was performed with the aid of frequencies, percentages, factor analysis and ordinary least square method of estimation. Results reveal that the majority of SMEs operators do not aware of the strategic planning process in their respective business organizations and their enterprises did not prepare enough for the formulation and implementation of the strategic plan. Furthermore, results also reveal that organizational complexities, scarce firm resources, new technology and environment dynamics in business operations influenced their adoption to strategic planning, while the presence of an effective strategic plan could facilitate good performance of SMEs via better decisions, customer satisfaction, increased capacity, and identification of problems, chance of success, better solutions, competitive advantage, and market recognition. Results show that inadequate resources, lack of experts and difficult to align organizational culture and strategic plan are the major challenges facing the implementation of a strategic plan in SMEs. Subsequently, the study recommends that entrepreneurial development agencies, as well as the government of Nigeria, should organize training and seminar for SMEs operators on the introduction and formulation of strategic planning. Hence the SME operators will have a full understanding of the industry in which it operates so as to cut an edge for the enterprises. Keywords: Strategic Planning, SMEs, Organizational Complexities, Firm Resources, Environment Dynamics DOI: 10.7176/EJBM/12-8-02 Publication date: March 31 st 2020

Classical Estimation of the Index Spmk and Its Confidence Intervals for Power Lindley Distributed Quality Characteristics

The process capability index (PCI) has been introduced as a tool to aid in the assessment of process performance. Usually, conventional PCIs perform well under normally distributed quality characteristics. However, when these PCIs are employed to evaluate nonnormally distributed process, they often provide inaccurate results. In this article, in order to estimate the PCI Spmk when the process follows power Lindley distribution, first, seven classical methods of estimation, namely, maximum likelihood method of estimation, ordinary and weighted least squares methods of estimation, Cramèr–von Mises method of estimation, maximum product of spacings method of estimation, Anderson–Darling, and right-tail Anderson–Darling methods of estimation, are considered and the performance of these estimation methods based on their mean squared error is compared. Next, three bootstrap confidence intervals (BCIs) of the PCI Spmk, namely, standard bootstrap, percentile bootstrap, and bias-corrected percentile bootstrap, are considered and compared in terms of their average width, coverage probability, and relative coverage. Besides, a new cost-effective PCI, namely, Spmkc is introduced by incorporating tolerance cost function in the index Spmk. To evaluate the performance of the methods of estimation and BCIs, a simulation study is carried out. Simulation results showed that the maximum likelihood method of estimation performs better than their counterparts in terms of mean squared error, while bias-corrected percentile bootstrap provides smaller confidence length (width) and higher relative coverage than standard bootstrap and percentile bootstrap across sample sizes. Finally, two real data examples are provided to investigate the performance of the proposed procedures.

On the Alpha Power Transformed Power Inverse Lindley Distribution

In this paper, we introduce a new generalization of the power inverse Lindley distribution referred to as the alpha power transformed power inverse Lindley (APTPIL). The APTPIL model provides a better fit than the power inverse Lindley distribution. It includes the alpha power transformed inverse Lindley, power inverse Lindley and inverse Lindley as special sub models. Various properties of the APTPIL distribution including moments, incomplete moments, quantiles, entropy, and stochastic ordering are obtained. Maximum likelihood, maximum products of spacings, and ordinary and weighted least squares methods of estimation are utilized to obtain the estimators of the population parameters. Extensive numerical simulation is performed to examine and compare the performance of different estimates. Important data set is employed to show how the proposed model works in practice.

The Effect of International Financial Reporting Standards on the Association between Foreign Direct Investment and Economic Growth: Evidence from Selected Countries in Africa

The study aims at examining how IFRS adoption influences the relationship existing among foreign direct investment (FDI) and economic growth. The data consist of 12 developing economies that are the highest recipients of FDI in Africa, and the years of study are from 1996-2018. Using Ordinary Least Square and Generalized Least Square method of estimation, the result shows that IFRS is significantly positive to FDI. With FDI inflows in these countries, the result provides evidence that Non fully-IFRS adopted countries experience higher inflows of FDI than the fully-IFRS adopted countries. We find FDI inflows to also have positive influence on economic growth. The interaction of FDI and IFRS also influences economic growth positively when further analysis was carried on. The results provide evidence of positive relation among FDI, IFRS, and economic growth. IFRS adoption promotes FDI inflows which consequently spurs economic growth. There is, therefore, the need for policymakers to ensure adoption and enforcement of IFRS.

Short-term forecasting of renewable energy consumption: Augmentation of a modified grey model with a Kalman filter

One of the important global trends in near future is to replace fossil-fuel energy with sustainable energy. The accurate predictions of the renewable energy consumption are seemingly crucial in both national and international levels. In the context of a limited number of historical data, grey prediction system of single variable is one of primary choices for such prediction. Nonetheless, this seems rather sceptical when the dynamics of a system relies on solely one variable. This paper presents a novel approach based on a modification of multivariable grey prediction model whereby the influences of exogenous variables are taken into account. Furthermore, instead of employing the least square method for parameter estimation, states and parameters in our proposed method are sequentially estimated by means of the traditional Kalman filtering. The genetic algorithm is additionally supplemented in the Kalman filter step in order to justify some unknown noise statistics. To validate the effectiveness of the proposed scheme, it is employed to estimate and predict the renewable energy consumption in Thailand along with its associated factors using the data from 1990 to 2015. Compared with the multivariable grey model using the least square method for estimation of model parameters, the results show that the hybrid approach provides a better estimation and prediction performance.

THE DYNAMIC CORRELATION BETWEEN FISCAL SPENDING ON EDUCATION, HEALTH, CONSUMPTION AND STANDARD OF LIVING IN NIGERIA

The fiscal spending of the government have always been a strong instrument towards achieving development and recovering economy from recession. This paper investigates the long run and short run impact of three component of government expenditure (education, health, and consumption expenditure) on standard of living in Nigeria with time series data from 1981 to 2017. The study employs ordinary least square method of estimation on a range of equation models: Vector Error Correction Model (VECM) and the Impulse Responses Function Model. The result shows that fiscal spending on education, health, and consumption have a long run relationship with standard of living in Nigeria and the speed of adjustment towards long –run equilibrium is 61.45%, moderately high. The short run coefficient results reveals that education expenditure in both lag 1 &2 have a positive and significant impact on standard of living while health and consumption expenditure have insignificant impact on standard of living in Nigeria. Using Impulse Response Function model, we found that none of our fiscal spending variables (education expenditure, health and consumer spending) were able to emit positive impulses/shocks on the standard of living in Nigeria. The study recommends that government should ensure that fiscal spending on education, health, and consumption should be well managed, accounted for and the method should be transparent to the populace.