An empirical analysis of monetary and multidimensional poverty: evidence from a household survey in Pakistan

ABSTRACT

The present study computes multidimensional poverty and compares it with unidimensional estimates of poverty for the district of Mandi Bahuddin in the Punjab province of Pakistan for the years 2010 and 2014. By employing the Foster, Greer and Thorbecke (FGT) and Alkire-Foster Methods, the incidence, severity and depth of unidimensional and multidimensionality poverty was estimated. We found an increase in absolute and relative poverty levels in 2014 as compared to 2010. The multidimensional poverty in terms of household assets has also increased over time. However, the relative proportion of educational and health poverty towards MPI remains higher, thereby calling for a holistic approach to identify multidimensional poverty in the social sector. A comprehensive policy dossier needs to be framed for designing effective poverty alleviation and social welfare programmes in the Punjab, Pakistan.     

A Note On Beta Inverse-Weibull Distribution

The inverse Weibull distribution is one of the widely applied distribution for problems in reliability theory. In this article, we introduce a generalization—referred to as the Beta Inverse-Weibull distribution—generated from the logit of a beta random variable. We provide a comprehensive treatment of the mathematical properties of the Beta Inverse-Weibull distribution. The shapes of the corresponding probability density function and the hazard rate function have been obtained and graphical illustrations have been given. The distribution is found to be unimodal. Results for the non central moments are obtained. The relationship between the parameters and the mean, variance, skewness, and kurtosis are provided. The method of maximum likelihood is proposed for estimating the model parameters. We hope that this generalization will attract wider applicability to the problems in reliability theory and mechanical engineering.     

Poverty assessment as a multidimensional socio-economic concept: the case of the Rawalpindi region in Pakistan

The definition on poverty has progressed into a multidimensional concept focusing more on socio-economic dimensions than being a mere measure of financial deprivation. Corresponding to this advancement, this study investigated the incidence of multidimensional poverty (MDP) in the Rawalpindi region of Pakistan, taking into account three dimensions, i.e. education, health and housing. Findings revealed an inconsistent declining trend of MDP over time. This inconsistency was mainly attributed to observed fluctuations in deprivation levels of education, health and housing in the region. Over time, education deprivation showed a significant net increase. Notably, the magnitude of MDP in rural areas was higher than in urban areas.     

中沙关系回顾与展望

中国和沙特政治制度不同,但两国发展积极友好的关系没有障碍.目前,沙特是中国在西亚和非洲最大的贸易伙伴,两国经贸合作前景广阔.同时,中沙双方均奉行独立自主的外交政策,拥有良好的政治关系,未来在区域组织和联合国等国际舞台上将有更广泛的合作领域.     

The analysis of policy implementation models in higher education: the case study of Indonesia

This paper aims to analyse and understand the models of policy implementation in Indonesian state universities during the ongoing process of market-driven reforms and how academics respond to these models. The research undertaken was in the form of qualitative study using semi-structured interviews as instruments to collect data. Interviews were conducted with 30 academics in three state universities in Indonesia. The research demonstrated that policy implementation in Indonesian state universities takes largely a dialectical form which takes place both at macro and micro levels, suggesting a blended application of top-down and bottom-up approaches. The results of this study also confirmed that the interaction between policy and local systems plays an important role for the successful implementation of the policy. Indonesian academics perceived that each of these models has its strength and weaknesses particularly in relation to the aspect of collegiality. It is anticipated that the study will both contribute to a better understanding of the dynamics between governments as policy makers and academics as street level bureaucrats in the implementation of a policy, and offer guidance for policy makers in the formulation and enactment of relevant policies in higher education sectors both in Indonesia and other contexts implementing policy implementation.     

Compromise allocation in multivariate stratified surveys with stochastic quadratic cost function

In many real life situations the linear cost function does not approximate the actual cost incurred adequately. The cost of traveling between the units selected in the sample within a stratum is significant, instead of linear cost function. In this paper, we have considered the problem of finding a compromise allocation for a multivariate stratified sample survey with a significant travel cost within strata is formulated as a problem of non-linear stochastic programming with multiple objective functions. The compromise solutions are obtained through Chebyshev approximation technique, D ₁- distance and goal programming. A numerical example is presented to illustrate the computational details of the proposed methods.     

Using the Diffusion of Innovation Concept to Explain the Factors That Contribute to the Adoption Rate of E-journal Publishing

This paper reports on the factors that contribute to the adoption rate of e-journal publishing based upon responses from 82 Malaysian journal publishers. Drawing upon the theory of innovation diffusion, the study examines the role of awareness, three organization variables (publication size, age of the journal, and experience of editors), and attributes of e-journals (relative advantage, compatibility, complexity, trialability and observability) as influences to the rate of e-journal publishing adoption. Findings show that only two attributes—complexity and trialability—emerge as significant contributors to e-journal adoption rates, and all three organization variables—journal's age, publication size, and editorial experience—are significant. Collectively, these five significant variables explained 57.8% of the variance in adoption rate. We discuss the results and implication of the findings with respect to the wider context of e-journal publishing.     

Mixed ranked set sampling design

The main focus of agricultural, ecological and environmental studies is to develop well designed, cost-effective and efficient sampling designs. Ranked set sampling (RSS) is one method that leads to accomplish such objectives by incorporating expert knowledge to its advantage. In this paper, we propose an efficient sampling scheme, named mixed RSS (MxRSS), for estimation of the population mean and median. The MxRSS scheme is a suitable mixture of both simple random sampling (SRS) and RSS schemes. The MxRSS scheme provides an unbiased estimator of the population mean, and its variance is always less than the variance of sample mean based on SRS. For both symmetric and asymmetric populations, the mean and median estimators based on SRS, partial RSS (PRSS) and MxRSS schemes are compared. It turns out that the mean and median estimates under MxRSS scheme are more precise than those based on SRS scheme. Moreover, when estimating the mean of symmetric and some asymmetric populations, the mean estimates under MxRSS scheme are found to be more efficient than the mean estimates with PRSS scheme. An application to real data is also provided to illustrate the implementation of the proposed sampling scheme.     

A new bivariate exponential distribution for modeling moderately negative dependence

This paper introduces a new bivariate exponential distribution, called the Bivariate Affine-Linear Exponential distribution, to model moderately negative dependent data. The construction and characteristics of the proposed bivariate distribution are presented along with estimation procedures for the model parameters based on maximum likelihood and objective Bayesian analysis. We derive Jeffreys prior and discuss its frequentist properties based on a simulation study and MCMC sampling techniques. A real data set of mercury concentration in largemouth bass from Florida lakes is used to illustrate the methodology.     

Improved best linear unbiased estimators for the simple linear regression model using double ranked set sampling schemes

ABSTRACT

In this paper, we consider the best linear unbiased estimators (BLUEs) based on double ranked set sampling (DRSS) and ordered DRSS (ODRSS) schemes for the simple linear regression model with replicated observations. We assume three symmetric distributions for the random error term, i.e., normal, Laplace and some scale contaminated normal distributions. The proposed BLUEs under DRSS (BLUEs-DRSS) and ODRSS (BLUEs-ODRSS) are compared with the BLUEs based on ordered simple random sampling (OSRS), ranked set sampling (RSS), and ordered RSS (ORSS) schemes. These estimators are compared in terms of relative efficiency (RE), RE of determinant (RED), and RE of trace (RET). It is found that the BLUEs-ODRSS are uniformly better than the BLUEs based on OSRS, RSS, ORSS, and DRSS schemes. We also compare the estimators based on imperfect RSS (IRSS) schemes. It is worth mentioning here that the BLUEs under ordered imperfect DRSS (OIDRSS) are better than their counterparts based on IRSS, ordered IRSS (OIRSS), and imperfect DRSS (IDRSS) methods. Moreover, for sensitivity analysis of the BLUEs, we calculate REs and REDs of the BLUEs under the assumption of normality when in fact the parent distribution follows a non normal symmetric distribution. It turns out that even under violation of normality assumptions, BLUEs of the intercept and the slope parameters are found to be unbiased with equal REs under each sampling scheme. It is also observed that the BLUEs under ODRSS are more efficient than the existing BLUEs.