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.     

Dynamics of Current Account Deficit: A Lesson from Pakistan

This study investigates the determinants of the current account deficit in Pakistan by using the annual time series data for the period from 1976 to 2010. The cointegration results suggest the positive and significant long run relationship of the current account deficit with the exchange rate, trade deficit and fiscal deficit while a significant negative relationship is found with external debt and private saving. The error correction model also confirms the significant positive relationship of the current account deficit with trade deficit and fiscal deficit in the short run. The Granger-causality test shows the bidirectional causal relationship of exchange rate and external debt with current account deficit. While, unidirectional causality is found from current account deficit to trade deficit and private savings. It is recommended that the government needs to be cautious in financing its fiscal deficit. Savings habits should be increased to narrow the investment gap in economy.     

Ethnic Resurgence,Minority Communities,and State Policies in a Network Society: The Dynamics of Malay Identity Formation in Postcolonial Singapore

While much has been written about identity formation and the politics of ethnicity among minority communities in various parts of modern-day Southeast Asia, the same cannot be said regarding the Malay community of Singapore. This article seeks to address this scholarly neglect by bringing into sharp focus the dynamics, processes, and circumstances that shaped Malay identity in postcolonial Singapore during the 1980s. By interweaving historical data with theoretical insights derived from the works of Andrew Willford, Manuel Castells, and Richard Jenkins, among others, this article provides an analytical reading of the global, regional, and local developments that brought about an ethnic resurgence within one of the largest minority groups in this island city-state. Such developments prompted the Singapore government to devise new laws and employ multi-faceted strategies to regain its legitimacy in the eyes of a certain segment of the population, and to enhance its ruling capacity. The problematics embedded within the state's interpretation of Malay identity and the effects of citizen resistance against state policies are considered in detail in the final sections of this article.     

Effect of outgroup social categorization by host-country nationals on expatriate premature return intention and buffering effect of mentoring

Outgroup social categorization by host-country nationals (HCNs) is a common challenge for expatriates and it has received inadequate scholarly attention in expatriate research. This study explores how outgroup social categorization affects expatriate intention to terminate international assignments prematurely and how this adversity can be lessened through organizational mentoring interventions. We theorize that outgroup social categorization by HCNs results in social isolation for expatriates, which triggers expatriates' early return intentions, and mentoring mitigates this indirect effect. The hypotheses were supported by the analyses of multisource data collected from expatriates and their local co-workers in multinational enterprises operating in China. Theoretical and practical implications of the research findings are discussed.     

Estimation in a competing risks proportional hazards model under length-biased sampling with censoring

What population does the sample represent? The answer to this question is of crucial importance when estimating a survivor function in duration studies. As is well-known, in a stationary population, survival data obtained from a cross-sectional sample taken from the population at time $t_0$ represents not the target density $f(t)$ but its length-biased version proportional to $tf(t)$ , for $t>0$ . The problem of estimating survivor function from such length-biased samples becomes more complex, and interesting, in presence of competing risks and censoring. This paper lays out a sampling scheme related to a mixed Poisson process and develops nonparametric estimators of the survivor function of the target population assuming that the two independent competing risks have proportional hazards. Two cases are considered: with and without independent censoring before length biased sampling. In each case, the weak convergence of the process generated by the proposed estimator is proved. A well-known study of the duration in power for political leaders is used to illustrate our results. Finally, a simulation study is carried out in order to assess the finite sample behaviour of our estimators.     

Mean and sensitivity estimation of a sensitive variable through additive scrambling

Abstract

This article focuses on reducing the additional variance due to randomization of the responses. The idea of additive scrambling and its inverse has been used along with (i) split sample approach and (ii) double response approach. Specifically, our proposal is based on Gupta et al. (2006) randomized response model. We selected this model for improvement because it provides estimator of mean and sensitivity level of a sensitive variable and is better than all of its competitors proposed earlier to it and even Gupta et al. (2006) sensitivity estimator is better than that of Gupta et al. (2010). Our suggested estimators are unbiased estimators and perform better than Gupta et al. (2006) estimator. The issue of privacy protection is also discussed.     

Maximum likelihood estimation of variance components of heteroscedastic random anova model

the estimation of variance components of heteroscedastic random model is discussed in this paper. Maximum Likelihood (ML) is described for one-way heteroscedastic random models. The proportionality condition that cell variance is proportional to the cell sample size, is used to eliminate the efffect of heteroscedasticity. The algebraic expressions of the estimators are obtained for the model. It is seen that the algebraic expressions of the estimators depend mainly on the inverse of the variance-covariance matrix of the observation vector. So, the variance-covariance matrix is obtained and the formulae for the inversions are given. A Monte Carlo study is conducted. Five different variance patterns with different numbers of cells are considered in this study. For each variance pattern, 1000 Monte Carlo samples are drawn. Then the Monte Carlo biases and Monte Carlo MSE’s of the estimators of variance components are calculated. In respect of both bias and MSE, the Maximum Likelihood (ML) estimators of variance components are found to be sufficiently good.     

Optimal designing of an SkSP-R double sampling plan

In this article, we propose a method of planning and determining the optimum parameters of a SkSP-R skip-lot sampling plan by using the attribute double sampling plan as the reference plan. The SkSP-R plan is a new type of skip-lot sampling plan which has a provision for re-inspecting the submitted lots. The optimal plan parameters of the suggested sampling plan are estimated with the target that the average sample number be minimized and satisfying both the specified producer's as well as the consumer's risks simultaneously. In order to obtain the optimum parameters, tables are also built for different combinations of the acceptable quality level and the limiting quality level in conjunctions with different producer's and consumer's risks. An illustrative example is provided for the implementation of the suggested plan. The advantages of the suggested plan over the existing conventional sampling plans and other existing skip-lot sampling plans are also described.     

On using non identical and independent Bernoulli trials in human surveys

Unlike the usual randomized response techniques, as a pioneering attempt, this article focuses on using non identical independent Bernoulli trials in sensitive surveys. For this purpose, a general class of randomized response techniques is considered. The usual randomized response techniques are based on a fixed probability of having a yes answer. Contrary to usual techniques, in the proposed technique every respondent has a different probability of reporting a yes answer. With this setting, in most of the situations, the proposed technique is observed performing better in terms of variability. To illustrate and support the superiority of the proposed technique it is compared with models such as Warner (1965), Greenberg et al. (1969), Mangat and Singh (1990), and Mangat (1994) using identical Bernoulli trials. Relative efficiency and privacy protection are studied in detail using Warner (1965) and Mangat (1994) models.