A Child Labour Estimator: A Case of Bahawalpur Division

Social Indicators Research - Child labor is a distressing issue. There have been many attempts to estimate its magnitude. It is attempted here to develop an estimator to assess the magnitude of...     

EWMA and DEWMA repetitive control charts under non-normal processes

In this paper, we present a repetitive sampling method to construct control charts using exponentially weighted moving averages (EWMA) and double exponentially weighted moving averages (DEWMA) to monitor shift in the process. For non-normal processes, t-distribution with various degrees of freedom (i.e. df=4,10,20,40,50) is used as symmetric distribution, gamma distribution with unit scale parameter and various shape parameters (i.e. 0.5,1,2,3,4) is used as positively skewed distribution and Weibull distribution with unit scale parameter and various shape parameters (i.e. 10 and 20) is used as negatively skewed distribution. We use Monte Carlo simulations to check whether the process is out of control. We use average run length as a tool to find the ability of proposed control charts to identify a shift earlier in a process, as compared to other control charts currently used to monitor the same type of process. The proposed control charts are applied to two real datasets.KEYWORDS: Control charts, EWMA statistic, DEWMA statistic, t distribution, gamma distribution, Weibull distribution     

Islamic Religious Organizations Across Borders: The Case of the Pakistani Migrant Muslim Community in Korea (South)

With the formation of small migrant communities in foreign lands, some religious organizations migrate along with the migrants and play a part in shaping and reshaping the socio-religious experiences of respective migrants. This paper looks into how Islamic religious organizations have been established in South Korea; how the socio-religious experience of the Pakistani Muslim minority community in Korea is mediated by these organizations; and what is the impact of this mediation on the daily socio-religious lives of the migrants. Two Islamic religious organizations—Dawat-e-Islami and Minhaj-ul-Quran—have been discussed here which originated in Pakistan and have been working around the world including Korea. Using the conceptual framework of social capital, we elaborate on three stages for establishment and working of these religious institutions: deployment of social capital for initiation; reinforcement of social capital for establishment; and sustenance with social capital over a course of time. This paper proposes that these religious organizations are established by the migrant community because of the social capital created within, as opposed to any master plan from the respective parent organizations in the country of origin. Further, these organizations become connected to mainstream organizations as a result of community efforts.     

Does Nominal Devaluation Precede Real Devaluation? The Case of The Philippines

This paper attempts to examine the link between nominal devaluation and real devaluation with special reference to the Philippines. In doing so, we have used log linear relationship between the variables and have employed some sophisticated tests such as Ng–Perron unit root test, autoregressive distributive lag model, and dynamic ordinary least squares test for the long run correlation. The findings of the study with the Philippino quarterly data suggest that not only in the long run, but also in the short run, nominal devaluation leads to real devaluation.

EXPONENTIAL SMOOTHING AND NON‐NEGATIVE DATA

The most common forecasting methods in business are based on exponential smoothing, and the most common time series in business are inherently non‐negative. Therefore it is of interest to consider the properties of the potential stochastic models underlying exponential smoothing when applied to non‐negative data. We explore exponential smoothing state space models for non‐negative data under various assumptions about the innovations, or error, process. We first demonstrate that prediction distributions from some commonly used state space models may have an infinite variance beyond a certain forecasting horizon. For multiplicative error models that do not have this flaw, we show that sample paths will converge almost surely to zero even when the error distribution is non‐Gaussian. We propose a new model with similar properties to exponential smoothing, but which does not have these problems, and we develop some distributional properties for our new model. We then explore the implications of our results for inference, and compare the short‐term forecasting performance of the various models using data on the weekly sales of over 300 items of costume jewelry. The main findings of the research are that the Gaussian approximation is adequate for estimation and one‐step‐ahead forecasting. However, as the forecasting horizon increases, the approximate prediction intervals become increasingly problematic. When the model is to be used for simulation purposes, a suitably specified scheme must be employed.     

Female Entrepreneurship and the Metanarrative of Economic Growth: A Critical Review of Underlying Assumptions

This critical review of the literature on female entrepreneurship problematizes the metanarrative of economic growth and the mechanisms through which it both operates and is maintained. Central to this is the axiomatic ‘underperformance hypothesis’, which states that ‘all else being equal, female entrepreneurs tend to be less successful than their male counterparts in terms of conventional economic performance measures’ (Du Rietz and Henrekson (2000, p. 1). As an axiom, the truth of the ‘underperformance hypothesis’ is taken for granted, and thus it invisibly serves as a starting point, delimiter and interpretive lens for analysis in this field. While it remains invisible, the hypothesis will continue to reproduce the differences between male and female entrepreneurs, and thus the subordination of women to men in the realm of entrepreneurship. The review illustrates how, by associating females with underperformance, the persistent influence of the metanarrative of economic growth has been masked and the image of the female entrepreneur as problematic and inferior to her male counterpart has been reinforced. The authors argue that a postmodern feminist epistemology will destabilize both the metanarrative of economic growth, and the axiomatic ‘underperformance hypothesis’ it supports, thus opening up space for a heterogeneous understanding of (female) entrepreneurship. By questioning accepted knowledge about female entrepreneurs, the review sets the platform for the exploration of new research questions and a broad agenda for future research. Such an agenda is crucial in order to move future research beyond the pervasive influence of the metanarrative of economic growth and its attendant underperformance hypothesis.     

On designing new optimal synthetic Tukey’s control charts

Tukey’s control chart is generally used for monitoring the processes where the measurement process physically damages the product. It is based on single observation and robust to outliers. In this paper, two optimal synthetic Tukey’s control charts are proposed by integrating the conforming run length chart with the Tukey’s control chart and its modification. The performance comparison of the proposed charts with the existing Tukey’s control charts is made by using out-of-control average run length and extra quadratic loss as performance metrics. The proposed charts offer better protection against the process shifts as compare to the existing Tukey’s control charts when the underlying process distribution is symmetric or asymmetric. Simulation studies also establish the supremacy of the proposed control charts over the existing Tukey’s control charts. In the end, an illustrative example based on a real data set of the combined cycle power plant is provided for practical implementation.     

A power log-Dagum distribution: estimation and applications

Development and application of probability models in data analysis are of major importance for all sciences. Therefore, we introduce a new model called a power log-Dagum distribution defined on the entire real line. The model contains many new sub-models: power logistic, linear log-Dagum, linear logistic and log-Dagum distributions among them. Some properties of the model including three different estimation procedures are justified. The model exhibits various shapes for the density and hazard rate functions. Moreover, the estimation procedures are compared using simulation studies. Finally, the model with others are fitted to three data sets, and it shows a better fit than the compared distributions defined on the real line.     

Approximate Bayesian analysis of doubly censored samples from mixture of two Weibull distributions

The purpose of the paper is to estimate the parameters of the two-component mixture of Weibull distribution under doubly censored samples using Bayesian approach. The choice of Weibull distribution is made due to its (i) capability to model failure time data from engineering, medical and biological sciences (ii) added advantages over the well-known lifetime distributions such as exponential, Raleigh, lognormal and gamma distribution in terms of flexibility, increasing and decreasing hazard rate and closed-form distribution function and hazard rate. The proposed two-component mixture of Weibull distribution is even more flexible than its conventional form. However, the estimation of the parameters from the proposed mixture is more complex. Further, we have assumed couple of loss functions under non informative prior for the Bayesian analysis of the parameters from the mixture model. As the resultant Bayes estimators and associated posterior risks cannot be derived in the closed form, we have used the importance sampling and Lindley’s approximation to obtain the approximate estimates for the parameters of the mixture model. The comparison between the performances of approximation techniques has been made on the basis of simulation study and real-life data analysis. The importance sampling is found to be better than Lindley’s approximation as it gives better estimation for shape and mixing parameters of the mixture model and computations under this technique are much easier/shorter than those under Lindley’s approximation.     

The Performance of Gaussian and non Gaussian dynamic models in assessing market risk: The Implications for risk management

The developing markets are more volatile, unstable illiquid, and more prone to the external shocks. The non Gaussian VaR model gives more accurate risk models than Gaussian VaR models. Hence, the purpose of this study is to test if and how non Gaussian VaR models are comparatively better fit for risk modeling of developing markets than the Gaussian VaR models. The study measures the market risk for the daily closing price of Karachi Stock Exchange 100 index over the period of 2004–2016. The evaluation of VaR models suggests that non Gaussian dynamic model outperformed the Gaussian VaR models in developing markets.