A new way to order independent components

A relatively newer computational technique adopted by statisticians is known as independent component analysis (ICA) which is used to analyze complex multidimensional data with the objective to separate it into components that are independent to each other. Quite often the main interest for conducting ICA is to identify a small number of significant independent components (ICs) to replace the original complex dimensions with. For this, determining the order of identified ICs is a pre-requisite. The area is not unaddressed but it does deserve a careful revisiting. This is the subject matter of the paper which introduces a new method to order ICs. The proposed method is based upon regression approach. It compares the magnitude of the mixing coefficients and regression coefficients of the regression of the original series on ICs. Their compatibility determines the order.     

A control chart for COM-Poisson distribution using a modified EWMA statistic

In this paper, a control chart has been developed for the Conway–Maxwell Poisson (COM-Poisson) distribution using the modified exponentially weighted moving average statistic. The proposed chart provides an efficient detection of smaller changes in the location parameter of the COM-Poisson distribution. The performance of the proposed control chart has been evaluated by the average and the standard deviation of the run length distribution for various parameters. Better detecting ability has also been compared with the existing control chart using EWMA statistic. Using simulation, we also showed the detecting ability over the traditional EWMA chart.     

Risk Communication for Empowerment: Interventions in a Rohingya Refugee Settlement

There are many reasons that people, when warned of an impending extreme event, do not take proactive, self-defensive action. We focus on one possible reason, which is that, sometimes, people lack a sense of agency or even experience disempowerment, which can lead to passivity. This article takes up one situation where the possibility of disempowerment is salient, that of Rohingya refugees who were evicted from their homes in Myanmar and forced to cross the border into neighboring Bangladesh. In their plight, we see the twin elements of marginalization and displacement acting jointly to produce heightened vulnerability to the risks from extreme weather. Building on a relational model of risk communication, a consortium of researchers and practitioners designed a risk communication training workshop that featured elements of empowerment-based practice. The program was implemented in two refugee camps. Evaluation suggests that the workshop may have had an appreciable effect in increasing participants' sense of agency and hope, while decreasing their level of fatalism. The outcomes were considerably more positive for female than male participants, which has important implications. This work underscores the potential for participatory modes of risk communication to empower the more marginalized, and thus more vulnerable, members of society.     

Efficient Estimation and Robust Inference of Linear Regression Models in the Presence of Heteroscedastic Errors and High Leverage Points

It is common for linear regression models that the error variances are not the same for all observations and there are some high leverage data points. In such situations, the available literature advocates the use of heteroscedasticity consistent covariance matrix estimators (HCCME) for the testing of regression coefficients. Primarily, such estimators are based on the residuals derived from the ordinary least squares (OLS) estimator that itself can be seriously inefficient in the presence of heteroscedasticity. To get efficient estimation, many efficient estimators, namely the adaptive estimators are available but their performance has not been evaluated yet when the problem of heteroscedasticity is accompanied with the presence of high leverage data. In this article, the presence of high leverage data is taken into account to evaluate the performance of the adaptive estimator in terms of efficiency. Furthermore, our numerical work also evaluates the performance of the robust standard errors based on this efficient estimator in terms of interval estimation and null rejection rate (NRR).     

Trade Liberalization and Child Labor: A Case Study of Pakistan

The boom in industrial sector has lead to many problems and child labor is no exception. This study explores the linkages between trade liberalization and child labor both in short and long-run. The results suggest that GDP per capita and income inequality increase the child labor in the long-run but these results disappear in short-run. The study also finds that income inequality has positive and significant impact on child labor. Our findings also support that trade openness along with trade sanctions (imposed by the developed countries) are associated with the reduction in child labor in Pakistan.     

Asymmetric impact of inflation and unemployment on poverty in Pakistan: new evidence from asymmetric ARDL cointegration

The current study is intended to examine the asymmetric impact of inflation and unemployment on the poverty of Pakistan over the period of 1970 to 2016 by applying asymmetric Autoregressive Distributed Lag (ARDL) cointegration approach. The results revealed the presence of long-run asymmetries among inflation, unemployment and poverty. These findings also confirmed the atypical reaction of poverty to negative and positive shocks in unemployment and inflation. Furthermore, findings also confirmed negative and significant association among health expenditures (HE), population growth and poverty. The findings of the study have relevant implications for policymakers interested in the asymmetric relationship among inflation, unemployment and poverty in Pakistan.     

Filtration of ASTA: a weak convergence approach

Consider a stochastic process (X,A), where X represents the evolution of a system over time, and A is an associated point process that has stationary independent increments. Suppose we are interested in estimating the time average frequency of the process X being in a set of states. Often it is more convenient to have a sampling procedure for estimating the time average based on averaging the observed values of X(T_n) (T_n being a point of A) over a long period of time: the event average of the process. In this paper we examine the situation when the two procedures—event averaging and time averaging—produce the same estimate (the ASTA property: Arrivals See Time Averages). We prove a result stronger than ASTA. Under a lack-of-anticipation assumption we prove that the point process, A, restricted to any set of states, has the same probabilistic structure as the original point process. In particular, if the original point process is Poisson the new point process is still Poisson with the same parameter as the original point process. We develop our results in the more general setting of a stochastic process (X,A), that is, a process with an imbedded cumulative process, A={A(t),t0}, which is assumed to be a Levy process with non-decreasing sample paths. This framework allows for modeling fluid processes, as well as compound Poisson processes with non-integer increments. First, we state the result in discrete time; the discrete-time result is then extended to the continuous-time case using limiting arguments and weak-convergence theory. As a corollary we give a proof of ASTA under weak conditions and a simple, intuitive proof of (Poisson Arrivals See Time Averages) under the standard conditions. The results are useful in queueing and statistical sampling theory.     

Urban growth management-the Saudi experience

Saudi Arabia experienced a high rate of urbanization during the period 1970–1986 resulting in accelerated annual growth rates for Saudi cities averaging more than 6.4%. Higher than usual growth rates created demand for the opening up of huge areas to meet housing, commercial, industrial and other land uses. Government's land grant policy and liberal interest free loans resulted in massive expansion of cities and towns all over the country with major cities of Riyadh, Jeddah, and Dammam having the biggest share. Lack of planning frameworks and weak city institutions could not direct the growth properly leading to sprawl and lop-sided development. This meant rapid extension of road network and utilities with high financial outlays. The slow-down in the economy and ever-increasing demand for infrastructure provision forced the government to initiate growth boundaries to tackle these problems in 1986. The paper discusses the methodology adopted and the process of devising urban limits and evaluates their impact on urban structures of Saudi cities. The paper draws some conclusions in the realization of objectives of the exercise with respect to, (a) control urban sprawl by encouraging infill development where utilities were generally available; (b) reduce cost of provision of infrastructure through better coordination tied to commonly agreed phasing; (c) maintain natural environment around the cities.     

The Role of Financial Development and Economic Misery on Life Expectancy: Evidence from Post Financial Reforms in India

Several survey studies have found that internal migrants report lower levels of happiness than locals, even after accounting for socio-economic factors. Traditional global self-ratings reveal that the migrant–local happiness-gap is also present in the data we present. The reasons for the migrant–local happiness-gap are as yet unclear. This paper aims to open this ‘black box’ by exploring the role of daily activities among a population that has generally been overlooked despite their high migration frequency: young adults. An innovative smartphone application is used that combines two techniques for multiple moment assessment: the experience sampling method and the day reconstruction method. Based on the application data, we examine whether internal migrants spend their time differently than locals and in which situations they feel noticeably less happy than locals. The data reveal that internal migrants distribute less time to happiness-producing activities such as active leisure, social drinking/parties, and activities outside home/work/transit. Internal migrants feel less happy than locals when spending time with friends and while eating. Possible explanations focusing on the role of social capital are discussed. Further analyses reveal that daily life experiences greatly enhance the explanation of the migrant–local happiness-gap. This paper demonstrates the potential value of real-time data and phone applications in solving happiness puzzles.     

Relationship Between Government Size and Trade Openness: Evidence from Pakistan

In this paper the effect of trade openness on government’s role in the economy is investigated in Pakistan using data for the period 1947–2009. The results demonstrate that there is a significant positive association between trade openness and government size. The explanation appears that as openness increases the size of government will inflate. This association is robust to the inclusion of a wide range of control variables and model specifications. The results support the compensation hypothesis and imply that government consumption plays a risk-reducing role in Pakistan. The empirical findings also highlight the role of other variables in determining the government size. Government size increases with income, democracy, foreign debt and investment, while it decreases with the increase in inflation and urbanization.