A general class of non parametric tests for comparing scale parameters

In this paper, a general class of non parametric tests is proposed for the two-sample scale problem. Testing of the scale parameter is very useful in real-life situations commonly faced in engineering, trade, cultivation, industries, medicine, etc. In all these fields, one will prefer the method that gives more consistent results. Thus, it is worthwhile to test the equality of scale parameters. The distribution of the proposed test is established. To assess the performance of the proposed test, the asymptotic efficacies are studied for some underlying distributions and the results are interpreted with useful information. To see the working of the proposed test, an illustrative example for the real-life data set is provided. The simulation study is also carried out to find the asymptotic power of the proposed test. An extension of the general class of tests to the multiple-sample problem is also discussed.     

Analyzing Social Media Engagement and its Effect on Online Product Purchase Decision Behavior

The continuous progress of society in using online resources has given opportunity to many business executives to utilize social media for their brand promotion or recognition. Organizations utilize social media sites like Twitter, Facebook, LinkedIn, Flicker, Google Plus, and YouTube to promote their product, service, or brand worldwide. Increase of consumer engagement in online social activities has forced companies to integrate social media factors into their marketing strategy. The objective of this study is to find the important factors on which the online purchasing decision depends, based on the personality types of consumers and their attitude toward social media with brand perception.     

Food subsidy,income transfer and the poor: A comparative analysis of the public distribution system in India's states

The Targeted Public Distribution System (TPDS) – the largest food subsidy program in India – has been a dismal failure in targeting the poor. The present paper examines its performance in three Indian states – Andhra Pradesh, Maharashtra and Rajasthan, based on primary data collected for this study. As real income transfers through food price subsidies are a tiny fraction of expenditure per person under this scheme, a contribution of the present study is to model determinants of real income transfers through subsidised wheat, rice and sugar. The analysis throws new light on how income transfers vary with economic status of a household, inequality in the distribution of land in a village, amount of food price subsidy, transaction costs of buying from ‘fair price shops’ (FPS), and supply shortages. The policy implications of these results are profound. Desperate measures such as a universal food subsidy enshrined in a proposed National Food Security Act are rejected on the grounds that the enormous leakages and wastage under the present TPDS would only get worse. Assertions that a universal food subsidy is the only option consistent with the right to food are rejected as mistaken. Instead, it is worthwhile to overhaul the PDS within the existing outlay.     

Prevalence of job strain among Indian foundry shop floor workers

Global competition in manufacturing sector demand higher productivity levels. In this context, workers in this sector are set with high output targets, leading to job strain. In addition to the strain, hazardous conditions also prevail in some of the manufacturing processes like foundry activities. This paper attempts to appraise the prevalence of job strain among foundry shop floor workers in India with the help of Demands-Control model [8]. In this study, data was collected through a survey using 49-item Job Content Questionnaire (JCQ) [9], a widely used and well-validated test for job strain. Then the data was subjected to statistical analysis after ascertaining the reliability. This survey has revealed that 25% of workers in foundry were experiencing high job strain. Hazardous working conditions, limited decision making authority, etc. appear to be the main contributing factors for the higher levels of strain.     

Spatial Sampling Design for a Demographic and Health Survey

The recent advances in global position systems (GPS), geographic information systems (GIS), and remote sensing (RS) can be exploited for spatial sampling design for demographic and health surveys. These technologies are particularly useful when a sampling frame is unavailable and/or location (of household) is important for data collection (e.g., location of residence might greatly impact exposure to ambient air pollution among members of a population). Building on these technologies, this article presents a methodology of spatial sampling adopted for the respiratory health and demographic survey conducted in Delhi and its environs from January through April 2004. The overall goal of the survey was to select households that adequately represented exposure to ambient air pollution. The proposed methodology involved constructing a sampling frame of residential areas and the simulation of weighted random points within residential areas. The simulated locations were navigated with the aid of GPS to identify households at these locations and to acquire residents’ consent to participate in the survey; a total of 1,576 households at the 2,000 simulated locations were found suitable and participated in the survey. The average ambient air pollution at the sample sites was not significantly different from the average air pollution observed in the study area, which demonstrates the robustness of the proposed sampling method.     

GROUP INEQUALITY

We explore the combined effect of segregation in social networks, peer effects, and the relative size of a historically disadvantaged group on the incentives to invest in market‐rewarded skills and the dynamics of inequality between social groups. We identify conditions under which group inequality will persist in the absence of differences in ability, credit constraints, or labor market discrimination. Under these conditions, group inequality may be amplified even if initial group differences are negligible. Increases in social integration may destabilize an unequal state and make group equality possible, but the distributional and human capital effects of this depend on the demographic composition of the population. When the size of the initially disadvantaged group is sufficiently small, integration can lower the long‐run costs of human capital investment in both groups and result in an increase the aggregate skill share. In contrast, when the initially disadvantaged group is large, integration can induce a fall in the aggregate skill share as the costs of human capital investment rise in both groups. We consider applications to concrete cases and policy implications.     

The Assets Agenda and Social Policy

The assets agenda or asset-based welfare has provoked much interest in recent times. This approach insists that the stock of assets that a person owns is an important element of well-being. The assets agenda is not a unified body of thought. However, there is a common failure to distinguish between these different parts, and this clouds rather than clarifies debates. This article seeks to add analytical clarity to current debates about asset-based welfare. I distinguish between social policy and citizenship, and consider their implications for social policy. This discussion is important because analytical clarity is a precondition for a balanced assessment of asset-based welfare.     

Estimation of smooth regression functions in monotone response models

We consider the estimation of smooth regression functions in a class of conditionally parametric co-variate-response models. Independent and identically distributed observations are available from the distribution of (Z,X)$(Z,X)$, where Z is a real-valued co-variate with some unknown distribution, and the response X conditional on Z   is distributed according to the density p(·,ψ(Z))$p(·,\psi (Z))$, where p(·,θ)$p(·,\theta )$ is a one-parameter exponential family. The function ψ$\psi$ is a smooth monotone function. Under this formulation, the regression function E(X|Z)$E(X|Z)$ is monotone in the co-variate Z   (and can be expressed as a one–one function of ψ$\psi$); hence the term “monotone response model”. Using a penalized least squares approach that incorporates both monotonicity and smoothness, we develop a scheme for producing smooth monotone estimates of the regression function and also the function ψ$\psi$ across this entire class of models. Point-wise asymptotic normality of this estimator is established, with the rate of convergence depending on the smoothing parameter. This enables construction of Wald-type (point-wise) as well as pivotal confidence sets for ψ$\psi$ and also the regression function. The methodology is extended to the general heteroscedastic model, and its asymptotic properties are discussed.