The impact of India’s food security policy on domestic and international rice market

Food security policy making in India is at crossroads. India has emerged as a leading rice exporter. The Government of India has introduced the National Food Security Act which requires 33.6 million tons of rice per year for its public food distribution system. In this study, we modeled India’s rice market and analyzed policy implications of the long-term impact of India’s food security act on domestic and international rice market. We developed a structural economic demand and supply model for India’s rice market and further added subsidy equations to trace the consequence of National Food Security Act on domestic rice consumption and on the international market. We specifically focus on three different scenarios: subsidy as price effect, subsidy as inelastic income effect, and subsidy as elastic income effect under the broader framework of National Food Security Act. We found that at the end of the projection period (2024–2025), as a result of rice subsidy program, the consumption of rice increases significantly in the case of price effect while the inelastic income effect has no or less impact on production, consumption, and export of rice. Hence, the policy implication of our study is that if the objective of the National Food Security Act is to increase consumption then it needs to be implemented as price effect.     

Data aggregation for <Emphasis Type="Italic">p</Emphasis>-median problems

In this paper, we use a pseudo-Boolean formulation of the p-median problem and using data aggregation, provide a compact representation of p-median problem instances. We provide computational results to demonstrate this compactification in benchmark instances. We then use our representation to explain why some p-median problem instances are more difficult to solve to optimality than other instances of the same size. We also derive a preprocessing rule based on our formulation, and describe equivalent p-median problem instances, which are identical sized instances which are guaranteed to have identical optimal solutions.     

Laws of large numbers for bootstrappedU-statistics

For the bootstrapped mean, a strong law of large numbers is obtained under the assumption of finiteness of the rth moment, for some r>1, and a weak law of large numbers is obtained under the finiteness of the first moment. The results are then extended to bootstrapped U-statistics under parallel conditions. Stochastic convergence of the jackknifed estimator of the variance of a bootstrapped U-statistic is proved. The asymptotic normality of the bootstrapped pivot and the bias of the bootstrapped U-statistic are indicated.     

Proportional hazards models: a latent competing risk approach

We propose a novel semiparametric version of the widely used proportional hazards survival model. Features include an arbitrarily rich class of continuous base-line hazards, an attractive epidemiological interpretation of the hazard as a latent competing risk model and trivial handling of censoring. Models are fitted by using a data augmentation scheme. The methodology is applied to a data set recording times to first hospitalization following clinical diagnosis of acquired immune deficiency syndrome for a sample of 169 patients.     

The use of the weighted likelihood in the natural exponential families with quadratic variance

The authors propose a weighted likelihood concept for the estimation of parameters in natural exponential families with quadratic variance. They apply the results to both simulated and real data.     

Competition and Sustainability: The Impact of Consumer Awareness

Sustainability, a broad concept that includes numerous environmental and social dimensions, has emerged as an important product evaluation criterion for consumers. We suggest the impact of sustainability on consumer behavior depends on two factors—each individual consumer's unique level of concern about sustainability, and the general level of awareness regarding the sustainability of competing products—that together determine the level of heterogeneity among consumer attitudes toward sustainability. We incorporate sustainability concern and awareness into a model of horizontal competition in a duopoly, where one firm's product is more sustainable than the other's. Our results suggest that marginal increases in awareness can benefit all firms, including the less sustainable one, when awareness is sufficiently high (the explicit goal of recent sustainability labeling initiatives). In several model extensions, we provide additional insights for the following cases: the sustainable firm controls the extent of its sustainability advantage, the sustainable firm can directly influence the general level of awareness, and the distribution of sustainability concern across consumers is nonuniform. Our results enable us to suggest several new insights for managers, both those whose products enjoy a sustainability advantage and those whose products do not.     

A continuous repeated measurements model:the experimental design problem with fixed time constraints

A repeated measurements model where the within-subject response is modeled as a continuous time regression is analyzed using reproducing kernel Hilbert space methods, Parzen (1961). The basic goal is to study the statistical design problem when experimental units and measurements are "free", but the total measurement time is fixed. This kind of situation arises when the experiment uses scarce resources such as space or oceanographic platforms or a magnetic resonance imaging (MRI) device. In this situation the only constraint is the total time allocated to the experiment.     

A study of the Gamma-Pareto (IV) distribution and its applications

ABSTRACT

Pareto distributions and their close relatives and generalizations provide very flexible families of heavy-tailed distributions that may be used to model income distributions as well as a wide variety of other social and economic distributions. On the other hand, gamma distribution has a wide application in various social and economic spheres such as survival analysis, to model aggregate insurance claims, and the amount of rainfall accumulated in a reservoir etc. Combining the above two heavy-tailed distributions, using the technique by Alzaatreh et al. (2012 Alzaatreh, A., Famoye, F., Lee, C. (2012). Gamma-Pareto distribution and its applications. J. Modern Appl. Stat. Methods. 11:78–94.[Crossref] , [Google Scholar]), we define a new distribution, namely Gamma-Pareto (IV) distribution, hereafter called as GPD^(IV) distribution. Various properties of the GPD^(IV) are investigated such as limiting behavior, moments, mode, and Shannon entropy. Also some characterizations of the GPD^(IV) distribution are mentioned in this paper. Maximum likelihood method is proposed for estimating the model parameters. For illustrative purposes, real data sets are considered as applications of the GPD^(IV) distribution.     

Using observed confidence levels to perform principal component analyses

ABSTRACT

This paper focuses on applying the method of observed confidence levels to problems commonly encountered in principal component analyses. In particular, we focus on assigning levels of confidence to the number of components that explain a specified proportion of variation in the original data. Approaches based on the normal model as well as a non parametric model are explored. The usefulness of the methods are discussed using an example and an empirical study.