STOCHASTIC COST-VOLUME-PROFIT ANALYSIS WITH A LINEAR DEMAND FUNCTION

In this paper we incorporate a linear demand function to model the price-volume causal relationship into stochastic cost-volume-profit (CVP) analysis. We assume that the objective function is to maximize expected profit; other objective functions are also discussed and compared. A linear stochastic model follows from which probabilistic statements can be easily obtained if the random variables are assumed to be multivariate normal. The basic framework is shown to be a special case of project value maximization where project value is the cash flow of the project discounted for time and risk according to the capital asset pricing model. Moreover, an intertemporal extension that considers inventory is developed. In summary, a new approach to stochastic CVP analysis that incorporates the management decision process in an uncertain environment is developed.     

Widowhood,family size,and post-reproductive Mortality: a comparative Analysis of three populations in Nineteenth-Century Europe

Researchers from a number of disciplines have offered competing theories about the effects oJ childbearing on parents 'postreproductive longevity. The "disposable soma theory" argues that investments in somatic maintenance increase longevity but reduce childbearing. "Maternal depletion" models suggest that the rigors of childrearing increase mortality in later years. Other researchers consider continued childbearing a sign of healthy aging and a predictor of future longevity. Empirical studies have produced inconsistent and contradictory results. Our focus is on the experience of widowhood, which has been ignored in previous studies. We hypothesize that the death of a spouse is a stressful event with long-term consequences for health, especially for women with small children. Data are drawn from historical sources in Sweden, Belgium, and the Netherlands from 1766 to 1980. Postreproductive mortality was highest among young widows with larger families in all three samples. Age at last birth had little or no effect. We conclude that raising children under adverse circumstances can have long-lasting, harmful effects on a mother's health.     

Correlation in a Bayesian framework

The authors consider the correlation between two arbitrary functions of the data and a parameter when the parameter is regarded as a random variable with given prior distribution. They show how to compute such a correlation and use closed form expressions to assess the dependence between parameters and various classical or robust estimators thereof, as well as between p‐values and posterior probabilities of the null hypothesis in the one‐sided testing problem. Other applications involve the Dirichlet process and stationary Gaussian processes. Using this approach, the authors also derive a general nonparametric upper bound on Bayes risks.     

Learning from a lot: Empirical Bayes for high‐dimensional model‐based prediction

Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, stored in public repositories. We review applications of a variety of empirical Bayes methods to several well‐known model‐based prediction methods, including penalized regression, linear discriminant analysis, and Bayesian models with sparse or dense priors. We discuss “formal” empirical Bayes methods that maximize the marginal likelihood but also more informal approaches based on other data summaries. We contrast empirical Bayes to cross‐validation and full Bayes and discuss hybrid approaches. To study the relation between the quality of an empirical Bayes estimator and p, the number of variables, we consider a simple empirical Bayes estimator in a linear model setting. We argue that empirical Bayes is particularly useful when the prior contains multiple parameters, which model a priori information on variables termed “co‐data”. In particular, we present two novel examples that allow for co‐data: first, a Bayesian spike‐and‐slab setting that facilitates inclusion of multiple co‐data sources and types and, second, a hybrid empirical Bayes–full Bayes ridge regression approach for estimation of the posterior predictive interval.     

The influence of ‘topic and resource’ on some aspects of social theorising

Developments in sociological theory since the 1960s have been responses to disciplinary problems rather than changes in fashion. The problem of topic and resource—where sociology has to use everyday understandings and practices as study resources even though they are legitimate topics of enquiry—has been an important and sometimes neglected spur to many of these developments. The turn to discourse, conversation analysis and the rise of Bourdieu's reflexivity are all attempts to address the problem, but each is shown to be unsatisfactory in different ways. In summary, they seek to address the issue as requiring either a principled methodological or a principled theoretical solution, and neither approach is capable of comprehensively addressing the matter. It is argued that these ‘solutions’ depend, in turn, on one of two particular construals of what the ‘problem’ consists in, neither of which is necessary or coherent. Each, it is argued, depends on a philosophical trick: making language out to need formal improvement (the Bertrand Russell trick) or introducing inappropriate scepticism to everyday life (the René Descartes trick). It is suggested that treating topic and resource not as a problem but as something which opens up new areas of investigation successfully deflates the issue and avoids unnecessary theoretical and methodological contortions.     

Trust,Sexual Trust,and Sexual Health: An Interrogative Review

Trust is experienced almost constantly in all forms of social and interpersonal relationships, including sexual relationships, and may contribute both directly and indirectly to sexual health. The purpose of this review is to link three aspects of trust to sexual health: (1) the role of trust in sexual relationships; (2) the role of trust in sexually transmitted infection (STI) prevention, particularly condom use; and (3) the relevance of trust in sexual relationships outside of the traditional model of monogamy. The review ends with consideration of perspectives that could guide new research toward understanding the enigmas of trust in partnered sexual relations in the context of sexual and public health.     

Custom Epoch Estimation for Surveys

The paper provides a method for generating epoch estimates for time series survey data, allowing for different periods of time (or even point estimates) according to user demand. The method uses a modified kriging estimator, which suppresses the contribution of sampling error variability in order to guarantee that custom epoch estimates have an interpolation property. For the veteran population variable of the American Community Survey, we utilize a simple Brownian Motion model of the population process and derive the modified kriging estimator for this case. The tuning parameters of this population model can be calibrated to the data via simple formulas. We illustrate the application of this method to the generation of point estimates of veteran population, an important objective for Veterans Affairs.