AD HOC MODEL BUILDING USING TIME-VARYING PARAMETER MODELS*

Decision support for managers and policy makers, such as required in planning and evaluation efforts, often requires ad hoc behavioral modeling to account for context-specific phenomena and to handle data limitations. This paper introduces a systematic approach useful for meeting these requirements in which time-varying parameter estimation plays an important role. A case study evaluating the impacts of public policy actions on residential natural gas conservation illustrates the approach.     

Applications and Implementation DECISION SUPPORT SYSTEMS: AN EMPIRICAL ASSESSMENT FOR DECISION MAKING

A laboratory experiment examined the effects of applying decision support system (DSS) technology to decision making in ill-structured problem environments under varying information conditions. Marketing executives participated in the experiment which investigated the effects of DSS availability, DSS training, and data availability on dependent variables that included: (1) the number of alternatives considered by a subject during decision making, (2) the period of time spent by a subject to complete the decision-making process, (3) the subject's perceived confidence in the decisions he or she had made, (4) the amount of data considered by a subject's during decision making, (5) the individual subject's decision processing, and (6) the subject's performance overall. Our results indicate that all three factors significantly affect the number of alternatives considered by subjects during the decision-making process. We therefore suggest that DSS training be coordinated with decision training in order to realize the potential of DSSs as described in the DSS literature.     

ON MODELING ADVERTISING PULSING DECISIONS

Based on empirical findings in the literature, sales response to advertising pulsing policy (APP) is modeled mathematically. The implications for APP are discussed. This policy is compared with an alternative policy of uniform expenditures (UAP), a commonly used strategy. The results of the research indicate that substantial savings in advertising budget or an increase in sales revenues may be achieved for a firm using APP.     

Nonlinear models of disability and age applied to census data

It is usually considered that the proportion of handicapped people grows with age. Namely, the older the man/woman, the more the level of disability he/she suffers. However, empirical evidence shows that this assessment is not always true, or at least, it is not true in the Spanish population. The study tries to assess the impact of age on disability in Spain. Each gender has been treated separately because it can be shown that men and women have their own pattern of behaviour. Three different methods of estimation have been used to check the link between those variables. The results seem to support the idea that the relationship among age and the intensity of disability is not always direct. One of the concluding remarks in this analysis is that the method of estimation has a great incidence in the final results, especially in central ages between 20 and 80 years old.     

Bayesian unit-root tests for Stochastic Volatility models

In this article, we consider Bayesian inference procedures to test for a unit root in Stochastic Volatility (SV) models. Unit-root tests for the persistence parameter of the SV models, based on the Bayes Factor (BF), have been recently introduced in the literature. In contrast, we propose a flexible class of priors that is non-informative over the entire support of the persistence parameter (including the non-stationarity region). In addition, we show that our model fitting procedure is computationally efficient (using the software WinBUGS). Finally, we show that our proposed test procedures have good frequentist properties in terms of achieving high statistical power, while maintaining low total error rates. We illustrate the above features of our method by extensive simulation studies, followed by an application to a real data set on exchange rates.     

Ackoff's Fables revisited: stories to inform operational research practice

This paper considers Ackoff's Fables, a set of short stories published by Ackoff in 1978 as guides to creative problem solving. The paper argues that storytelling of this kind contributes usefully to management and MS/OR education, before addressing how such Fables might be interpreted. It is demonstrated, using one of Ackoff's Fables, The Smart Jackass, for illustrative purposes, that interpretation of even apparently straightforward stories such as these is not unambiguous. The Fables can be interpreted in a multitude of different and sometimes contradictory ways, and the truths they might contain are not self-evident. Yet, as the basis for discussion, they still have much to offer as educational tools. The paper concludes with a discussion of literal truth in stories, and presents a classification of story types according to their relationship to literal truth.     

Smooth goodness of fit tests for the weibull distribution with singly censored data

The smooth goodness of fit tests are generalized to singly censored data and applied to the problem of testing Weibull (or extreme value) fit. Smooth tests, Pearson-type tests, and the spacings tests proposed by Mann, Schemer, and Fertig (1973) are compared on the basis of local asymptotic relative efficiency with respect to the asymptotic best test against generalized gamma alternatives, The smooth test of order one Is found to be most efficient for the generalized gamma alternatives.     

A frailty model for (interval) censored family survival data,applied to the age at onset of non-physical problems

Family survival data can be used to estimate the degree of genetic and environmental contributions to the age at onset of a disease or of a specific event in life. The data can be modeled with a correlated frailty model in which the frailty variable accounts for the degree of kinship within the family. The heritability (degree of heredity) of the age at a specific event in life (or the onset of a disease) is usually defined as the proportion of variance of the survival age that is associated with genetic effects. If the survival age is (interval) censored, heritability as usually defined cannot be estimated. Instead, it is defined as the proportion of variance of the frailty associated with genetic effects. In this paper we describe a correlated frailty model to estimate the heritability and the degree of environmental effects on the age at which individuals contact a social worker for the first time and to test whether there is a difference between the survival functions of this age for twins and non-twins.     

The International Adoption Experience: Do They Live Happily Ever After?

This study presents the perspective of parents who adopted children internationally and their now adult adopted children regarding the impact of international adoption on their lives. Areas explored include adaptation of the child and family, challenges experienced along the way, influence on various aspects of their lives, parent-child relationship, rewards and regrets associated with the adoption experience, recommendations for those considering international adoptions, and an adjective that would describe their journey. The outcome illuminates the success of international adoptions and the life-changing bond that is formed when parents and children transcend all boundaries to form a family to call their own.     

Methods for calculating stationary distribution in linear models of time series

The article deals with methods for computing the stationary marginal distribution in linear models of time series. Two approaches are described. First, an algorithm based on approximation of solution of the corresponding integral equation is briefly reviewed. Then, we study the limit behaviour of the partial sums c ₁ η₁+c ₂ η₂+···+c _n η _n where η _i are i.i.d. random variables and c _i real constants. We generalize procedure of Haiman (1998) [Haiman, G., 1998, Upper and lower bounds for the tail of the invariant distribution of some AR(1) processes. Asymptotic Methods in Probability and Statistics, 45, 723–730.] to an arbitrary causal linear process and relax the assumptions of his result significantly. This is achieved by investigating the properties of convolution of densities.