Common Mathematical Foundations of Expected Utility and Dual Utility Theories

We show that the main results of the expected utility and dual utility theories can be derived in a unified way from two fundamental mathematical ideas: the separation principle of convex analysis, and integral representations of continuous linear functionals from functional analysis. Our analysis reveals the dual character of utility functions. We also derive new integral representations of dual utility models

Nonparametric Analysis of Random Utility Models

This paper develops and implements a nonparametric test of Random Utility Models. The motivating application is to test the null hypothesis that a sample of cross-sectional demand distributions was generated by a population of rational consumers. We test a necessary and sufficient condition for this that does not rely on any restriction on unobserved heterogeneity or the number of goods. We also propose and implement a control function approach to account for endogenous expenditure. An econometric result of independent interest is a test for linear inequality constraints when these are represented as the vertices of a polyhedron rather than its faces. An empirical application to the U.K. Household Expenditure Survey illustrates computational feasibility of the method in demand problems with 5 goods.Comment: 54 pages, 2 figure

Future Utility Analysis Research: Continue, but Expand the Cognitive and Strategic Focus

[Excerpt] Does utility analysis research have a future? I believe the answer depends on how we contemplate the nature of such research. The distinction between two potential paths has never been more apparent. On the one hand, as researchers, industrial psychologists and others have accumulated decades of utility analysis applications and proposals for new utility approaches and estimation methods. Numerous utility applications exist, especially in selection. Spirited debates have occurred in the scholarly journals on such topics as the value of capital budgeting (Hunter, Schmidt & Coggin, 1988), the appropriate underlying conceptual utility model for scaling performance differences into dollars (Raju, Burke & Normand, 1990), and the appropriate measure of dollar-valued performance variability (SDy) (see Boudreau, 1991 for a review). One would think that after such a long and public history, we would have a set of accepted principles that might guide utility analysis applications, measurement and theory. Unfortunately, we do not. The title of this symposium testifies to the ongoing consternation faced by the scientific community about utility analysis

Utility Analysis for Multiple Selection Devices and Multiple Outcomes

Traditional utility analysis only calculates the value of a given selection procedure over random selection. This assumption is not only an inaccurate representation of staffing policy but leads to overestimates of a device\u27s value. This paper generates a new utility model that accounts for multiple selection devices and multiple criteria. The model is illustrated using previous utility analysis work and an actual case of secretarial employees with eight predictors and nine criteria. A final example also is provided which includes these advancements as well as other researchers\u27 advances in a combined utility model. Results reveal that accounting for multiple criteria and outcomes dramatically reduces the utility estimates of implementing new selection devices

Utility analysis : current trends and future directions.

Utility analysis procedures offer organizational decision-makers useful information regarding the relative values of different interventions. Years of research have resulted in a number of practically viable utility models and extensions. There is a continued need for research to examine the accuracy of utility estimates and to further compare the different models. A more recent research concern is that of low levels of acceptance of utility analysis results by practitioners. Many researchers are turning their attention to ways in which this acceptance may be increased. This article reviews different utility models as well as a number of important extensions. It then discusses current utility analysis issues, such as the aforementioned acceptance problem and the introduction of a multi-attribute utility model. The article concludes with suggestions for future utility analysis researchUtility theory; Mathematical models; Decision making;

Image and Reality: the Case of Job Satisfaction

This study makes a distinction between two types of utility. Experienced utility is defined as the job satisfaction derived from the present job, estimated by using a subjective evaluation of job satisfaction. Anticipated utility is defined as the individual’s anticipated job satisfaction before starting the job and it is studied by using a stated preference methodology known as conjoint analysis. The results suggest that the two utility concepts are different. Information about experienced utility is useful for the evaluation of well-being policies and the welfare effects of various employer strategies. Anticipated utility provides knowledge about the job search process.European Commission, Fifth Framework Programme "Improving Human Potential" (contract number: HPSE-CT-2002-00143)

Fundamental flaws in the current cost regulatory capital value method of utility pricing

Jim Cuthbert and Margaret Cuthbert’s most recent analysis of the UK’s utility businesses (see QEC Vol 31 No 3) seeks to challenge the fundamental price setting methodology adopted by utility regulators. The basis of the challenge arises from an estimate of the size of the apparent super normal profits being made by utility companies. From this they conclude that the resultant equity return is too high and so leaves customers paying prices that are too high for the services provided1

Scoring methods, multiple criteria, and utility analysis

decision making;computers;information and uncertainty

Is Utility Transferable? A Revealed Preference Analysis

We provide a revealed preference analysis of the transferable utility hypothesis, which is widely used in economic models. First, we establish revealed preference conditions that must be satisfied for observed group behavior to be consistent with Pareto efficiency under transferable utility. Next, we show that these conditions are easily testable by means of integer programming methods. The tests are entirely nonparametric, which makes them robust with respect to specification errors. Finally, we demonstrate the practical usefulness of our conditions by means of an application to Spanish consumption data. To the best of our knowledge, this is the first empirical test of the transferable utility hypothesis.transferable utility hypothesis;generalized quasi-linearity;nonparamet- ric tests;revealed preferences

The development of a measure of social care outcome for older people. Funded/commissioned by: Department of Health

An essential element of identifying Best Value and monitoring cost-effective care is to be able to identify the outcomes of care. In the field of health services, use of utility-based health related quality of life measures has become widespread, indeed even required. If, in the new era of partnerships, social care outcomes are to be valued and included we need to develop measures that reflect utility or welfare gain from social care interventions. This paper reports on a study, commissioned as part of the Department of Health’s Outcomes of Social Care for Adults Initiative, that developed an instrument and associated utility indexes that provide a tool for evaluating social care interventions in both a research and service setting. Discrete choice conjoint analysis used to derive utility weights provided us with new insights into the relative importance of the core domains of social care to older people. Whilst discrete choice conjoint analysis is being increasingly used in health economics, this is the first study that has attempted to use it to derive a measure of outcome