Should we expect commitment?

And I, who felt my head surrounded by horrors, Said: Master, what then is it that I am hearing? And what people are these, so crushed by pain?     

Consumption Over the Life Cycle

This paper estimates a structural model of optimal life‐cycle consumption expenditures in the presence of realistic labor income uncertainty. We employ synthetic cohort techniques and Consumer Expenditure Survey data to construct average age‐profiles of consumption and income over the working lives of typical households across different education and occupation groups. The model fits the profiles quite well. In addition to providing reasonable estimates of the discount rate and risk aversion, we find that consumer behavior changes strikingly over the life cycle. Young consumers behave as buffer‐stock agents. Around age 40, the typical household starts accumulating liquid assets for retirement and its behavior mimics more closely that of a certainty equivalent consumer. Our methodology provides a natural decomposition of saving and wealth into its precautionary and life‐cycle components.     

Nonparametric Engel Curves and Revealed Preference

This paper applies revealed preference theory to the nonparametric statistical analysis of consumer demand. Knowledge of expansion paths is shown to improve the power of nonparametric tests of revealed preference. The tightest bounds on indifference surfaces and welfare measures are derived using an algorithm for which revealed preference conditions are shown to guarantee convergence. Nonparametric Engel curves are used to estimate expansion paths and provide a stochastic structure within which to examine the consistency of household level data and revealed preference theory. An application is made to a long time series of repeated cross–sections from the Family Expenditure Survey for Britain. The consistency of these data with revealed preference theory is examined. For periods of consistency with revealed preference, tight bounds are placed on true cost of living indices.     

Integrating Individual Differences in Career Assessment: The Atlas Model of Individual Differences and the Strong Ring

Career assessment methods often include measures of individual differences constructs, such as interests, personality, abilities, and values. Although many researchers have recently called for the development of integrated models, career counseling professionals have long faced the challenge of integrating this information into their practice. The authors examine the use of integrated models to enhance the career counseling process, including Armstrong, Day, McVay, and Rounds's (2008) RIASEC‐based Atlas Model of Individual Differences (using Holland's 1997, typology of 6 interest types: Realistic, Investigative, Artistic, Social, Enterprising, and Conventional [RIASEC]) and Armstrong, Smith, Donnay, and Rounds's (2004) basic interests‐based Strong Ring. These models provide a structured framework for presenting clients with assessment feedback that emphasizes connections between interests, personality, and abilities.     

Using expected values to simplify decision making under uncertainty

A simulation study examines the impact of a simplification strategy that replaces distributional attribute evaluations with their expected values and uses those expectations in an additive value model. Several alternate simplified forms and approximation approaches are investigated, with results showing that in general the simplified models are able to provide acceptable performance that is fairly robust to a variety of internal and external environmental changes, including changes to the distributional forms of the attribute evaluations, errors in the assessment of the expected values, and problem size. Certain of the simplified models are shown to be highly sensitive to the form of the underlying preference functions, and in particular to extreme non-linearity in these preferences.     

Best Nonparametric Bounds on Demand Responses

This paper uses revealed preference inequalities to provide the tightest possible (best) nonparametric bounds on predicted consumer responses to price changes using consumer‐level data over a finite set of relative price changes. These responses are allowed to vary nonparametrically across the income distribution. This is achieved by combining the theory of revealed preference with the semiparametric estimation of consumer expansion paths (Engel curves). We label these expansion path based bounds on demand responses as E‐bounds. Deviations from revealed preference restrictions are measured by preference perturbations which are shown to usefully characterize taste change and to provide a stochastic environment within which violations of revealed preference inequalities can be assessed.     

Estimating Consumer Exposure to PFOS and PFOA

Perfluorinated compounds have been used for more than 50 years as process aids, surfactants, and for surface protection. This study is a comprehensive assessment of consumer exposure to perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) from a variety of environmental and product-related sources. To identify relevant pathways leading to consumer exposure to PFOS and PFOA a scenario-based approach has been applied. Scenarios represent realistic situations where age- and gender-specific exposure occurs in the everyday life of consumers. We find that North American and European consumers are likely to experience ubiquitous and long-term uptake doses of PFOS and PFOA in the range of 3 to 220 ng per kg body weight per day (ng/kg_bw/day) and 1 to 130 ng/kg_bw/day, respectively. The greatest portion of the chronic exposure to PFOS and PFOA is likely to result from the intake of contaminated foods, including drinking water. Consumer products cause a minor portion of the consumer exposure to PFOS and PFOA. Of these, it is mainly impregnation sprays, treated carpets in homes, and coated food contact materials that may lead to consumer exposure to PFOS and PFOA. Children tend to experience higher total uptake doses (on a body weight basis) than teenagers and adults because of higher relative uptake via food consumption and hand-to-mouth transfer of chemical from treated carpets and ingestion of dust. The uptake estimates based on scenarios are within the range of values derived from blood serum data by applying a one-compartment pharmacokinetic model.     

Applying Relational Models to the Graduation of Disability Schedules

Age-specific rates of particular disability types are important for planning purposes and are a valuable input to estimates and projections of populations with different disabilities. However, survey estimates of schedules of disability rates display evidence of sampling variability and sub-national disability schedules are often unavailable for reasons of disclosure protection. This paper develops and evaluates a method to smooth sampling variability in national schedules of disability using a technique that has applicability to sub-national estimation of age-specific disability rates. Relational models are used to adjust the limiting long-term illness schedule for England (Census 2001) to represent different disability schedules (Health Survey for England 2000/2001) smoothing sampling fluctuations. For hearing disability a simple Brass relational model involving two parameters provides a good fit. For other disability types a modified version of the Ewbank relational model with three parameters is required. This paper illustrates that relational models can accurately capture the relationship between age-specific rates of limiting long-term illness and various disability types.