Saving behaviour and earnings uncertainty: Evidence from the British Household Panel Survey

For the first time, this paper uses a panel data set, the British Household Panel Survey, to analyse saving behaviour in Britain. One objective is to test the precautionary saving hypothesis, according to which households save to self-insure against uncertainty. Our results show that in accordance with this hypothesis, various measures of uncertainty based on earnings variability have a statistically significant effect on households' saving decisions. Moreover, in accordance with the life cycle model, households save more if they expect their financial situation to deteriorate. Received: 15 June 1999/Accepted: 4 January 2001     

走向未来的藏语文——从其现状趋势及主客观条件看藏语文的命运

文章在对藏语文使用现状及发展趋势进行分析的基础上 ,从制度保障、人口与地域条件以及藏语文自身所具有的优势等方面 ,就藏语文的未来命运进行了理性的思考和科学的判断 ,藏语文将与时偕进 ,站在更高的起点上与世界对话。藏语文的前途将更加光辉而灿烂。     

Deciding with Thresholds: Importance Measures and Value of Information

Risk‐informed decision making is often accompanied by the specification of an acceptable level of risk. Such target level is compared against the value of a risk metric, usually computed through a probabilistic safety assessment model, to decide about the acceptability of a given design, the launch of a space mission, etc. Importance measures complement the decision process with information about the risk/safety significance of events. However, importance measures do not tell us whether the occurrence of an event can change the overarching decision. By linking value of information and importance measures for probabilistic risk assessment models, this work obtains a value‐of‐information‐based importance measure that brings together the risk metric, risk importance measures, and the risk threshold in one expression. The new importance measure does not impose additional computational burden because it can be calculated from our knowledge of the risk achievement and risk reduction worth, and complements the insights delivered by these importance measures. Several properties are discussed, including the joint decision worth of basic event groups. The application to the large loss of coolant accident sequence of the Advanced Test Reactor helps us in illustrating the risk analysis insights.     

Geoadditive modeling for extreme rainfall data

Extreme value models and techniques are widely applied in environmental studies to define protection systems against the effects of extreme levels of environmental processes. Regarding the matter related to the climate science, a certain importance is covered by the implication of changes in the hydrological cycle. Among all hydrologic processes, rainfall is a very important variable as it is strongly related to flood risk assessment and mitigation, as well as to water resources availability and drought identification. We implement here a geoadditive model for extremes assuming that the observations follow a generalized extreme value distribution with spatially dependent location. The analyzed territory is the catchment area of the Arno River in Tuscany in Central Italy.     

Bayesian Analysis in Regression Models Using Pseudo-Likelihoods

This article deals with the issue of using a suitable pseudo-likelihood, instead of an integrated likelihood, when performing Bayesian inference about a scalar parameter of interest in the presence of nuisance parameters. The proposed approach has the advantages of avoiding the elicitation on the nuisance parameters and the computation of multidimensional integrals. Moreover, it is particularly useful when it is difficult, or even impractical, to write the full likelihood function.

We focus on Bayesian inference about a scalar regression coefficient in various regression models. First, in the context of non-normal regression-scale models, we give a theroetical result showing that there is no loss of information about the parameter of interest when using a posterior distribution derived from a pseudo-likelihood instead of the correct posterior distribution. Second, we present non trivial applications with high-dimensional, or even infinite-dimensional, nuisance parameters in the context of nonlinear normal heteroscedastic regression models, and of models for binary outcomes and count data, accounting also for possibile overdispersion. In all these situtations, we show that non Bayesian methods for eliminating nuisance parameters can be usefully incorporated into a one-parameter Bayesian analysis.     

A Passion for Gambling: A Generation-Specific Conceptual Analysis and Review of Gambling Among Older Adults in Canada

The proliferation of gambling opportunities in Canada, coupled with an aging population, has led to an increased prevalence of gambling among older adults. Encouraged by this trend, gambling industries have modified their activities to attract and market to this group. Yet, older adults are not a homogeneous group. The life experiences, values, and attitudes shared by generations make a cohort-specific analysis of gambling among older adults a worthwhile pursuit. Drawing from the Dualistic Model of Passion (Vallerand et al. in J Pers Soc Psychol 85(4):756–767, 2003), we discuss the role of passion in shaping gambling behaviours, and the implications of a harmonious or obsessive passion on the benefits and risks to two distinct generations of older adults. Based on their generational attributes, we posit that members of the Silent Generation (those born between 1925 and 1942) stand to gain more from the benefits of recreational gambling, but also stand lose more from problem gambling, than their children’s generation, the Baby Boomers (those born between 1942 and 1964). Preventative strategies to assist problem gambling seniors, along with recommendations for further research, are discussed.     

Disappointment without prior expectation: a unifying perspective on decision under risk

The central idea of Disappointment theory is that an individual forms an expectation about a risky alternative, and may experience disappointment if the outcome eventually obtained falls short of the expectation. We abandon the hypothesis of a well-defined prior expectation: disappointment feelings may arise from comparing the outcome received with anyof the gamble’s outcomes that the individual failed to get. This leads to a new, general form of Disappointment model. It encompasses Rank Dependent Utility with an explicit one-parameter probability transformation, and Risk-Value models with a generic risk measure including Variance, providing a unifying behavioral foundation for these models. JEL Classification D80 . D81     

Survival Trees: An Alternative Non-Parametric Multivariate Technique for Life History Analysis

In this paper an extension of tree-structured methodology to cover censored survival analysis is discussed. Tree-based methods (also called recursive partitioning) provide a useful alternative to the classical survival data analysis techniques, such as the semi-parametric model of Cox, whenever the main purpose is defining groups of individuals, either with complete or censored life history, having different survival probability, based on the values of selected covariates. The essential feature of recursive partitioning is the construction of a decision rule in the form of a binary tree. Trees generally require fewer assumptions than classical methods and handle non standard and non linear data structures efficiently. Tree-growing methods make the processes of covariate selection and grouping of categories in event history models explicit. An example concerning the analysis of time to marriage of Italian women is presented.     

A new 'biased coin design' for the sequential allocation of two treatments

Summary.  Efron's biased coin design is a well-known randomization technique that helps to neutralize selection bias in sequential clinical trials for comparing treatments, while keeping the experiment fairly balanced. Extensions of the biased coin design have been proposed by several researchers who have focused mainly on the large sample properties of their designs. We modify Efron's procedure by introducing an adjustable biased coin design, which is more flexible than his. We compare it with other existing coin designs; in terms of balance and lack of predictability, its performance for small samples appears in many cases to be an improvement with respect to the other sequential randomized allocation procedures.     

Income Share Elasticity and Stochastic Dominance

Income share elasticity is a function π which can describe the size distribution of income (Esteban in Intern Econ Rev 27:439–444, 1986). On the other hand, the conventional density representation of the latter gives parameters of first or second order stochastic dominance (SD), widely used to describe shifts in income distribution, to which inequality measures are attached. The paper draws a link between the two, by providing conditions such that a given shift to π is equivalent to a first or second order SD shift of the distribution of income. Some applications to Lorenz rankings are also provided.