Quality of Life in the Economic and Urban Economic Literature

Quality of life (QoL) is increasingly becoming a concept researched empirically and theoretically in the field of economics. In urban economics in particular, this increasing interest stems mainly from the fact that QoL affects urban competitiveness and urban growth: research shows that when households and businesses decide where to locate, QoL considerations can play a very important role. The purpose of the present paper is to examine the way economic literature and urban economic literature in particular, have adopted QoL considerations in the economic thinking. Moreover, it presents the ways various studies have attempted to capture the multidimensional nature of the concept, and quantify it for the purposes of empirical research. Conclusions are drawn on the state of affairs regarding the study of QoL in economics, as well as the problems of measurement arising mainly from the complex nature of the concept.      

On estimation and influence diagnostics for log-Birnbaum–Saunders Student-t regression models: Full Bayesian analysis

The purpose of this paper is to develop a Bayesian approach for log-Birnbaum–Saunders Student-t regression models under right-censored survival data. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian procedure for the considered model. In order to attenuate the influence of the outlying observations on the parameter estimates, we present in this paper Birnbaum–Saunders models in which a Student-t distribution is assumed to explain the cumulative damage. Also, some discussions on the model selection to compare the fitted models are given and case deletion influence diagnostics are developed for the joint posterior distribution based on the Kullback–Leibler divergence. The developed procedures are illustrated with a real data set.     

Accuracy of Power-Divergence Statistics for Testing Independence and Homogeneity in Two-Way Contingency Tables

The small-sample accuracy of seven members of the family of power-divergence statistics for testing independence or homogeneity in contingency tables was studied via simulation. The likelihood ratio statistic G ² and Pearson's X ² statistic are among these seven members, whose behavior was studied at nominal test sizes of.01 and.05 with marginal distributions that could be uniform or skewed and with a set of sample sizes that included sparseness conditions as measured through table density (i.e., the ratio of sample size to number of cells). The likelihood ratio statistic G ² rejected the null hypothesis too often even with large table density, whereas Pearson's X ² was sufficiently accurate and only presented a minor misbehavior when table density was less than two observations/cell. None of the other five statistics outperformed Pearson's X ². A nonasymptotic variant of X ² solved the minor inaccuracies of Pearson's X ² and turned out to be the most accurate statistic for testing independence or homogeneity, even with table densities of one observation/cell. These results clearly advise against the use of the likelihood ratio statistic G ².     

Testing the Time‐Variancy of Explanatory Factors of Strategic Change1

The article proposes an empirical framework able to: (1) assess the relative validity of both adaptive and inertial views of strategic change and (2) verify the potential time‐ or context‐dependency by testing the structural stability of the empirical model, in Spanish banks, 1983–1997. Results offer inconclusive findings regarding (1) but strong evidence to answer (2). The assumption of structural stability is rejected and the effect of many explanatory factors considered in the empirical model varies over time as some factors show different effects and/or significance levels depending on the period considered. These findings suggest that explanatory models of strategic change should be viewed as ‘time‐’ or ‘context‐dependent’. The article provides a conceptual model in which alternative explanations operate in a sequential way. The results highlight, first, that inconclusive past findings about adaptive versus inertial views should be reviewed under this new evidence, and future empirical research must assure that its methods and interpretations are robust to potential structural breakdowns; and second, the limitations raised by the static approach offered by the available theories/models when approaching the dynamic and complex nature of strategic change. Theoretical developments and implications for managerial practice are suggested.     

The Poisson-exponential model for recurrent event data: an application to bowel motility data

This paper presents a new parametric model for recurrent events, in which the time of each recurrence is associated to one or multiple latent causes and no information is provided about the responsible cause for the event. This model is characterized by a rate function and it is based on the Poisson-exponential distribution, namely the distribution of the maximum among a random number (truncated Poisson distributed) of exponential times. The time of each recurrence is then given by the maximum lifetime value among all latent causes. Inference is based on a maximum likelihood approach. A simulation study is performed in order to observe the frequentist properties of the estimation procedure for small and moderate sample sizes. We also investigated likelihood-based tests procedures. A real example from a gastroenterology study concerning small bowel motility during fasting state is used to illustrate the methodology. Finally, we apply the proposed model to a real data set and compare it with the classical Homogeneous Poisson model, which is a particular case.     

A flexible model for survival data with a cure rate: a Bayesian approach

In this paper we deal with a Bayesian analysis for right-censored survival data suitable for populations with a cure rate. We consider a cure rate model based on the negative binomial distribution, encompassing as a special case the promotion time cure model. Bayesian analysis is based on Markov chain Monte Carlo (MCMC) methods. We also present some discussion on model selection and an illustration with a real data set.     

Climate,stress and satisfaction: a multilevel study in the public sector / Clima,estrés y satisfacción: un estudio multinivel en el sector público

The aim of this study was to examine the mediating effect of role ambiguity on the relationship between climate and job satisfaction in local public administration. Taking the job demands-resources model (JD-R) as the starting point, a multilevel mediation analysis was used to determine the influence of the different services within the sample. The sample consisted of 196 employees in 29 integrated services of two local corporations. Results confirm the job demands-resources model by showing multilevel partial mediation of role ambiguity in the relationship between climate and job satisfaction of public employees. These results indicate the importance of climate in organizational contexts and its implications for reducing role stressors while strengthening and maintaining the wellbeing of employees.     

Ecological and genetic consequences of fragmentation in a semiarid Mediterranean urban forest

Urbanization threatens biodiversity worldwide and is expected to increase in the future. This involves intensification of fragmentation and increase of urban forest remnants. Thus, it is important to understand the functioning of these patches for the preservation of local biodiversity. Mutualistic interactions such as seed dispersal have a key role in the dynamics of plant populations and could help to mitigate the negative effects of fragmentation on wild plant populations. In this context, we have used the mastic Pistacia lentiscus, a common Mediterranean shrub, as a model to study the interaction between seed dispersal by birds and the local genetic diversity of individuals in a highly fragmented semiarid forestry area of the Iberian Southeast (Murcia, Spain). Results reveal a high genetic diversity and a lack of differentiation between shrub patches of P. lentiscus in the area, probably as a result of a strong, but rather recent fragmentation, and an apparently poor contribution of birds to the dispersal of Pistacia seeds. However, the existence of latent impacts cannot be discarded, since at least one of the patches shows some signs of inbreeding.     

Hypothesis testing for the dispersion parameter of the hyper-Poisson regression model

The Poisson distribution is widely used to deal with count data, however, it is unable to capture the dispersion problems. The hyper-Poisson distribution is a particular case of the extended Conway–Maxwell distribution which takes into account the dispersion phenomena of the count data. The main motivation to consider this model is the possibility to link the mean to the regressor variables in very natural way to solve testing problems. So, this paper will be focalized in the gradient statistics to detect dispersions and to compare with the classical likelihood ratio statistic. Two illustrative applications are considered.     

Family Policy Index: A Tool for Policy Makers to Increase the Effectiveness of Family Policies

Social Indicators Research - This paper presents the Family Policy Index (XFPI), an analytical tool designed to measure and compare different models of countries’ provision of educational...