The perception of the values of urban space by senior citizens of Valparaiso

This paper is framed within the context of the Fondecyt Research Project (No. 1061179) entitled “Senior Citizens' quality of life in an Urban Habitat: Valparaiso, a Case Study.” It investigates how certain topographical conditions in the urban habitat impact on the quality of life of the population's most senior age group. Following a theoretical approach, we discuss some of the initial results obtained in our field research, integrating a quantitative technique of territorial analysis, GIS maps, and the qualitative techniques of Focus Groups and ethnographic interviews. The study of senior citizens' perceptions of their quality of life in Valparaiso indicates that the city's irregular topography and character as a heritage city mediate how the elderly perceive the urban space, creating social networks and a sense of community uniquely their own.     

Low-pass filter design using locally weighted polynomial regression and discrete prolate spheroidal sequences

The paper concerns the design of nonparametric low-pass filters that have the property of reproducing a polynomial of a given degree. Two approaches are considered. The first is locally weighted polynomial regression (LWPR), which leads to linear filters depending on three parameters: the bandwidth, the order of the fitting polynomial, and the kernel. We find a remarkable linear (hyperbolic) relationship between the cut-off period (frequency) and the bandwidth, conditional on the choices of the order and the kernel, upon which we build the design of a low-pass filter.The second hinges on a generalization of the maximum concentration approach, leading to filters related to discrete prolate spheroidal sequences (DPSS). In particular, we propose a new class of low-pass filters that maximize the concentration over a specified frequency range, subject to polynomial reproducing constraints. The design of generalized DPSS filters depends on three parameters: the bandwidth, the polynomial order, and the concentration frequency. We discuss the properties of the corresponding filters in relation to the LWPR filters, and illustrate their use for the design of low-pass filters by investigating how the three parameters are related to the cut-off frequency.     

The Relationship Between Social Leisure and Life Satisfaction: Causality and Policy Implications

Social leisure is generally found to be positively correlated with life satisfaction in the empirical literature. We ask if this association captures a genuine causal effect by using panel data from the GSOEP. Our identification strategy exploits the change in social leisure brought about by retirement, since the latter is an event after which the time investable in (the outside job) relational life increases. We instrument social leisure with various measures of the age cohort specific probability of retirement. With such approach we document that social leisure has a positive and significant effect on life satisfaction. Our findings shed some light on the age-happiness pattern. Policy implications are also discussed.     

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.     

Assessing the effect of the amount of financial aids to Piedmont firms using the generalized propensity score

Regional and national development policies play an important role to support local enterprises in Italy. The amount of financial aid may be a key feature for firms’ employment policies. We study the impact on employment of the amount of financial aid attributed to enterprises located in Piedmont, a region in northern Italy, analysing small-sized firms and medium- or large-sized firms separately. We apply generalized propensity score methods under the unconfoundedness assumption that adjusting for differences in a set of observed pre-treatment variables removes all biases in comparisons by different amounts of financial aid. We find that the estimated effects are increasing with amount of financial aid for both small-sized and medium- or large-sized firms, whereas the marginal effects of additional incentives are decreasing with amount of financial aid for small-sized firms, and have an inverse J-shape for medium- or large-sized firms.     

Gender-Egalitarian Attitudes and Assortative Mating by Age and Education

European Journal of Population - In the last decades, conventional patterns of assortative mating have been challenged by changes in the gender-gap in education. In many countries, educationally...     

Serials Control for the Italian Union Catalog of Serials

Abstract

European and Italian libraries are strongly involved in efforts to facilitate access to European information resources. The Italian union catalogue of serials has evolved from a traditional catalog to a sophisticated resource that provides access to serials services. Serials control is the most recent service of the union catalog with features for end users and professional staff. The software is BASIS Techlib by ID Technology (Italy), affinity partner of Open Text (USA). The ability to customize features presents a very satisfactory, easy-to-use product that might be considered interesting for union catalogs in other countries. Serials Review 2003; 29:169–178.     

Inference from PseudoLikelihoods with Plug‐In Estimates

Effective implementation of likelihood inference in models for high‐dimensional data often requires a simplified treatment of nuisance parameters, with these having to be replaced by handy estimates. In addition, the likelihood function may have been simplified by means of a partial specification of the model, as is the case when composite likelihood is used. In such circumstances tests and confidence regions for the parameter of interest may be constructed using Wald type and score type statistics, defined so as to account for nuisance parameter estimation or partial specification of the likelihood. In this paper a general analytical expression for the required asymptotic covariance matrices is derived, and suggestions for obtaining Monte Carlo approximations are presented. The same matrices are involved in a rescaling adjustment of the log likelihood ratio type statistic that we propose. This adjustment restores the usual chi‐squared asymptotic distribution, which is generally invalid after the simplifications considered. The practical implication is that, for a wide variety of likelihoods and nuisance parameter estimates, confidence regions for the parameters of interest are readily computable from the rescaled log likelihood ratio type statistic as well as from the Wald type and score type statistics. Two examples, a measurement error model with full likelihood and a spatial correlation model with pairwise likelihood, illustrate and compare the procedures. Wald type and score type statistics may give rise to confidence regions with unsatisfactory shape in small and moderate samples. In addition to having satisfactory shape, regions based on the rescaled log likelihood ratio type statistic show empirical coverage in reasonable agreement with nominal confidence levels.     

Estimating and using propensity score in presence of missing background data: an application to assess the impact of childbearing on wellbeing

Propensity score methods are an increasingly popular technique for causal inference. To estimate propensity scores, we must model the distribution of the treatment indicator given a vector of covariates. Much work has been done in the case where the covariates are fully observed. Unfortunately, many large scale and complex surveys, such as longitudinal surveys, suffer from missing covariate values. In this paper, we compare three different approaches and their underlying assumptions of handling missing background data in the estimation and use of propensity scores: a complete-case analysis, a pattern-mixture model based approach developed by Rosenbaum and Rubin (J Am Stat Assoc79:516–524, 1984), and a multiple imputation approach. We apply these methods to assess the impact of childbearing events on individuals’ wellbeing in Indonesia, using a sample of women from the Indonesia Family Life Survey. I am grateful to all the participants at the project “Poverty Dynamics and Fertility in Developing Countries” for their support and encouragement. Special thanks are due to Fabrizia Mealli for her insightful suggestions and discussions. I also thank Jungho Kim, who is the main author of the STATA code to produce Indonesia consumption expenditure. Finally, I thank Arnstein Aassve, and Letizia Mencarini for help working with the data and their very useful discussions, and Alexia Fuernkranz-Prskawetz, and Henriette Engelhardt for detailed comments and suggestions which have improved the paper. Financial support from CNR-EFS and COFIN 2005 is gratefully acknowledged.