Effect of family structure on life satisfaction: australian evidence

How do family arrangements affect subjective well-being? We investigate this issue using data pooled from the IsssA and HILDA, both large, representative national samples of Australia (pooled n=38 447). Our regression analysis of cross-sectional and panel data examines how large are the differences in life satisfaction according to marital status and cohabitation. We find that women and men in formal marriages experience higher levels of life satisfaction than do people in other family arrangements. Moreover, both multiple tests in the cross-section, and tests controlling for prior happiness in the panel analysis, suggest that this is a causal relationship. Aggregating up the levels of life satisfaction generated by different marriage and cohabitation arrangements across a lifetime, suggests that a life-long marriage is the most satisfying. Early divorce followed by an enduring second marriage is little worse (because little time is spent outside the married state). But divorce without remarriage, or long lasting cohabitation without formal marriage, reduce the lifetime sum of subjective well-being by 4–12% for both women and men.     

Inequality and welfare evaluation of heterogeneous income distributions

This paper establishes the principles that should govern the welfare and inequality analysis of heterogeneous income distributions. Two basic criteria – the equity preference condition and the compensation principle – are shown to be fundamentally incompatible. The paper favours the latter, thereby vindicating the traditional method of dealing with heterogeneous samples. However, inequality and welfare comparisons will usually be well defined only if equivalent incomes are obtained using constant scale factors; and researchers will need to distinguish clearly between inequality of nominal incomes and inequality of living standards. Furthermore, household observations must always be weighted according to family size.     

Small area estimation for longitudinal surveys

Over the last few years many studies have been carried out in Italy to identify reliable small area labour force indicators. Considering the rotated sample design of the Italian Labour Force Survey, the aim of this work is to derive a small area estimator which borrows strength from individual temporal correlation, as well as from related areas. Two small area estimators are derived as extensions of an estimation strategies proposed by Fuller (1990) for partial overlap samples. A simulation study is carried out to evaluate the gain in efficiency provided by our solutions. Results obtained for different levels of autocorrelation between repeated measurements on the same outcome and different population settings show that these estimators are always more reliable than the traditional composite one, and in some circumstances they are extremely advantageous.The present paper is financially supported by Murst-Cofin (2001) Lutilizzo di informazioni di tipo amministrativo nella stima per piccole aree e per sottoinsiemi della popolazione (National Coordinator Prof. Carlo Filippucci).     

A weighted polynomial regression method for local fitting of spatial data

Typically, parametric approaches to spatial problems require restrictive assumptions. On the other hand, in a wide variety of practical situations nonparametric bivariate smoothing techniques has been shown to be successfully employable for estimating small or large scale regularity factors, or even the signal content of spatial data taken as a whole.We propose a weighted local polynomial regression smoother suitable for fitting of spatial data. To account for spatial variability, we both insert a spatial contiguity index in the standard formulation, and construct a spatial-adaptive bandwidth selection rule. Our bandwidth selector depends on the Gearys local indicator of spatial association. As illustrative example, we provide a brief Monte Carlo study case on equally spaced data, the performances of our smoother and the standard polynomial regression procedure are compared.This note, though it is the result of a close collaboration, was specifically elaborated as follows: paragraphs 1 and 2 by T. Sclocco and the remainder by M. Di Marzio. The authors are grateful to the referees for constructive comments and suggestions.     

Occupational stress as it relates to higher education,individuals and organizations

This study examined through survey research methodology the degree to which, faculty, administrators and program coordinators, working in higher education, experience stress at work. The Occupational Stress Indicator was used, composed of four compound factors: sources of occupational stress, individual characteristics, coping strategies and the effects of stress. Preliminary findings showed that occupational stress has a negative impact on the degree of satisfaction with their achievement, value and growth, being strongest with faculty and coordinators, (dissatisfaction with career opportunities, personal growth, skill utilization). Another significant outcome was the dissatisfaction of faculty with the organizational design, structure and processes (communication, change implementation, motivation, supervision style, participation in decision-making). All possess individual characteristics of the Type A Scale; they all considered major sources of pressure in their jobs to be their relationships with others, home/work interface, their need to achieve personal and corporate success. Occupational stress has affected their state of health.     

Social context and adolescent health behavior: does school-level smoking prevalence affect students' subsequent smoking behavior?

This paper examines the links between individual adolescent smoking behavior and actual and perceived smoking behavior in the individual's school cohort. We hypothesized that students enrolled in schools with higher smoking prevalence among students in their grade are more likely to smoke subsequently. We also expected perceived school-level prevalence of smoking to have a greater impact than actual prevalence because the former is a more direct measure of perceived norms. Adjusting for demographics, actual school-level prevalence at baseline (grade 7) was strongly associated with smoking frequency one year later. However, the association disappeared after adjusting for individual smoking frequency at baseline. School-level prevalence did not moderate the association between individual's baseline and subsequent smoking frequency. Perceived prevalence of smoking among grade 8 students and two measures tapping the behavior of smaller peer groups--cigarette offers and exposure to friends and other peers who smoke--were associated with increased risk of smoking.     

Missing at random (MAR) in nonparametric regression - A simulation experiment

The additive model is considered when some observations on x are missing at random but corresponding observations on y are available. Especially for this model, missing at random is an interesting case because the complete case analysis is expected to be no more suitable. A simulation experiment is reported and the different methods are compared based on their superiority with respect to the sample mean squared error. Some focus is also given on the sample variance and the estimated bias. In detail, the complete case analysis, a kind of stochastic mean imputation, a single imputation and the nearest neighbor imputation are discussed.     

Beyond Empathic Failures: Cultural Racism as Narcissistic Trauma and Disenfranchisement of Grandiosity

Applying a self-psychological perspective, this paper explores the effects of cultural racism on a person's sense of self. Racism assaults victims with experiences of being perceived as less-than-human by the social milieu. Such experiences can utterly erode self-esteem and ambition and cause a depression of disenfranchisement whereby one feels abjectly ungrandiose. The paper utilizes a literary example and one from clinical experience to illustrate how chronic experiences of antipathy—derived from cultural racism—can erode a person's sense of self by virtue of the disenfranchisement of grandiosity.     

An efficient polynomial space and polynomial delay algorithm for enumeration of maximal motifs in a sequence

In this paper, we consider the problem of enumerating all maximal motifs in an input string for the class of repeated motifs with wild cards. A maximal motif is such a representative motif that is not properly contained in any larger motifs with the same location lists. Although the enumeration problem for maximal motifs with wild cards has been studied in Parida et al. (2001), Pisanti et al. (2003) and Pelfrêne et al. (2003), its output-polynomial time computability has been still open. The main result of this paper is a polynomial space polynomial delay algorithm for the maximal motif enumeration problem for the repeated motifs with wild cards. This algorithm enumerates all maximal motifs in an input string of length n in O(n ³) time per motif with O(n) space, in particular O(n ³) delay. The key of the algorithm is depth-first search on a tree-shaped search route over all maximal motifs based on a technique called prefix-preserving closure extension. We also show an exponential lower bound and a succinctness result on the number of maximal motifs, which indicate the limit of a straightforward approach. The results of the computational experiments show that our algorithm can be applicable to huge string data such as genome data in practice, and does not take large additional computational cost compared to usual frequent motif mining algorithms. This work is done during the Hiroki Arimura’s visit in LIRIS, University Claude-Bernard Lyon 1, France.