Consistency between fertility attitudes and behaviour: A conceptual model

The consistency (or lack of it) between attitude and behaviour has been a controversial issue in social psychology for the past several decades,¹ and more recently has become a focus of considerable controversy in the field of population studies.² In accordance with Freedman, Hermalin and Chang,³it is argued here that this controversy will not be resolved by theoretical discussions, and evidence is needed from many countries at several time points to resolve this issue. This paper presents evidence on consistency between fertility attitudes and behaviour from survey data from Venezuela and, based upon analysis of the present data, suggests a conceptual model for the study of consistency between fertility attitudes and behaviour.     

Bayesian Probabilistic Projections of Life Expectancy for All Countries

We propose a Bayesian hierarchical model for producing probabilistic forecasts of male period life expectancy at birth for all the countries of the world to 2100. Such forecasts would be an input to the production of probabilistic population projections for all countries, which is currently being considered by the United Nations. To evaluate the method, we conducted an out-of-sample cross-validation experiment, fitting the model to the data from 1950–1995 and using the estimated model to forecast for the subsequent 10 years. The 10-year predictions had a mean absolute error of about 1 year, about 40 % less than the current UN methodology. The probabilistic forecasts were calibrated in the sense that, for example, the 80 % prediction intervals contained the truth about 80 % of the time. We illustrate our method with results from Madagascar (a typical country with steadily improving life expectancy), Latvia (a country that has had a mortality crisis), and Japan (a leading country). We also show aggregated results for South Asia, a region with eight countries. Free, publicly available R software packages called bayesLife and bayesDem are available to implement the method.     

Modelling Deceleration in Senescent Mortality

Mortality deceleration is the observed but yet to be understood phenomenon that the increase in the late-life death rate slows down after a certain species-related advanced age. Various definitions of onsets of mortality deceleration are examined. A new distribution based on the Strehler-Mildvan theory of aging takes on the required shapes. The application is done on mortality data from the 1892 cohort of Swedish women and on Mediterranean fruit flies.     

Compositional biplots including external non-compositional variables

Biplots represent a widely used statistical tool for visualizing the resulting loadings and scores of a dimension reduction technique applied to multivariate data. If the underlying data carry only relative information (i.e. compositional data expressed in proportions, mg/kg, etc.) they have to be pre-processed with a logratio transformation before the dimension reduction is carried out. In the context of principal component analysis, the resulting biplot is called compositional biplot. We introduce an alternative, the ilr biplot, which is based on a special choice of orthonormal coordinates resulting from an isometric logratio (ilr) transformation. This allows to incorporate also external non-compositional variables, and to study the relations to the compositional variables. The methodology is demonstrated on real data sets.     

Partner Choice in Sweden Following a Failed Intermarriage

This paper is based on the assumption that divorced and separated individuals bring with them the experience of a failed union which may shape their future choices on the marriage market. It aims to contribute to our knowledge of intermarriage, and social interaction in Sweden in general, by comparing the repartnering choices of immigrants and natives in Sweden who had made what is still considered an atypical choice of entering a native-immigrant union with the partner choices of natives and immigrants whose previous union was endogamous. The empirical analysis in this paper is based on the Swedish register data from the STAR data collection (Sweden over Time: Activities and Relations) and covers the period 1990–2007. All the analyses in the paper include individuals aged 20–55 at the time of union dissolution. The multivariate analysis is based on discrete-time multinomial logistic regression. The results show that for all four groups defined by sex and nativity (native men, native women, immigrant men, and immigrant women), there is a positive association between the previous experience of intermarriage and the likelihood of initiating another intermarriage after union dissolution. Another important finding is that the magnitude of this positive association increases with the degree of social distance between the groups involved in the union. Gender differences are modest among natives and somewhat more pronounced among immigrants.     

Estimating a uniform distribution when data are measured with a normal additive error with unknown variance

The problem of estimating the width of a symmetric uniform distribution on the line together with the error variance, when data are measured with normal additive error, is considered. The main purpose is to analyse the maximum-likelihood (ML) estimator and to compare it with the moment-method estimator. It is shown that this two-parameter model is regular so that the ML estimator is asymptotically efficient. Necessary and sufficient conditions are given for the existence of the ML estimator. As numerical problems are known to frequently occur while computing the ML estimator in this model, useful suggestions for computing the ML estimator are also given.     

Connectivity‐informed adaptive regularization for generalized outcomes

One of the challenging problems in neuroimaging is the principled incorporation of information from different imaging modalities. Data from each modality are frequently analyzed separately using, for instance, dimensionality reduction techniques, which result in a loss of mutual information. We propose a novel regularization method, generalized ridgified Partially Empirical Eigenvectors for Regression (griPEER), to estimate associations between the brain structure features and a scalar outcome within the generalized linear regression framework. griPEER improves the regression coefficient estimation by providing a principled approach to use external information from the structural brain connectivity. Specifically, we incorporate a penalty term, derived from the structural connectivity Laplacian matrix, in the penalized generalized linear regression. In this work, we address both theoretical and computational issues and demonstrate the robustness of our method despite incomplete information about the structural brain connectivity. In addition, we also provide a significance testing procedure for performing inference on the estimated coefficients. Finally, griPEER is evaluated both in extensive simulation studies and using clinical data to classify HIV+ and HIV? individuals.     

Strategic sustainability and financial performance: exploring abnormal returns

The ongoing empirical debate about whether SRI is associated, if anything, with subpar or surpassing financial performance is characterized by a somewhat indistinct focus and the infeasibility of tapping the full potential of existing models. By indistinct focus, we mean an analysis based on an aggregation of a myriad of SRI factors that potentially affect a firm’s financial performance. The inability of taking full advantage of existing models is reflected by the fact that studies with European data have not been able to comprehensively account for systematic risk tilts. This paper presents a portfolio analysis that overcomes these issues by analyzing a distinct selection of small and innovative firms. We argue that both their strategic implementation of Corporate Social Responsibility and the general growth in socially responsible investments (SRI) lend themselves to an explanation for positive abnormal returns of this portfolio. We account for the idiosyncratic investment style of SRI by introducing a comprehensive pan-European risk-adjusted portfolio analysis based on the Carhart four-factor model. A novel propensity score matching method in conjunction with the estimation of structural models completes the conventional robustness checks in the literature.