SIMPCA: a framework for rotating and sparsifying principal components

We propose an algorithmic framework for computing sparse components from rotated principal components. This methodology, called SIMPCA, is useful to replace the unreliable practice of ignoring small coefficients of rotated components when interpreting them. The algorithm computes genuinely sparse components by projecting rotated principal components onto subsets of variables. The so simplified components are highly correlated with the corresponding components. By choosing different simplification strategies different sparse solutions can be obtained which can be used to compare alternative interpretations of the principal components. We give some examples of how effective simplified solutions can be achieved with SIMPCA using some publicly available data sets.     

Population Density is a Key Factor in Declining Human Fertility

In studying the complex determinants of human fertility, social scientists have given little attention to population density, although reproduction has been shown to be density-dependent for a wide variety of other species. Using fixed effects models on the time series of 145 countries and controlling for key social and economic variables, we find a consistent and significant negative relationship between human fertility and population density. Moreover, we find that individual fertility preferences also decline with population density. These findings suggest that population density should be included as a variable in future studies of fertility determinants.

Analysing International Student Mobility Flows in Higher Education: A Comparative Study on European Countries

The analysis of the factors pulling and pushing students in a foreign country to complete their higher education is key for the implementation of university policies aimed at increasing the number of credits gained by students abroad and hence the degree of internationalisation of institutions. Consistent with previous studies, the present contribution examines the roles played by countries in the Erasmus student mobility flows by considering a joint strategy of analysis based on social network analysis and exploratory data analysis. First, data on Erasmus student exchanges among countries are gathered at macro-level from the European Union Open Data Portal and network data structures are analysed. Second, educational indicators from the Eurostat website are collected to describe the investments in higher education. The main findings suggest the presence of a core-periphery configuration in the student mobility network with few central countries in which the economic benefits and the investments in education seem to act as key elements for university attractiveness.

     

What’s in a yardscape? A case study of emergent ecosystem services and disservices within resident yardscape discourses in Minnesota

Urban Ecosystems - Residential yardscapes are at the forefront of human interaction with nature for those living in urban areas across Europe and North America. In recent years a significant amount...     

The Great Convergence: Gender and Unpaid Work in Europe and the United States

Over the past decades, men's and women's time use in industrialized nations has changed dramatically, suggesting a gender revolution. Women increased their time in paid work and reduced time in unpaid activities, while men increased their time in unpaid work, but not enough to compensate for women's retreat. We investigate developments regarding men's and women's unpaid work across Europe and the United States, using time diary data from the mid‐1980s and onward. We find evidence for gender convergence in unpaid work over time, but different trends for housework and childcare. Gender convergence in housework primarily resulted from women reducing their time, whereas childcare time increased for both sexes, resulting in convergence only where men increased more than did women. Decomposition analyses show that trends in housework and childcare are explained by changes in behavior rather than compositional changes in population characteristics. Though level differences in unpaid work persist, our findings regarding trends support gender convergence in that they are general across country contexts that vary regarding policy and social norms about gender, family, and work.     

A new regression model for bimodal data and applications in agriculture

We define the odd log-logistic exponential Gaussian regression with two systematic components, which extends the heteroscedastic Gaussian regression and it is suitable for bimodal data quite common in the agriculture area. We estimate the parameters by the method of maximum likelihood. Some simulations indicate that the maximum-likelihood estimators are accurate. The model assumptions are checked through case deletion and quantile residuals. The usefulness of the new regression model is illustrated by means of three real data sets in different areas of agriculture, where the data present bimodality.     

A Bitcoin-inspired infinite-server model with a random fluid limit

The synchronization process inherent to the Bitcoin network gives rise to an infinite-server model with the unusual feature that customers interact. Among the closed-form characteristics that we derive for this model is the busy period distribution which, counterintuitively, does not depend on the arrival rate. We explain this by exploiting the equivalence between two specific service disciplines, which is also used to derive the model’s stationary distribution. Next to these closed-form results, the second major contribution concerns an asymptotic result: a fluid limit in the presence of service delays. Since fluid limits arise under scalings of the law-of-large-numbers type, they are usually deterministic, but in the setting of the model discussed in this paper the fluid limit is random (more specifically, of growth-collapse type).     

Trajectories of Limitations with Activities of Daily Living Among Older Adults of Mexican Descent: The Role of Widowhood

Using seven waves of data from the Hispanic Established Population for the Epidemiologic Study of the Elderly (1993–2011), this study applies multiphase growth models to examine changes in limitations with activities of daily living (ADL) across widowhood experience among 385 older adults of Mexican descent. This study also investigates the implications of demographic characteristics, health, socioeconomic status, living arrangements, and social involvement. ADL limitations increased pre-widowhood, were at higher levels immediately before and especially during the transition to widowhood, and increased at a steeper rate post-widowhood. Age and partially depressive symptoms accounted for these trends in ADL limitations pre-widowhood and to a lesser extent during the transition to widowhood and post-widowhood. Older age, being female, chronic conditions, financial strain, lower educational attainment, coresidence with children and others, and less frequent church attendance were risk factors for higher levels of and greater increases in these functional limitations throughout widowhood experience.