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.

     

The Development of Multiple Self‐Concept Dimensions During Adolescence

The purpose of this research was to analyze the development of self‐concept during adolescence. Participants included 484 teenagers (226 boys and 258 girls) from middle‐class families in the Basque Country region of Spain (M_age = 14.99, SD = 1.81 in Time 1 and M_age = 15.64, SD = 1.80 in Time 2). Longitudinal analysis found differences in the general school dimension. Six dimensions (math, verbal, general school, physical abilities, parent relationships and same‐sex relationships) reported a linear trend with a decreasing monotonic pattern; self‐esteem fit a cubic trend and physical appearance a quadratic trend line. Males showed higher means in self‐esteem, math, physical abilities, physical appearance, emotional stability and parent relationships; and females had higher values in verbal and general school.     

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.     

Dynamic Updating of Labour Force Estimates: JARES

Abstract. In this paper a new algorithm is proposed in order to produce an automatic dynamic compound estimator of the labour force based on an interactive scheme. The proposed algorithm, JARES, is based on the probability estimator of Jaynes based on the notion of maximum entropy of a given probability distribution with a constraint on the average of an external information. The iterative scheme is based on the solution of a set of linear equations which represent the algebraic relationships between the weights and the estimates.     

Cytometry inference through adaptive atomic deconvolution

In this paper, we consider a statistical estimation problem known as atomic deconvolution. Introduced in reliability, this model has a direct application when considering biological data produced by flow cytometers. From a statistical point of view, we aim at inferring the percentage of cells expressing the selected molecule and the probability distribution function associated with its fluorescence emission. We propose here an adaptive estimation procedure based on a previous deconvolution procedure introduced by Es, Gugushvili, and Spreij [(2008), ‘Deconvolution for an atomic distribution’, Electronic Journal of Statistics, 2, 265–297] and Gugushvili, Es, and Spreij [(2011), ‘Deconvolution for an atomic distribution: rates of convergence’, Journal of Nonparametric Statistics, 23, 1003–1029]. For both estimating the mixing parameter and the mixing density automatically, we use the Lepskii method based on the optimal choice of a bandwidth using a bias-variance decomposition. We then derive some convergence rates that are shown to be minimax optimal (up to some log terms) in Sobolev classes. Finally, we apply our algorithm on the simulated and real biological data.     

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).