Urban vegetation cover correlates with environmental variables in a desert city: insights of mitigation measures to climate change

Urban Ecosystems - Green cover and air quality are important components of life quality and human ecology in arid lands. In the Sonoran Desert of Mexico, Hermosillo is the largest city with a...     

Comparative Perspectives on Social Indicators

Social Indicators Research -     

Accurate estimation for extra-Poisson variability assuming random effect models

In this study, the components of extra-Poisson variability are estimated assuming random effect models under a Bayesian approach. A standard existing methodology to estimate extra-Poisson variability assumes a negative binomial distribution. The obtained results show that using the proposed random effect model it is possible to get more accurate estimates for the extra-Poisson variability components when compared to the use of a negative binomial distribution where it is possible to estimate only one component of extra-Poisson variability. Some illustrative examples are introduced considering real data sets.     

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.     

Learning from a lot: Empirical Bayes for high‐dimensional model‐based prediction

Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, stored in public repositories. We review applications of a variety of empirical Bayes methods to several well‐known model‐based prediction methods, including penalized regression, linear discriminant analysis, and Bayesian models with sparse or dense priors. We discuss “formal” empirical Bayes methods that maximize the marginal likelihood but also more informal approaches based on other data summaries. We contrast empirical Bayes to cross‐validation and full Bayes and discuss hybrid approaches. To study the relation between the quality of an empirical Bayes estimator and p, the number of variables, we consider a simple empirical Bayes estimator in a linear model setting. We argue that empirical Bayes is particularly useful when the prior contains multiple parameters, which model a priori information on variables termed “co‐data”. In particular, we present two novel examples that allow for co‐data: first, a Bayesian spike‐and‐slab setting that facilitates inclusion of multiple co‐data sources and types and, second, a hybrid empirical Bayes–full Bayes ridge regression approach for estimation of the posterior predictive interval.     

Efficient Bayesian inference in generalized inverse gamma processes for stochastic volatility

This paper develops a novel and efficient algorithm for Bayesian inference in inverse Gamma stochastic volatility models. It is shown that by conditioning on auxiliary variables, it is possible to sample all the volatilities jointly directly from their posterior conditional density, using simple and easy to draw from distributions. Furthermore, this paper develops a generalized inverse gamma process with more flexible tails in the distribution of volatilities, which still allows for simple and efficient calculations. Using several macroeconomic and financial datasets, it is shown that the inverse gamma and generalized inverse gamma processes can greatly outperform the commonly used log normal volatility processes with Student’s t errors or jumps in the mean equation.     

“Migrant Capital” and Domestic Work: Labour Trajectories of Immigrant Women in Spain

This article analyses the labour trajectory of migrant women in domestic service. The research considers women's working conditions upon arrival, or their “migrant capital” (i.e. their human, social and economic capital) as the defining factors in their labour trajectories. The study, conducted on a sample of migrant women in domestic service, reveals the different value each type of capital has at each stage of a labour trajectory. The social network is the core capital in their first job. Nevertheless, the key factors in labour mobility are human capital and a household's financial needs. The processes of administrative regularization and family reunification prompt far‐reaching changes in these women's labour trajectories. Finally, labour trajectories during the economic crisis have been shaped by financial needs, leading to a decapitalization of the human capital acquired, with even legal status surrendering its value.     

The Global Compact for Safe,Orderly and Regular Migration: What's Next

The Director General of IOM reflects on the next steps to implement the Global Compact for Migration, IOM's new responsibility as Coordinator of the UN Migration Network, and the role that research can play in realizing the Compact's potential.     

The Role of Self-Conscious Emotions in the Sexual Health of Gay and Bisexual Men: Psychometric Properties and Theoretical Validation of the Sexual Shame and Pride Scale

Researchers have theorized about the role of sexual shame as a mechanism through which sexual minority stress manifests into mental health difficulties, such as sexual compulsivity for gay and bisexual men (GBM), and about the resilience-promoting effects of sexual pride. However, no validated measures to date have directly tapped into these constructs rather than using proxies for them, such as internalized homonegativity. We developed the Sexual Shame and Pride Scale (SSPS) and conducted a psychometric evaluation of it using a sample of 260 highly sexually active GBM. The scale had the expected structure in factor analysis and showed evidence of internal consistency and test–retest reliability. Correlational analyses demonstrated the convergent validity of sexual shame and sexual pride with relevant constructs. Regression analyses demonstrated the predictive validity of sexual shame in relation to sexual compulsivity, accounting for unique variability even after adjusting for previously demonstrated etiological factors, and the predictive validity of both shame and pride, which interacted to consistently predict four sexual behavior outcomes. Findings suggest the SSPS is a psychometrically valid and reliable measure that may be useful in future empirical work and highlight preliminary evidence for the role of these constructs in the sexual health of GBM.     

H-Day 1967 – An alternative perspective on “propaganda” in the historiography of public relation

This article presents an alternative perspective regarding the concept of “propaganda” in the historiography of public relations. Recent scholars of public relations have rightly criticized early attempts to write the field’s history as a linear progression, from propaganda to excellence. At the same time, however, the same recent scholars have come to accept a linear conceptual change, and that “propaganda” became an impossible term in liberal democratic countries in the 1960s. By using the empirical case of the massive communication efforts initiated by the Swedish Commission on Right-Hand Traffic, which was assigned to implement right-hand traffic in 1967, this article shows that the concept of “propaganda” both occurred frequently and was used in a neutral sense. To deepen the understanding of this alternative perspective, the article both presents how the historical actors conceptualized their work, and describes how the communication work of the Commission was performed.