Mitigating the political participation gap from the school: the roles of civic knowledge and classroom climate

Empirical evidence has consistently shown that political participation is positively related with socioeconomic background. Furthermore, recent research suggests that children who come from low status families are already less willing to get politically involved. The present paper aims to analyze the possible impact that schools can have in mitigating the effect of parents' socioeconomic status on students' expected electoral participation, focusing on two variables: civic knowledge and classroom climate. The analyses are based on a series of multilevel models using Chilean data of the International Civic and Citizenship Education Study 2009. The results support the influence of students' socioeconomic background on expected electoral participation. Furthermore, civic knowledge and classroom climate show a positive and similar influence on students' expected participation. However, classroom climate appears less affected by students' background than civic knowledge, opening the discussion about which strategy should be emphasized when aiming to mitigate the political participation gap.     

Joint regression modeling for missing categorical covariates in generalized linear models

Missing covariates data is a common issue in generalized linear models (GLMs). A model-based procedure arising from properly specifying joint models for both the partially observed covariates and the corresponding missing indicator variables represents a sound and flexible methodology, which lends itself to maximum likelihood estimation as the likelihood function is available in computable form. In this paper, a novel model-based methodology is proposed for the regression analysis of GLMs when the partially observed covariates are categorical. Pair-copula constructions are used as graphical tools in order to facilitate the specification of the high-dimensional probability distributions of the underlying missingness components. The model parameters are estimated by maximizing the weighted log-likelihood function by using an EM algorithm. In order to compare the performance of the proposed methodology with other well-established approaches, which include complete-cases and multiple imputation, several simulation experiments of Binomial, Poisson and Normal regressions are carried out under both missing at random and non-missing at random mechanisms scenarios. The methods are illustrated by modeling data from a stage III melanoma clinical trial. The results show that the methodology is rather robust and flexible, representing a competitive alternative to traditional techniques.     

US and them: Job quality differences between natives and immigrants in Europe

Using microdata from the European Union Labour Force Survey (EU-LFS) and aggregate indicators of labour market institutions, this article compares the job quality of native and non-native workers across European countries and analyses the impact of the institutional settings on the job quality differential between both groups. The LFS is used to measure a job quality index for the period 2005–2017. We find that some immigrant groups fare worse than natives, the contribution of the “composition effect” to explain this differential is large, and the institutional framework affects the immigration gap in job quality. In particular, some labour market institutions (more centralized wage bargaining, stricter employment protection legislation) tend to be detrimental for immigrants relative to natives, while integration policies seem to work well in reducing these differences.     

Consistent Testing of Cointegrating Relationships

In this paper we investigate methods for testing the existence of a cointegration relationship among the components of a nonstationary fractionally integrated (NFI) vector time series. Our framework generalizes previous studies restricted to unit root integrated processes and permits simultaneous analysis of spurious and cointegrated NFI vectors. We propose a modified F‐statistic, based on a particular studentization, which converges weakly under both hypotheses, despite the fact that OLS estimates are only consistent under cointegration. This statistic leads to a Wald‐type test of cointegration when combined with a narrow band GLS‐type estimate. Our semiparametric methodology allows consistent testing of the spurious regression hypothesis against the alternative of fractional cointegration without prior knowledge on the memory of the original series, their short run properties, the cointegrating vector, or the degree of cointegration. This semiparametric aspect of the modelization does not lead to an asymptotic loss of power, permitting the Wald statistic to diverge faster under the alternative of cointegration than when testing for a hypothesized cointegration vector. In our simulations we show that the method has comparable power to customary procedures under the unit root cointegration setup, and maintains good properties in a general framework where other methods may fail. We illustrate our method testing the cointegration hypothesis of nominal GNP and simple‐sum (M1, M2, M3) monetary aggregates.     

Transnational social protection infrastructures: African migrants in Mexico

In the past years, increasingly restrictive migration policies have pushed many migrants to seek new and more risky migration routes. Many studies have investigated aspects of social protection for migrants from the Global South in industrialized countries of the Global North, with powerful welfare states. Yet, such focus has failed to understand the complexities during the migration process, where people often spend uncertain periods of time in transit countries and the state is frequently absent. In these contexts, social protection is predominantly provided by the third sector (TS) and informal networks both nationally and transnationally. Based on ethnographic fieldwork conducted with African migrants and TS organizations in Mexico, this paper explores the different and often semi-formal relationships between the TS, the state, and the migrants that result in complex transnational social protection infrastructures to cover the migrants' basic social protection needs.