Transform orders and stochastic monotonicity of statistical functionals

In some inferential statistical methods, such as tests and confidence intervals, it is important to describe the stochastic behavior of statistical functionals, aside from their large sample properties. We study such a behavior in terms of the usual stochastic order. For this purpose, we introduce a generalized family of stochastic orders, which is referred to as transform orders, showing that it provides a flexible framework for deriving stochastic monotonicity results. Given that our general definition makes it possible to obtain some well known ordering relations as particular cases, we can easily apply our method to different families of functionals. These include some prominent inequality measures, such as the generalized entropy, the Gini index, and its generalizations. We also illustrate the applicability of our approach by determining the least favorable distribution, and the behavior of some bootstrap statistics, in some goodness-of-fit testing procedures.     

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.     

A flexible link for joint modelling longitudinal and survival data accounting for individual longitudinal heterogeneity

Statistical Methods & Applications - This work aims at jointly modelling longitudinal and survival HIV data by considering the sharing of a set of parameters of interest. For the CD4...     

Predicting burrowing owl flight trajectories in urban environments

Urban Ecosystems - It is important to understand how animals respond to changes in landscape structure, especially when considering habitat alteration and urbanization. Using the burrowing owl...     

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.