The multiplicity of citizenship: transnational and local practices and identifications of middle‐class migrants

In this article we focus on local and transnational forms of active citizenship, understood as the sum of all political practices and processes of identification. Our study, conducted among middle‐class immigrants in Rotterdam, the Netherlands, indicates that the importance of active transnational citizenship should not be overstated. Among these immigrants, political practices are primarily focused on the local level; political practices directed to the home country appear to be quite rare. However, although transnational activities in the public sphere are rather exceptional, many immigrants do participate in homeland‐directed activities in the private sphere. If we look at processes of identification, we see that a majority of the middle‐class immigrants have a strong local identity. Many of them combine this local identification with feelings of belonging to people in their home country.     

Reactive transnationalism: homeland involvement in the face of discrimination

In this article we examine whether migrants' perceived discrimination in the country of settlement leads to an increase of their transnational involvement. So far, this so‐called ‘reactive transnationalism’ has not been studied extensively. Based on literature on discrimination and transnationalism, reactive transnationalism is expected to be most prominent among socioeconomically successful migrants, particularly among males and those who consider themselves Muslims. Our research among middle‐class migrants in Rotterdam, the Netherlands, indeed shows that the more respondents experienced discrimination, the more transnationally involved they are, both regarding transnational identifications and transnational activities. While no gender difference was found regarding reactive transnational activities, for women perceived discrimination proves to lead to stronger instead of weaker transnational identifications than for men. The fact that no difference was found between Muslim and non‐Muslim respondents regarding reactive transnationalism suggests that, despite heated public debates about ‘Islam’, in the Netherlands, ethnic divides – being considered as ‘Dutch’ or ‘non‐Dutch’ – are even more prominent than religious ones.     

ECONOMICS COURSEWORK AND LONG‐TERM BEHAVIOR AND EXPERIENCES OF COLLEGE GRADUATES IN LABOR MARKETS AND PERSONAL FINANCE

Using survey data from over 2,000 students who attended one of four large public universities in 1976, 1986, or 1996, we investigate the relationship between taking more coursework in economics, or choosing economics as an undergraduate major, and a wide range of later decisions and outcomes in labor markets and personal finance, many of which have not been analyzed in earlier research. Generally, economics coursework and majoring in economics are significantly related to higher levels of earnings, home equity, and savings. They are also associated with working more hours and negatively related to completing graduate degrees (except the MBA). Among graduates with positive savings, those with more economics coursework invest more in individual stocks and money market accounts, and are more likely to have employer‐provided life insurance. They have fewer credit cards, which are more often paid in full each month. Most of these findings also hold for graduates who majored in business, but on average economics majors worked more hours and earned more than business majors, were more likely to have been self‐employed, and expected to retire at an older age. Business majors were more likely to have experienced a layoff, and were even less likely than economics majors to complete graduate degrees (except the MBA). Economics majors expected to save even more than business majors by retirement, and viewed short‐term and precautionary motives for saving as more important. Finally, our results suggest that exposure to economics through course‐taking is more important for later outcomes than actual performance in those courses. (JEL A22, J3, D12)     

Asymptotic Normality of Kernel-Type Deconvolution Estimators

Abstract.  We derive asymptotic normality of kernel-type deconvolution estimators of the density, the distribution function at a fixed point, and of the probability of an interval. We consider so-called super smooth deconvolution problems where the characteristic function of the known distribution decreases exponentially, but faster than that of the Cauchy distribution. It turns out that the limit behaviour of the pointwise estimators of the density and distribution function is relatively straightforward, while the asymptotic behaviour of the estimator of the probability of an interval depends in a complicated way on the sequence of bandwidths.     

Estimation for High‐Dimensional Linear Mixed‐Effects Models Using ℓ1‐Penalization

Abstract. We propose an ?₁‐penalized estimation procedure for high‐dimensional linear mixed‐effects models. The models are useful whenever there is a grouping structure among high‐dimensional observations, that is, for clustered data. We prove a consistency and an oracle optimality result and we develop an algorithm with provable numerical convergence. Furthermore, we demonstrate the performance of the method on simulated and a real high‐dimensional data set.     

A New Kernel Distribution Function Estimator Based on a Non-parametric Transformation of the Data

Abstract.  A new kernel distribution function (df) estimator based on a non-parametric transformation of the data is proposed. It is shown that the asymptotic bias and mean squared error of the estimator are considerably smaller than that of the standard kernel df estimator. For the practical implementation of the new estimator a data-based choice of the bandwidth is proposed. Two possible areas of application are the non-parametric smoothed bootstrap and survival analysis. In the latter case new estimators for the survival function and the mean residual life function are derived.     

Uniform Representation of Product-Limit Integrals with Applications

Abstract.  Let X be a d -variate random vector that is completely observed, and let Y be a random variable that is subject to right censoring and left truncation. For arbitrary functions φ we consider expectations of the form E [ φ ( X ,  Y )], which appear in many statistical problems, and we estimate these expectations by using a product-limit estimator for censored and truncated data, extended to the context where covariates are present. An almost sure representation for these estimators is obtained, with a remainder term that is of a certain negligible order, uniformly over a class of φ -functions. This uniformity is important for the application to goodness-of-fit testing in regression and to inference for the regression depth, which we consider in more detail.