The Welfare State as Safety Net in Migration Preferences: Empirical Evidence from an Experiment Among Dutch Master Students

Population Research and Policy Review - The welfare state can be perceived as a safety net which helps individuals adjust to situations of risk or transition. Starting from this idea of the welfare...     

Bayesian model selection and parameter estimation for possibly asymmetric and non-stationary time series using a reversible jump Markov chain Monte Carlo approach

A Markov chain Monte Carlo (MCMC) approach, called a reversible jump MCMC, is employed in model selection and parameter estimation for possibly non-stationary and non-linear time series data. The non-linear structure is modelled by the asymmetric momentum threshold autoregressive process (MTAR) of Enders & Granger (1998) or by the asymmetric self-exciting threshold autoregressive process (SETAR) of Tong (1990). The non-stationary and non-linear feature is represented by the MTAR (or SETAR) model in which one ( 𝜌 1 ) of the AR coefficients is greater than one, and the other ( 𝜌 2 ) is smaller than one. The other non-stationary and linear, stationary and nonlinear, and stationary and linear features, represented respectively by ( 𝜌 1 = 𝜌 2 = 1 ), ( 𝜌 1 p 𝜌 2 < 1 ) and ( 𝜌 1 = 𝜌 2 < 1 ), are also considered as possible models. The reversible jump MCMC provides estimates of posterior probabilities for these four different models as well as estimates of the AR coefficients 𝜌 1 and 𝜌 2 . The proposed method is illustrated by analysing six series of US interest rates in terms of model selection, parameter estimation, and forecasting.     

Patterns and Drivers of Emigration of the Turkish Second Generation in the Netherlands

European Journal of Population - Using unique longitudinal data from the Dutch population registers, this study investigates the patterns and drivers of emigration of the Turkish second generation...     

International and internal migration decision making: a value-expectancy based analytical framework of intentions to move from a rural Philippine province

"The study compares determinants of internal and international migration intentions, drawing upon interview data from a sample of adults in Ilocos Norte, a largely rural province in the Philippines. A regression model is applied to test the relative determinants of intentions to migrate to Manila and to Hawaii. The study is based on a value-expectancy model of migration decision making. The results document the importance of subjective expectations related to the attainment of different values and goals in Manila and Hawaii."     

Internalized Other Interviewing in Relational Therapy: Three Discursive Approaches to Understanding its Use and Outcomes

For over 20 years, family therapist Karl Tomm has been engaging families and couples with a therapeutic intervention he calls Internalized Other Interviewing (IOI). The IOI (cf. Emmerson‐Whyte, 2010; Hurley, 2006) entails interviewing clients, from the personal experiences of partners and family members as an internalized other. The IOI is based on the idea that through dialogues over time, one can internalize a sense of one's conversational partner responsiveness in reliably anticipated ways. Anyone who has thought in a conversation with a family member or partner, “Oh there s/he goes again,” or anticipates next words before they leave the other's mouth, has a sense of what we are calling an internalized other. For Tomm, the internalized anticipations partners and family members may have offers entry points into new dialogues with therapeutic potential—particularly, when their actual dialogues get stuck in dispreferred patterns.     

Dyadic Analyses of Preschool‐aged Children's Friendships: Convergence and Differences between Friendship Classifications from Peer Sociometric Data and Teacher's Reports

Peer sociometrics and teachers' friendship reports were compared in 2179 preschool dyads. One hundred twenty of 306 reciprocated friend dyads from peer sociometric data were also identified as good friends by their classroom teachers, and 301 of 600 of non‐reciprocated dyads in peer data were named as friends by one or both classroom teachers (overall kappa = .16). Friendship classifications from both peer and teacher data had significant relations with variables relevant to peer interactions, social skills, peer acceptance, and teacher‐rated scales (six of seven tests significant for peer data; five of eight significant for teacher data). Multilevel analyses indicated that friendship status effects were not qualified by classroom‐level differences. Findings suggest that sociometric tasks can identify preschoolers' peer friendships and that the range of correlates may be broader in peer‐choice data than in teachers' friendship evaluations.     

Religious Attendance,Stress, and Happiness in South Korea: Do Gender and Religious Affiliation Matter?

Is religious attendance positively associated with happiness in South Korea? If yes, can religious attendance buffer against the harmful effect of stress on happiness? Moreover, do gender and religious affiliation modify these associations? This study addresses these questions with data from 2009 Korean General Social Survey which is a nationally representative survey (N = 1,599). Ordinal least square regression analyses reveal that although the effect size is relatively small, religious attendance is associated with a higher level of happiness in South Korea. However, this positive effect holds only for women and only for Protestants. In addition, an interaction effect between religious attendance and stress is observed for women only; the negative association between stress and happiness is weakened among those women who report more frequent church attendance. In this regard, a high level of church attendance buffers against the deleterious effects of stress on happiness for women. I discuss the implications of the findings with regard to theories about religion, mental health, and gender in South Korean context.     

A modified LGB method for detecting significant effects based on a half-normal probability plot

In analyzing data from unreplicated factorial designs, the half-normal probability plot is commonly used to screen for the ‘vital few’ effects. Recently, many formal methods have been proposed to overcome the subjectivity of this plot. Lawson (1998) (hereafter denoted as LGB) suggested a hybrid method based on the half-normal probability plot, which is a blend of Lenth (1989) and Loh (1992) method. The method consists of fitting a simple least squares line to the inliers, which are determined by the Lenth method. The effects exceeding the prediction limits based on the fitted line are candidates for the vital few effects. To improve the accuracy of partitioning the effects into inliers and outliers, we propose a modified LGB method (hereafter denoted as the Mod_LGB method), in which more outliers can be classified by using both the Carling’s modification of the box plot (Carling, 2000) and Lenth method. If no outlier exists or there is a wide range in the inliers as determined by the Lenth method, more outliers can be found by the Carling method. A simulation study is conducted in unreplicated $2^4$ designs with the number of active effects ranging from 1 to 6 to compare the efficiency of the Lenth method, original LGB methods, and the proposed modified version of the LGB method.