Bootstrap Algorithms for Testing and Determining the Cointegration Rank in VAR Models1

In this paper a bootstrap algorithm for a reduced rank vector autoregressive model with a restricted linear trend and independent, identically distributed errors is analyzed. For testing the cointegration rank, the asymptotic distribution under the hypothesis is the same as for the usual likelihood ratio test, so that the bootstrap is consistent. It is furthermore shown that a bootstrap procedure for determining the rank is asymptotically consistent in the sense that the probability of choosing the rank smaller than the true one converges to zero.     

Statistical Corrections of Invalid Correlation Matrices

Suppose estimates are available for correlations between pairs of variables but that the matrix of correlation estimates is not positive definite. In various applications, having a valid correlation matrix is important in connection with follow‐up analyses that might, for example, involve sampling from a valid distribution. We present new methods for adjusting the initial estimates to form a proper, that is, nonnegative definite, correlation matrix. These are based on constructing certain pseudo‐likelihood functions, formed by multiplying together exact or approximate likelihood contributions associated with the individual correlations. Such pseudo‐likelihoods may then be maximized over the range of proper correlation matrices. They may also be utilized to form pseudo‐posterior distributions for the unknown correlation matrix, by factoring in relevant prior information for the separate correlations. We illustrate our methods on two examples from a financial time series and genomic pathway analysis.     

Incomplete equalization: The effect of tracking in secondary education on educational inequality

This paper tests whether the existence of vocationally oriented tracks within a traditionally academically oriented upper education system reduces socioeconomic inequalities in educational attainment. Based on a statistical model of educational transitions and data on two entire cohorts of Danish youth, we find that (1) the vocationally oriented tracks are less socially selective than the traditional academic track; (2) attending the vocationally oriented tracks has a negative effect on the likelihood of enrolling in higher education; and (3) in the aggregate the vocationally oriented tracks improve access to lower-tier higher education for low-SES students. These findings point to an interesting paradox in that tracking has adverse effects at the micro-level but equalizes educational opportunities at the macro-level. We also discuss whether similar mechanisms might exist in other educational systems.     

News: University prizes

Abstract

Stressful working environments are often assumed to create conditions that may lead to bullying. However, few studies have investigated how factors experienced in the work environment may trigger perpetrators to engage in bullying of others. Drawing on Spector and Fox's (2005) stressor–emotion model of counterproductive work behaviour, the present study investigated the predictive effects of both individual and situational factors as predictors of being a perpetrator of workplace bullying, as applied to a representative sample of the Norwegian workforce (N=2359). Results from logistic regression analysis show that being oneself a target of bullying, regardless of the frequency, and being male strongly predicted involvement in bullying of others. Among the situational factors, only role conflict and interpersonal conflicts significantly predicted being a perpetrator of bullying. The present findings support the notion that bullying will thrive in stressful working environments and thus yield an important contribution in identifying antecedent conditions to counteract the development of bullying at workplaces.     

Job characteristics as predictors of ill-health and sickness absenteeism in different occupational types--a multigroup structural equation modelling approach

The objective of the present study was to test for multigroup invariance in measurement models and structural models between job characteristics, psychosocial intervening variables, health outcomes and sickness absenteeism. Four types of occupation were represented in the study: blue-collar workers ( n = 241), white-collar workers ( n = 209), elderly-care workers ( n = 338) and child-care workers ( n = 336). A first-order, six-factor multigroup confirmatory factor analysis model (i.e. measurement model) composed of two perceived job characteristics ( job autonomy and skill discretion), appraised workload, job satisfaction, stress-related ill-health and sickness absenteeism provided a good model fit. Invariance tests showed that the six-factor model fits well for all occupations. A partially recursive mediated multigroup structural model showed both similarities and differences across occupations as regards the relationships between independent latent variables ( job autonomy, skill discretion), intervening latent variables (appraised workload, job satisfaction) and dependent latent variables (stressrelated ill-health, sickness absenteeism). By comparing a generic model with occupation-specific models across occupations, this study showed that occupation-specific models were more plausible. The results indicate that it is important to examine different occupational contexts in detail to better understand how certain psychosocial factors at work influence strain in different occupations. Since job characteristics can potentially be amended, the findings have important implications for the differentiation of prevention and intervention in different occupations.     

Correction to: Think Tanks: New Organizational Actors in a Changing Swedish Civil Society

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - In the captions for Figures 1 and 2, a reference was inadvertently omitted.