Estimation and Properties of a Time-Varying EGARCH(1,1) in Mean Model

Time-varying GARCH-M models are commonly employed in econometrics and financial economics. Yet the recursive nature of the conditional variance makes likelihood analysis of these models computationally infeasible. This article outlines the issues and suggests to employ a Markov chain Monte Carlo algorithm which allows the calculation of a classical estimator via the simulated EM algorithm or a simulated Bayesian solution in only O(T) computational operations, where T is the sample size. Furthermore, the theoretical dynamic properties of a time-varying-parameter EGARCH(1,1)-M are derived. We discuss them and apply the suggested Bayesian estimation to three major stock markets.     

Adolescent Online Gambling in Cyprus: Associated School Performance and Psychopathology

This paper presents results from the study of gambling behaviors in a representative sample of Cypriot high-school students. The aim of the study was to ascertain epidemiology of adolescent online gambling in Cyprus and possible correlates. The sample consisted of 2,684 students (48.5 % boys, 51.5 % girls) from the first grades of junior (Gymnasium) and senior (Lyceum) high school. Our results indicate that gamblers presented with lower school achievement and related expectations while scoring consistently higher on measures of Internet addiction, parental bonding and psychopathology. Discriminant analysis revealed two profiles which explained the most variance in gambling behavior; the first profile that corresponded to more explained variance was the student with higher psychopathology, less prosocial behavior, higher Internet addiction score with higher frequencies of online activities and moderate levels of truancy and lower expectation of school achievement. The second profile was that of a student who reported less psychopathology, more prosocial behavior, less involvement with the Internet in general but skipped classes more and his prospects on finishing high school were even slimmer. These results will be utilized in the design of a comprehensive prevention program in an effort to combat online addictive behaviors.     

From Bureaucracy to Debureaucratization?

More than previous mild recessions, the current global crisis calls into question the merits of a model that held sway for almost three decades. Celebrated in the nineties in a “National Bestseller”, which even President Clinton considered to be a “blueprint” “for all officials to read”, the book—Reinventing Government—preached the reform of government in private sector ways. In stark contrast to Bureaucracy, which they considered “Bankrupt”. Authors Osborne and Gaebler (1993) promoted Debureaucratization, which they summed up as decentralization, deregulation, downsizing and outsourcing. It is time to revisit the assumptions of the Osborne-Gaebler model that has demonstrably failed. More than the model, however, the ways of its promotion in the market of ideas invites a word of caution. It prompted simplistic distortions, which typically followed from superficial analyses of Weber’s seminal opus (Timsit 2008:864–875). This paper reconsiders these two contrasting models, though not in “black” and “white”. Rather, the two are explored in dialectical terms, as outcomes of shifting ideologies, often taken to extremes.     

Edgeworth and Moment Approximations: The Case of MM and QML Estimators for the MA(1) Models

Extending the results in Sargan (1976 Sargan , J. D. ( 1976 ). Econometric estimators and the Edgeworth approximation . Econometrica 44 : 421 – 448 .[Crossref], [Web of Science ®] , [Google Scholar]) and Tanaka (1984 Tanaka , K. ( 1984 ). An asymptotic expansion associated with the maximum likelihood estimators in ARMA models . J. Roy. Statist. Soc. B 46 : 58 – 67 . [Google Scholar]), we derive the asymptotic expansions of the distribution, the bias and the mean squared error of the MM and QML estimators of the first-order autocorrelation and the MA parameter for the MA(1) model. It turns out that the asymptotic properties of the estimators depend on whether the mean of the process is known or estimated. A comparison of the moment expansions, either in terms of bias or MSE, reveals that there is not uniform superiority of neither of the estimators, when the mean of the process is estimated. This is also confirmed by simulations. In the zero-mean case, and on theoretical grounds, the QMLEs are superior to the MM ones in both bias and MSE terms. We also discuss how the approximations are affected by moderate deviations from the unit root case. The results presented here are important for bias correction and increasing the efficiency of the estimators.     

Graphical Tests for the Frailty Distribution in the Shared Frailty Model

We extend a diagnostic plot for the frailty distribution in proportional hazards models to the case of shared frailty. The plot is based on a closure property of exponential family failure distributions with canonical statistics z and g(z), namely that the frailty distribution among survivors at time t has the same form, with the same values of the parameters associated with g(z). We extend this property to shared frailty, considering various definitions of a “surviving” cluster at time t. We illustrate the effectiveness of the method in the case where the “death” of the cluster is defined by the first death among its members.     

The EC hotspot approach in Greece: creating liminal EU territory

ABSTRACT

This article makes a theoretical argument stemming from our study of the European Commission’s hotspot approach to the management of migrant populations. It draws on empirical research findings from field research which took place on the island of Lesbos and in the city of Athens over the course of 20 months and links these to emerging critical studies of the new EU border regime. No clear definition exists of what comprises a hotspot: instead, the European Commission describes this as an integrated ‘approach’ for the enhancement of the capacity of member states to deal with crises resulting from pressures at the Union’s external borders. Effective in its ambiguity, the ‘hotspot approach’ therefore constitutes, as we argue, an integral part of the Europeanisation and institutionalisation of border management: a powerfully ambiguous dispositif in the EU’s emerging border regime. The article unpacks the notion of the hotspot from a historical perspective and explores the ways in which the hotspot contributes toward the culmination of European integration, paving the way for the flexible governance of mobility and asylum. We situate the hotspot within the historical shift of migration and mobility control from the border to the territory as a whole and conclude by arguing that the hotspot plays the role of a territorial incubator for the liminal EU territory: a paradigmatic space for a new form of governance that further disentangles territory from rights.     

Join the Union and Be Safe: The Effects of Unionization on Occupational Safety and Health in the European Union

This paper investigates the effect of unionization on occupational safety and health, as measured by the fatal and non‐fatal work accidents, after controlling for the country's gross domestic product. It uses a panel sample of 10 European Union countries, for the period 1982–2006. The study takes into account the time persistence in work injuries and the endogenous nature of the work injuries–union density relationship. In addition, the effect of union density is decomposed into a temporary and permanent effect. It is shown that increasing union density is associated with a decrease in the number of both fatal and non‐fatal work injuries.     

Modelling survival data using mixtures of frailties

Frailty models are often used to describe the extra heterogeneity in survival data by introducing an individual random, unobserved effect. The frailty term is usually assumed to act multiplicatively on a baseline hazard function common to all individuals. In order to apply the frailty model, a specific frailty distribution has to be assumed. If at least one of the latent variables is continuous, the frailty must follow a continuous distribution. In this paper, a finite mixture of continuous frailty distributions is used in order to describe situations in which one (or more) of the latent variables separates the population in study into two (or more) subpopulations. Closure properties of the unobserved quantity are given along with the maximum-likelihood estimates under the most common choices of frailty distributions. The model is illustrated on a set of lifetime data.