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.     

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.     

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.     

Information systems project failure – analysis of causal links using interpretive structural modelling

The analysis of the root causes of information systems project failure has been the subject of intense scrutiny for some time within industry and the academic community. Researchers have developed various models, notions of failure and categorisations to succinctly classify project failure into a set of key factors for organisations and project managers to focus on in their attempts to avoid failure. This study incorporates a technique titled: interpretive structural modelling as the methodology to formalise the relationships between the selected failure factors. This approach is positioned as a mechanism that can yield greater insights into the relationships between the factors surrounding project failure, thereby developing a better understanding of how these relationships can have a bearing on project outcomes. The findings identify key driving variables that are presented as having significant impact on the other factors within the model. A number of variables are also identified as being heavily dependent on other connected factors highlighting that a failure in one or more of these connected factors is likely to result in a failure in one or more of the dependent factors unless timely steps are taken to address these key issues. This research details a number of practical implications for senior management and project managers as well as the academic community. These considerations form an underlying thread within this study as specific practice-related implications are highlighted and discussed throughout the study.     

Case study: shipping trend estimation and prediction via multiscale variance stabilisation

Shipping and shipping services are a key industry of great importance to the economy of Cyprus and the wider European Union. Assessment, management and future steering of the industry, and its associated economy, is carried out by a range of organisations and is of direct interest to a number of stakeholders. This article presents an analysis of shipping credit flow data: an important and archetypal series whose analysis is hampered by rapid changes of variance. Our analysis uses the recently developed data-driven Haar–Fisz transformation that enables accurate trend estimation and successful prediction in these kinds of situation. Our trend estimation is augmented by bootstrap confidence bands, new in this context. The good performance of the data-driven Haar–Fisz transform contrasts with the poor performance exhibited by popular and established variance stabilisation alternatives: the Box–Cox, logarithm and square root transformations.     

Interference Phenomena in Temporal Evolution of Accident Probability in Workplaces

The aim of this article is to investigate some implications of complexity in workplace risk assessment. Workplace is examined as a complex system, and some of its attributes and aspects of its behavior are investigated. Failure probability of various workplace elements is examined as a time variable and interference phenomena of these probabilities are presented. Potential inefficiencies of common perceptions in applying probabilistic risk assessment models are also discussed. This investigation is conducted through mathematical modeling and qualitative examples of workplace situations. A mathematical model for simulation of the evolution of workplace accident probability in time is developed. Its findings are then attempted to be translated in real-world terms and discussed through simple examples of workplace situations. The mathematical model indicates that workplace is more likely to exhibit an unpredictable behavior. Such a behavior raises issues about usual key assumptions for the workplace, such as aggregation. Chaotic phenomena (nonlinear feedback mechanisms) are also investigated for in simple workplace systems cases. The main conclusions are (1) that time is an important variable for risk assessment, since behavior patterns are complex and unpredictable in the long term and (2) that workplace risk identification should take place in a holistic view (not by work post).     

Decisive FDI obstacles as an explanatory reason for limited FDI inflows in an EMU member state: The case of Greece

A questionnaire survey covering MNCs that had invested in Greece during the period 1995–2003 is carried out in order to determine the barriers of inward FDI in Greece through a phase of increased expectations on foreign investment from hosting the 2004 Olympiad. The underlying assumption made is that the views of the local managers reflect the views of the mother company when deciding to invest. Although the findings represent the time that the investment took place, the influence of the conditions shaping the economic environment at the time the survey was carried out is also discussed. The findings indicate that the primary barriers to foreign investors are bureaucracy, taxation, corruption, and the labor market structure and support those of previous quantitative studies, leading to the conclusion that there is no progress made regarding these factors, in order to enhance FDI attractiveness. It becomes crucial for Greece to modernize and upgrade state mechanisms, through a more effective organization and administrative policies.