Autoregressive Moving Average Infinite Hidden Markov-Switching Models

Markov-switching models are usually specified under the assumption that all the parameters change when a regime switch occurs. Relaxing this hypothesis and being able to detect which parameters evolve over time is relevant for interpreting the changes in the dynamics of the series, for specifying models parsimoniously, and may be helpful in forecasting. We propose the class of sticky infinite hidden Markov-switching autoregressive moving average models, in which we disentangle the break dynamics of the mean and the variance parameters. In this class, the number of regimes is possibly infinite and is determined when estimating the model, thus avoiding the need to set this number by a model choice criterion. We develop a new Markov chain Monte Carlo estimation method that solves the path dependence issue due to the moving average component. Empirical results on macroeconomic series illustrate that the proposed class of models dominates the model with fixed parameters in terms of point and density forecasts.     

The Cassa Integrazione Guadagni

ABSTRACT: The purpose of this paper is to provide an analytical survey of the historical and normative evolution of the Italian Cassa Integrazione Guadagni (hereafter Earnings Integration Fund or EIF) through examination of the prevalent economic and juridical models during the 40 years of the EIF's existence. The evolution of the EIF in the periods examined is classified according to five theoretical models, so as to bring out the many different standards accumulated during the administration of the EIF, and the many measures adopted by Public Authorities in response to the various requirements which have arisen over time. The result is an overall reference framework for the EIF's present administration, which is characterised by the presence of both the need for various reforms and alterations, and an equal number of ways of carrying them out; from the development of an ever more direct link between crisis situations and specific EIF requirements, and the evident need to bring the institution within a normative framework correlated to a global labour policy. A verification of the different methods of utilising the EIF is therefore, for the authors, utilizable in defining suitable solutions for modern situations, which require effective EIF models to be worked out in conjunction with an appropriate mix of active labour policies.     

A Spatio‐Temporal Exposure‐Hazard Model for Assessing Biological Risk and Impact

We developed a simulation model for quantifying the spatio‐temporal distribution of contaminants (e.g., xenobiotics) and assessing the risk of exposed populations at the landscape level. The model is a spatio‐temporal exposure‐hazard model based on (i) tools of stochastic geometry (marked polygon and point processes) for structuring the landscape and describing the exposed individuals, (ii) a dispersal kernel describing the dissemination of contaminants from polygon sources, and (iii) an (eco)toxicological equation describing the toxicokinetics and dynamics of contaminants in affected individuals. The model was implemented in the briskaR package (b iological risk a ssessment with R ) of the R software. This article presents the model background, the use of the package in an illustrative example, namely, the effect of genetically modified maize pollen on nontarget Lepidoptera, and typical comparisons of landscape configurations that can be carried out with our model (different configurations lead to different mortality rates in the treated example). In real case studies, parameters and parametric functions encountered in the model will have to be precisely specified to obtain realistic measures of risk and impact and accurate comparisons of landscape configurations. Our modeling framework could be applied to study other risks related to agriculture, for instance, pathogen spread in crops or livestock, and could be adapted to cope with other hazards such as toxic emissions from industrial areas having health effects on surrounding populations. Moreover, the R package has the potential to help risk managers in running quantitative risk assessments and testing management strategies.     

Youths' Organized Activities and Adjustment in Emerging Adulthood: A Multidimensional Conception of Participation

This longitudinal study examined how participation in organized activities during adolescence (ages 14–17) is associated with adjustment in emerging adulthood (age 21). It investigated the contribution of three dimensions of participation: activity portfolios (i.e., specific combinations of activity types), intensity, and duration. The sample included 287 Canadian adolescents. First, distinct activity portfolios were identified using a person‐centered approach. Second, differences between portfolios were examined with regard to salient indicators of adjustment in emerging adulthood: depressive symptoms, problematic alcohol use, educational status, and civic engagement. Third, the contributions of participation intensity and duration were examined. Results revealed that certain portfolios were related in distinct ways to specific outcomes and that these differences depended on intensity or duration of participation.     

Information criteria for inhomogeneous spatial point processes

The theoretical foundation for a number of model selection criteria is established in the context of inhomogeneous point processes and under various asymptotic settings: infill, increasing domain and combinations of these. For inhomogeneous Poisson processes we consider Akaike's information criterion and the Bayesian information criterion, and in particular we identify the point process analogue of ‘sample size’ needed for the Bayesian information criterion. Considering general inhomogeneous point processes we derive new composite likelihood and composite Bayesian information criteria for selecting a regression model for the intensity function. The proposed model selection criteria are evaluated using simulations of Poisson processes and cluster point processes.     

Employee strain and job satisfaction related to an implementation of quality in a public service organization: A longitudinal study

To date, few studies have focused on employee reactions to the quality-related aspects of the introduction of New Public Management (NPM). The aim of this study was to investigate the effects on employee strain and satisfaction of the implementation NPM in a public service organization. The study was designed as an empirical examination of the 'context-dependent approach' ( Edwards, Collinson, & Rees, 1998 ). This approach suggests that effects of an organizational change depend on the context of the implementation, i.e. organizational aspects (implementation strategies), job content and job context dimensions. They employed a single-case longitudinal design. The case was a large municipal service unit responsible for the public housing system of a city in Austria. The sample consisted of 217 employees. Measurements were taken before the organizational change, and at two different times during the change process. While the implementation of NPM can be considered to have been an organizational success (increase in customer satisfaction), it was accompanied by increases in job strain, and, at the same time, mixed results in job satisfaction. Less qualified employees mainly responsible for the customer interface experienced the organizational change most negatively. Using structural equation modelling, the context-dependent approach was empirically confirmed. Job control, role clarity and information were found to be the most important job and organizational resources.