Major Hazard Information Policy in the European Community: Implications for Risk Analysis

The main impetus to the development of information about major industrial hazards in the European Community comes from the so-called Seveso Directive, which defines an information network and requires the generation and transmission of information as the basis for accident prevention and risk management. This important policy development, which calls for the formal identification and analysis of major hazards and the communication of risk information to members of the public, presents new opportunities and challenges to risk analysis and research in Europe. This paper briefly reviews the accidents that gave rise to the Directive and shaped its content, and then summarizes its requirements. The status of its implementation in the EC Member States is discussed, with special emphasis given to the comparison of safety analysis practices, the Major Accident Reporting System (MARS), and risk communication. Some new research directions stimulated by the Directive are identified.     

Statistical Properties of Threshold Models

This article focuses the attention on the Self Exciting Threshold Autoregressive Moving Average model (SETARMA) proposed in Tong (1983 Tong , H. ( 1983 ). Threshold Models in Nonlinear Time Series Analysis . London : Springer-Verlag .[Crossref] , [Google Scholar]). The stochastic structure of the model is discussed and different specifications are presented. Starting from one of them, we give sufficient conditions for the weak stationarity of the model that are discussed and critically compared to other results given in literature. In particular, after showing that the SETARMA model belongs to the class of the Random Coefficients Autoregressive models, widely discussed in Nicholls and Quinn (1982 Nicholls , D. F. , Quinn , B. G. (1982). Random Coefficients Autoregressive Models. An Introduction . New York : Springer-Verlag.[Crossref] , [Google Scholar]), we give some issues on the weak stationarity of its stochastic structure that are more general than those given in the existing literature and appear not affected by the moving average component.     

A non-linear time series approach to modelling asymmetry in stock market indexes

In this paper we analyse the performances of a novel approach to modelling non-linear conditionally heteroscedastic time series characterised by asymmetries in both the conditional mean and variance. This is based on the combination of a TAR model for the conditional mean with a Constrained Changing Parameters Volatility (CPV-C) model for the conditional variance. Empirical results are given for the daily returns of the S&P 500, NASDAQ composite and FTSE 100 stock market indexes.     

Labour Market and Decentralized Decision-making: An Institutional Approach

The persistent failure in the labour market is due to uncertainty and asymmetric information, and relies on a reconsideration of the bargaining process. This process is not generated by individual action but rather by the behaviour of social groups and institutions in which State intervention can immprove the efficiency in matching demand and supply. In this framework we will discuss the ways by which institutional decentralization can be implemented in a labour market characterized by deep regional differences and by long-term unemployment persistence as in Italy. The main conclusion is that this policy option better fits the active labour policies. In fact the actual aim of such supply-side policies is to reduce the regional and skill mismatches and therefore it needs a substantial involvement of local public agencies.