In times of uncertainties scenarios offer a solution. Starting with Royal Dutch Shell by the late 1960s, corporate scenarios are intended to challenge managers’ “personal microcosms” and to reflect the present and the past, before structuring the uncertainties of the future. Therefore,...

An agent-based computational laboratory for exploratory energy policy by means of controlled computational experiments is proposed. It is termed the ACEGES (agent-based computational economics of the global energy system). In particular, it is shown how agent-based modelling and simulation can...

This evidence is presented to the Select Committee to provide a perspective in terms of the threats, vulnerability and consequences of the UK Energy Supply System within a global-national context characterized by unprecedented uncertainties and increasingly complex intertwines. This contribution...

This paper utilises the GAMLSS framework for the statistical modelling of movie box-office revenues. The dominant modelling paradigm of the film industry, traditionally exemplified by the nobody knows principle is based upon the infinite variance of the Pareto distribution. Using GAMLSS we have...

Most executives know that overarching paints of plausible futures will profoundly affect the competitiveness and survival of their organisation. Initially from the perspective of Shell, this article discuses oil scenarios and their relevance for upstream investments. Scenarios are then...

Information on observable economic and financial variables is sometimes limited to summary form. Therefore, in many practical situations, it is desirable to restrict the flexibility of nonparametric density estimators to accommodate information about the summary data as well as any prior...

In many practical statistical situations, it is desirable to restrict the flexibility of nonparametric regression models to accommodate prior information. We propose an estimator for regression models with a smoothness penalty and constraints imposed by the nature of the problem. Our estimator...

In many settings of empirical interest, time variation in the distribution parameters is important for capturing the dynamic behaviour of time series processes. Although the fitting of heavy tail distributions has become easier due to computational advances, the joint and explicit modelling of...

Using box-office data for movies released in the US market in the 1990s and 1930s, we establish probabilistic statements for the box-office revenues that the market at these instances dictate. Here, we propose a smooth and non-parametric model of heavy tails and skewness using the GAMLSS...

This paper illustrates the power of modern statistical modelling in understanding processes characterised by data that are skewed and have heavy tails. Our particular substantive problem concerns film box-office revenues. We are able to show that traditional modelling techniques based on the...