On Regional Unemployment: An Empirical Examination of the Determinants of Geographical Differentials in the UK

In this paper we consider the determinants of regional disparities in unemployment rates for the UK regions at NUTS‐II level. We use a mixture panel data model to describe unemployment differentials between heterogeneous groups of regions. The results indicate the existence of two clusters of regions in the UK economy, characterized by high and low unemployment rates, respectively. A major source of heterogeneity appears to be caused by the varying effect (between the two clusters) of the share of employment in the service sector, and we trace its origin to the fact that the high unemployment cluster is characterized by a higher degree of urbanization.     

Productivity growth and inflation in Europe: Evidence from panel cointegration tests

In this paper we investigate the productivity growth – inflation nexus in fifteen European countries over the period 1961–1999 using panel unit root and panel cointegration tests. Emphasis is placed on the distinction between long-run and short-run causality using recently developed tests appropriate for heterogeneous panel. The empirical results are relevant for the role of the EMU and the Treaty of Maastricht in catching up, real convergence, and the future growth prospects of Europe. The policy implications of the findings are discussed in detail.     

The chief executive officer as corporate champion of technological innovation: aii empirical investigation

Research on innovation has engoged the attention of many scientific disciplines over the past few decades. But while some categories of determining factors (mainly organizational and environmental) are at the centre of this research, others, such as the role and significance of strategic leadership, seem to have received much less empirical attention. Using evidence from a sample of 97 manufacturing enterprises, the present study tests a model of the impact of strategic leadership and corporate context on technological innovatin (TT). The personality and demographic characteristics of chief executive officers (CEis') are used to measure strategic leadership. A number of environmental and internal organizational variables measure the broader context. Four dimensions of TI are measured. Results suggest that CEO characteristics significantly influence TI, but the structural and environmental context is on aggregate more influential. Interestingly though, in new product introductions, CEIs' characteristics outweight environmental and internal organizational factors.     

UK macroeconomic forecasting with many predictors: Which models forecast best and when do they do so?

Block factor methods offer an attractive approach to forecasting with many predictors. These extract the information in these predictors into factors reflecting different blocks of variables (e.g. a price block, a housing block, a financial block, etc.). However, a forecasting model which simply includes all blocks as predictors risks being over-parameterized. Thus, it is desirable to use a methodology which allows for different parsimonious forecasting models to hold at different points in time. In this paper, we use dynamic model averaging and dynamic model selection to achieve this goal. These methods automatically alter the weights attached to different forecasting models as evidence comes in about which has forecast well in the recent past. In an empirical study involving forecasting output growth and inflation using 139 UK monthly time series variables, we find that the set of predictors changes substantially over time. Furthermore, our results show that dynamic model averaging and model selection can greatly improve forecast performance relative to traditional forecasting methods.     

Promoting energy efficiency policies over the information barrier

Stakeholders argue that the information barrier is the major obstacle restricting firms from adopting Energy Efficiency Technologies (EETs) in Europe. The present work examines the processes of information gathering as regards to EETs and explores the factors affecting the level of acquired information by EET adopters. Empirical evidence is provided by a data set of Greek manufacturing firms which have adopted EETs. In conclusion, we propose appropriate policy measures able to promote the adoption of EETs by overcoming the information barrier.     

Approximate basket option valuation for a simplified jump process

This study proposes the use of a simplified jump process, namely the Bernoulli jump process, to develop approximate basket option valuation formulas. The proposed model is based on a more realistic stochastic process—relative to the standard geometric Brownian motion—without introducing additional intractability. Typical approximations, necessary for the development of the closed form formulas, are validated on the basis of a Monte Carlo experiment. © 2007 Wiley Periodicals, Inc. Jrl Fut Mark 27:819–837, 2007     

Process-oriented knowledge management systems based on KM-services: the PROMOTE® approach

This article describes the PROMOTE^® approach, to define and implement a Service-Based Enterprise Knowledge Management System (E-KMS) that has been developed during the EC-funded project PROMOTE (IST-1999-11658). The aim is to define a modelling language that is used to analyse, document and implement an E-KMS on the basis of so-called Knowledge Management Processes (KMPs). KMPs define the knowledge interaction between knowledge workers in a process-oriented manner and consists of activities that are supported by knowledge management key actions (KA) like searching, categorising or storing information. These knowledge management key actions are supported by Knowledge Management Services (KM-Service). The prototype of PROMOTE^® is briefly mentioned to discuss the KMP-models and the service based E-KMS. Copyright © 2003 John Wiley & Sons, Ltd.     

Estimating Implied PDFs From American Options on Futures: A New Semiparametric Approach

This article develops a new methodology for estimating implied probability density functions for futures prices from American options. The restricting Black–Scholes assumption of a lognormal distribution for the underlying asset is relaxed with the use of the more flexible distributional form of an Edgeworth series expansion around a lognormal distribution. The model is applied to the crude oil market. The results provide strong evidence that the market consensus can be accurately reflected in the risk‐neutral densities recovered from observed option prices. The recovered distributions are tested and found to differ significantly from a single lognormal distribution. In addition, the recovered distributions are more robust than those recovered with a model, which assumes a mixture of two lognormal distributions. © 2002 John Wiley & Sons, Inc. Jrl Fut Mark 22:1–30, 2002     

VAR FORECASTING USING BAYESIAN VARIABLE SELECTION

This paper develops methods for automatic selection of variables in Bayesian vector autoregressions (VARs) using the Gibbs sampler. In particular, I provide computationally efficient algorithms for stochastic variable selection in generic linear and nonlinear models, as well as models of large dimensions. The performance of the proposed variable selection method is assessed in forecasting three major macroeconomic time series of the UK economy. Data‐based restrictions of VAR coefficients can help improve upon their unrestricted counterparts in forecasting, and in many cases they compare favorably to shrinkage estimators. Copyright © 2011 John Wiley & Sons, Ltd.