Determinants of intellectual capital disclosure in prospectuses of initial public offerings

Intellectual capital is recognised as the new economic era’s pivotal factor underlying value creation. Deficient and inconsistent intellectual capital reporting is escalating information asymmetry between informed and uninformed investors. This provides fertile ground for informed investors to extract higher abnormal returns and higher wealth transfers from uninformed investors, particularly during a firm’s initial public offering (IPO). This study investigates the association between intellectual capital disclosure levels in prospectuses of 444 IPOs listing on the Singapore Stock Exchange between 1997 and 2006, and three potential explanatory determinants: (1) ownership retention; (2) proprietary costs; and (3) corporate governance structure. Statistical analysis supports our conjecture of a positive association between intellectual capital disclosure and ownership retention. We also find, consistent with expectations, a negative influence of proprietary costs on the positive intellectual capital disclosure – ownership retention association. However, contrary to predictions, we do not find an IPO’s corporate governance structure significantly influences the negative interaction of proprietary costs on the ownership retention – proprietary cost association. Our findings have implications for various parties such as regulators who may impose unnecessary costs on issuers if they introduce mandatory disclosures whilst lacking an understanding of the factors influencing intellectual capital disclosures.     

Cooperation versus competition in product innovation

This paper analyzes the optimal antitrust policy in the context of a patent race. In a simplified model, we identify the conditions under which allowing cooperation yields greater welfare than imposing competition. In view of our results, we discuss, critically, the current European policy towards R&D cooperation.     

Government policies to enhance access to credit for infrastructure-based PPPs: an approach to classification and appraisal

Governments across the world have introduced a variety of instruments to enhance private investors’ appetites for public–private partnership (PPP) projects. The use of such instruments has become a core component of development and growth policies, for example by the EU as part of the Junker Plan. This paper provides a comprehensive categorization of these instruments, the risks they target and their effects, at both the project and system level, to support policy-makers to design the most appropriate instruments to attract private capital into infrastructure development.     

Integrated Risk Management with a Filtered Bootstrap Approach

We present a multi-period risk model to measure portfolio risk that integrates market risk, credit risk and, in a simplified way, liquidity risk. Thus, it overcomes the major limitation currently shared by many risk models that are unable to give a complete picture of all portfolio risks according to a single, coherent framework. The model is based on the Filtered Bootstrap approach; hence, it captures conditional heteroskedasticity, serial correlation and non-normality in the risk factors, that is, most of the features of observed financial time series. Being a simulation risk model, it copes in a natural way with derivatives as it allows the full valuation of the probability density function of the contracts. In addition, it is a suitable and flexible way to generate future scenarios on medium‐term horizons, so this model is particularly appropriate for asset management companies.     

Nonlinearities in stochastic clocks: trades and volume as subordinators of electronic markets

This paper discusses the possibility of recovering normality of asset returns through a stochastic time change, where the appropriate economic time is determined through a simple parametric function of the cumulative number of trades and/or the cumulative volume. The existing literature argues that the re-centred cumulative number of trades could be used as the appropriate stochastic clock of the market under which asset returns are virtually Gaussian. Using tick-data for FTSE-100 futures, we show that normality is not always recovered by conditioning on the re-centred number of trades. However, it can be shown that simply extending the approach to a nonlinear function can provide a better stochastic clock of the market.     

The behaviour of repeat visitors to museums: review and empirical findings

This study presents a theoretical and operational framework for analysing repeat visit to museums. Starting from the literature on repeat visit in tourism, the specificities of these cultural attractions are made explicit through a review of theoretical and applied works. Consistently with previous contributors, the paper suggests that the analysis of actual past behaviours has to be preferred to the one of attitudes. The application of proper econometric models is also remarked in order to put into account individual profiles. Information coming from three techniques is then used in an integrated way in order to provide a more comprehensive view of the phenomenon. Evidence from an ad hoc survey suggests the necessity to give a greater attention to perceived cultural value during the visit, promoting cultural events during the week and addressed to children, and taking care of those visitors that come from far places also through an integrated tourist supply.     

Uncertainty and the market valuation of R&D within a real options logic

The aim of this study is to provide new theoretical insights and empirical evidence on the effect of market and technological uncertainty on the market valuation of a firm's R&D capital. A set of hypotheses is developed adopting a real options logic and tested on a panel dataset of 290 manufacturing firms traded in the UK. Consistently with our theoretical model, we show that market and technological uncertainty have distinct effects on the valuation of R&D investments. The results have several important implications for resource allocation to R&D under uncertainty, which we discuss in the concluding section. Copyright © 2008 John Wiley & Sons, Ltd.     

Proximity,networking and knowledge production in Europe: What lessons for innovation policy?

This paper aims at investigating the role of different types of proximity on the technological activity of a region within the context of a knowledge production function, where R&D expenditure and human capital are the main internal inputs. We thus assess to what extent the creation of new ideas in a certain region is enhanced by knowledge flows coming from proximate regions. In particular, we examine in detail different kinds of proximity by combining the usual geographical dimension with the institutional, technological, social and organizational proximity. The analysis is implemented for an ample dataset referring to 276 regions in 29 European countries (EU27 plus Norway, Switzerland) over the last decade. Results show that human capital and R&D are clearly essential for innovative activity with the former being much more effective in driving the production of knowledge. As for the proximity and network effects, we find that technological proximity outperforms the geographic one, whilst a limited role is played by social and organizational networks. As a result, the first policy message is that European regions still need to focus on policies aimed at increasing the endowments of well-educated labour force and therefore their knowledge base. Furthermore, we need innovation policies based on each region's specific innovation potential, due to the existing differences in geographical, cognitive, institutional, social and organizational structures and networks.