Exact inference for the difference of Laplace location parameters

We consider exact procedures for testing the equality of means (location parameters) of two Laplace populations with equal scale parameters based on corresponding independent random samples. The test statistics are based on either the maximum likelihood estimators or the best linear unbiased estimators of the Laplace parameters. By conditioning on certain quantities we manage to express their exact distributions as mixtures of ratios of linear combinations of standard exponential random variables. This allows us to find their exact quantiles and tabulate them for several sample sizes. The powers of the tests are compared either numerically or by simulation. Exact confidence intervals for the difference of the means corresponding to those tests are also constructed. The exact procedures are illustrated via a real data example.     

Does Financial Development Affect Environmental Degradation? Evidence from the OECD Countries

In this study, building a simple model that incorporates static and dynamic elements, the relationship of financial development and economic growth to environmental degradation is investigated together with the validation of the Environmental Kuznets Curve (EKC) hypothesis. Our analysis is based on an unbalanced panel data set covering the OECD countries over the period 1970–2014. Our approach thoroughly accounts for the presence of cross‐sectional dependence between the sample variables and utilizes second generation panel unit root tests in order to investigate possible cointegration relationships. The empirical findings do indicate that local (NO_x per capita emissions) and global (CO₂ per capita emissions) pollutants redefine the EKC hypothesis when we account for the presence of financial development indicators. Specifically, in the case of global pollution an N‐shape relationship is evident in both static and dynamic frameworks, with a very slow adjustment. Lastly, our study calls for a strengthening of the effectiveness of environmental degradation policies by ensuring sustainability of the OECD banking system in order to drastically reduce emissions. Copyright © 2017 John Wiley & Sons, Ltd and ERP Environment     

When Do Expert Teams Fail to Create Impactful Inventions?

We investigate the salience of expertise in creating high impact inventions and question experts’ ability to deploy novel ideas. Specifically, we examine the relationships between expertise, component originality, and a team's structural holes’ position in the collaborative network and propose that, in relative terms, expert teams create lower impact inventions if they deploy more original components and if they occupy structural holes. We test and confirm our hypotheses in a sample of semiconductor firms. In post‐hoc analyses, we find a three‐way interaction where the negative effect of structural holes almost disappears when an expert team experiments with original components whereas an increase in non‐redundancy is detrimental when teams with high expertise use familiar components. Our findings inform a foundational view of the invention process and provide novel insights into the contingent benefits of domain expertise.     

Levelling the playing field for EU biomass usage

The threats of climate change, food security, resource depletion and energy security are driving society towards a sustainable low-carbon future. Within this paradigm, biomass plays an invaluable role in meeting the food, feed, energy and material needs of future generations. Current EU thinking advocates biomass for high-value materials, which is not aligned with EU public policy support for ‘lower value’ bioenergy applications. ‘High-technology’ and ‘no bioenergy mandate’ pathways explore market conditions that generate a more equitable distribution between competing biomass conversion technologies and competing biomass and fossil technologies. In achieving greater equity, these pathways ease biomass market tensions; enhance EU food security; improve EU biobased trade balances; accelerate biomaterial sectors’ output performance and favour macroeconomic growth. Moreover, an additional 80% increase in the oil price signals a tipping point in favour of first generation biofuels, whilst simultaneously boosting output in advanced material conversion technologies even more than the high-technology pathway.     

Testing for strict stationarity in financial variables

This paper considers the stationarity properties of a variety of financial variables using statistical tests for strict stationarity. We find that there has been a gradual shift in unconditional variances for the variables examined during the 90’s and 2000’s and that this is the main cause of the widespread rejection of the strict stationarity null hypothesis. This is a powerful result which suggests that the consideration of conditional mean and, especially, conditional variance models which assume stationarity is problematic for the period under examination. This casts serious doubts on the usefulness of models that assume strict stationarity and model conditional second moments, such as GARCH and stochastic volatility models.     

Technology Choice and Market Structure: strategic aspects of flexible manufacturing

This paper shows that the adoption of flexible manufacturing techniques by firms leads to a tougher price regime. However, consumers may not benefit since the tougher regime deters entry. Flexible manufacturing's ability to deter entry is moderated by two factors: non-prohibitive costs of re-anchoring flexible manufacturing processes and the possibility that entrants choose to produce niche products using designated technologies rather than adopt flexible manufacturing. Market preemption that deters entry will be characterized by excessive product variety. Alternatively, flexible manufacturers may prefer to accommodate entry by small-scale, niche firms. Moreover, ownership matters in determining equilibrium product configurations.     

Forecasting UK commercial real estate cycle phases with leading indicators: a probit approach

This paper examines the significance of widely used leading indicators of the UK economy for predicting the cyclical pattern of commercial real estate performance. The analysis uses monthly capital value data for UK industrials, offices and retail from the Investment Property Databank (IPD). Prospective economic indicators are drawn from three sources namely, the series used by the US Conference Board to construct their UK leading indicator and the series deployed by two private organisations, Lombard Street Research and NTC Research, to predict UK economic activity. We first identify turning points in the capital value series adopting techniques employed in the classical business cycle literature. Probit models are then estimated using the leading economic indicators as independent variables and forecast the probability of different phases of capital values, that is, periods of declining and rising capital values. The forecast performance of the models is tested and found to be satisfactory. The predictability of lasting directional changes in property performance represents a useful tool for real estate investment decision-making.