Evidence on the role of ownership structure on firms' innovative performance

Based on the Knowledge Production Function framework given by Griliches -1979-, we slightly modify it so that the innovative output depends upon a set of factors related to the firm internal characteristics and are influenced by the environment. Specifically, regarding the firm internal determinants the effect of the concentration of the ownership, the composition of the boards of directors and the effect of the nature of the ownership (foreign and public) are analyzed. Additionally, in order to capture the determinants of the environment in which the firm operates other variables concerning the internationalization of market, the agglomeration economies and the regional knowledge externalities are also considered. In order to assess the impact of these determinants on the number of patents and models of use awarded by the firm, the discreteness of the latter variable has to be taken into account. We apply Poisson and Negative Binomial models for a more comprehensive evaluation of the hypothesis in a panel of Spanish manufacturing firms. The results show patenting activity is positively favoured by being located in an environment with a high innovative activity, due to the existence of knowledge spillovers and agglomeration economies.

The summer North Atlantic Oscillation in CMIP3 models and related uncertainties in projected summer drying in Europe

This paper discusses uncertainties in model projections of summer drying in the Euro-Mediterranean region related to errors and uncertainties in the simulation of the summer NAO (SNAO). The SNAO is the leading mode of summer SLP variability in the North Atlantic/European sector and modulates precipitation not only in the vicinity of the SLP dipole (northwest Europe) but also in the Mediterranean region. An analysis of CMIP3 models is conducted to determine the extent to which models reproduce the signature of the SNAO and its impact on precipitation and to assess the role of the SNAO in the projected precipitation reductions. Most models correctly simulate the spatial pattern of the SNAO and the dry anomalies in northwest Europe that accompany the positive phase. The models also capture the concurrent wet conditions in the Mediterranean, but the amplitude of this signal is too weak, especially in the east. This error is related to the poor simulation of the upper-level circulation response to a positive SNAO, namely the observed trough over the Balkans that creates potential instability and favors precipitation. The SNAO is generally projected to trend upwards in CMIP3 models, leading to a consistent signal of precipitation reduction in NW Europe, but the intensity of the trend varies greatly across models, resulting in large uncertainties in the magnitude of the projected drying. In the Mediterranean, because the simulated influence of the SNAO is too weak, no precipitation increase occurs even in the presence of a strong SNAO trend, reducing confidence in these projections.

The Role of the Delay Time in the Modeling of Biological Range Expansions

The time interval between successive migrations of biological species causes a delay time in the reaction-diffusion equations describing their space-time dynamics. This lowers the predicted speed of the waves of advance, as compared to classical models. It has been shown that this delay-time effect improves the modeling of human range expansions. Here, we demonstrate that it can also be important for other species. We present two new examples where the predictions of the time-delayed and the classical (Fisher) approaches are compared to experimental data. No free or adjustable parameters are used. We show that the importance of the delay effect depends on the dimensionless product of the initial growth rate and the delay time. We argue that the delay effect should be taken into account in the modeling of range expansions for biological species