Does the motivation for foreign direct investment affect productivity spillovers to the domestic sector?

There is increasing empirical and theoretical evidence that foreign direct investment (FDI) may be motivated not by the desire to exploit some competitive advantage possessed by multinationals, but to access the technology of host economy firms. Using a panel of FDI flows across OECD countries and manufacturing sectors between 1984 and 1995, we test whether these contrasting motivations influence the effects that FDI has on domestic total factor productivity. The distinction between technology-exploiting FDI (TEFDI) and technology-sourcing FDI (TSFDI) is made using R&D intensity differentials between host and source sectors. The hypothesis that the motivation for FDI has an effect on total factor productivity spillovers is supported: TEFDI has a net positive effect, while TSFDI has a net negative effect. These net effects are explained in terms of the offsetting influences of productivity spillovers and market stealing effects induced by incoming multinationals.

On the adoption decision and the intensity of use of complementary innovations: The intra firm diffusion of management practices across UK establishments

This paper contributes to the literature on the intra-firm diffusion of innovations by investigating the factors that affect the firm’s decision to adopt and use sets of complementary innovations. We define complementary innovations those innovations whose joint use generates super additive gains, i.e. the gain from the joint adoption is higher than the sum of the gains derived from the adoption of each innovation in isolation. From a theoretical perspective, we present a simple decision model, whereby the firm decides ‘whether’ and ‘how much’ to invest in each of the innovations under investigation based upon the expected profit gain from each possible combination of adoption and use. The model shows how the extent of complementarity among the innovations can affect the firm’s profit gains and therefore the likelihood that the firm will adopt these innovations jointly, rather than individually. From an empirical perspective, we focus on four sets of management practices, namely operating (OMP), monitoring (MMP), targets (TMP) and incentives (IMP) management practices. We show that these sets of practices, although to a different extent, are complementary to each other. Then, we construct a synthetic indicator of the depth of their use. The resulting intra-firm index is built to reflect not only the number of practices adopted but also the depth of their individual use and the extent of their complementarity. The empirical testing of the decision model is carried out using the evidence from the adoption behaviour of a sample of 1,238 UK establishments present in the 2004 Workplace Employment Relations Survey (WERS). Our empirical results show that the intra-firm profitability based model is a good model in that it can explain more of the variability of joint adoption than models based upon the variability of adoption and use of individual practices. We also investigate whether a number of firm specific and market characteristics by affecting the size of the gains (which the joint adoption of innovations can generate) may drive the intensity of use of the four innovations. We find that establishment size, whether foreign owned, whether exposed to an international market and the degree of homogeneity of the final product are important determinants of the intensity of the joint adoption of the four innovations. Most importantly, our results point out that the factors that the economics of innovation literature has been showing to affect the intensity of use of a technological innovation do also affect the intensity of use of sets of innovative management practices. However, they can explain only a small part of the diversity of their joint adoption use by the firms in the sample.

Export propensity, export intensity and firm performance:the role of the entrepreneurial founding team

We investigate how the characteristics and experience of the entrepreneurial founding team (EFT) affect the export orientation and subsequent performance of the businesses they establish, while allowing for the mutually reinforcing relationship between exporting and productivity. Using a sample of UK technology-based firms, we hypothesise and confirm that the set of EFT human capital needed for entering export markets is different from that required for succeeding in export markets. Commercial and managerial experience helps firms become exporters, but once over the exporting hurdle it is education, both general and specific, that has a substantially positive effect. The overall pattern of human capital effects on productivity is similar to those for export propensity. We also find evidence that productive firms are more likely both to enter export markets and to be export intensive, and that exporting boosts subsequent firm productivity.

Facial affect processing inbipolar disorder:a magnetoencephalography study

Background: Identifying biological markers to aid diagnosis of bipolar disorder (BD) is critically important. To be considered a possible biological marker, neural patterns in BD should be discriminant from those in healthy individuals (HI). We examined patterns of neuromagnetic responses revealed by magnetoencephalography (MEG) during implicit emotion-processing using emotional (happy, fearful, sad) and neutral facial expressions, in sixteen BD and sixteen age- and gender-matched healthy individuals. Methods: Neuromagnetic data were recorded using a 306-channel whole-head MEG ELEKTA Neuromag System, and preprocessed using Signal Space Separation as implemented in MaxFilter (ELEKTA). Custom Matlab programs removed EOG and ECG signals from filtered MEG data, and computed means of epoched data (0-250ms, 250-500ms, 500-750ms). A generalized linear model with three factors (individual, emotion intensity and time) compared BD and HI. A principal component analysis of normalized mean channel data in selected brain regions identified principal components that explained 95% of data variation. These components were used in a quadratic support vector machine (SVM) pattern classifier. SVM classifier performance was assessed using the leave-one-out approach. Results: BD and HI showed significantly different patterns of activation for 0-250ms within both left occipital and temporal regions, specifically for neutral facial expressions. PCA analysis revealed significant differences between BD and HI for mild fearful, happy, and sad facial expressions within 250-500ms. SVM quadratic classifier showed greatest accuracy (84%) and sensitivity (92%) for neutral faces, in left occipital regions within 500-750ms. Conclusions: MEG responses may be used in the search for disease specific neural markers.