Internal and external R&D: complements or substitutes? Evidence from a dynamic panel data model.

We examine the impact of internal and external R&D on labor productivity in a 6-year panel of 304 innovating firms. We apply a dynamic linear panel data model that allows for decreasing returns to scale in internal and external R&D with a non-linear approximation of changes in the knowledge stock. We find complementarity between internal and external R&D, with a positive impact of external R&D only evident in case of sufficient internal R&D. The findings confirm the role of internal R&D in enhancing absorptive capacity and hence the effective utilization of external knowledge. These results suggest that empirical studies examining complementarities between continuously measured practices should adopt more general non-linear specifications to allow for correct inferences.R&D; Panel data; Innovating firms; Knowledge; Empirical study; Specifications;

Testing for complementarity and substitutability in the case of multiple practices.

Recent empirical studies of firm-level performance have been concerned with establishing potential complementarity between more than two organizational practices. These papers have drawn conclusions on the basis of potentially biased estimates of pair-wise interaction effects between such practices. In this paper we develop a consistent testing framework based on multiple inequality constraints that derives from the definition of (strict) supermodularity as suggested by Athey and Stern (1998). Monte Carlo results show that the multiple restrictions test is superior for performance models with high explanatory power. If practices explain only a minor part of organizational performance no test is able to identify complementarity or substitutability in a satisfactory manner.Complementarity; Constraint; Effects; Empirical study; Firm performance; Framework; Interaction effects; Model; Models; Performance; Power; Studies; Supermodularity;

The Implications of Content Analysis for the Interpretation of Unguentaria in Museum Collections

Scent has traditionally been an ephemeral component of rituals in ancient societies, including burial and other practices associated with the anointing of the body (Classen et al. 1994: 43; Houston and Taube 2000: 271). This thesis investigates the possible signifiers and social impact such scents might have had for individuals participating in such rituals by using the little explored approach of sensory archaeology. A discussion of the correlation between olfaction and the triggering of both the experiential and emotional aspects of memory contributes to a broader view of these rituals in the anthropological literature (Classen et al. 1994), while Houston and Taube\u27s work on scent in Mayan rituals provides a framework for applying sensory archaeology to Classical contexts (2000). Vessel contents are used as a proxy in this thesis for reconstructing the particular olfactory atmosphere associated with mortuary ritual in late Greek and early Roman cultural contexts. The residue spectra derived from the visible contents of twenty-seven out of a total of thirty-nine small glass and ceramic vials from collections at the Milwaukee Public Museum (MPM) are compared to other unguentaria residue studies as well as Greek and Roman written sources in which scented unguents, oils, perfumes, creams, and cosmetics are described to test the archaeological classification of this vessel category. Stylistic conventions are tested against data derived from content analysis rather than solely on the basis of assumed function implied by form. The chemical characterization of the contents of these vessels relies on the use of inductively coupled plasma-mass spectrometry (ICP-MS) and Fourier transform-infrared spectroscopy (FTIR). FT-IR was chosen for its successful application in a recent residue study of unguentaria (Ribechini et al. 2008a-b) while ICP-MS analysis was performed based upon its widespread application to the determination of sample origin

Further results on bias in dynamic unbalanced panel data models with an application to firm R&D investment

This article extends the lsdv bias-corrected estimator in (bun and carree, 2005 bun, m. And carree, m. 2005. Bias-corrected estimation in dynamic panel data models. Journal of business and economic statistics, 23: 200–9. [taylor & francis online], [web of science ®], , [google scholar]) to unbalanced panels and discusses the analytic method of obtaining the solution. Using a monte carlo approach the article compares the performance of this estimator with three other available techniques for dynamic panel data models. Simulation reveals that lsdv-bc estimator is a good choice except for samples with small t, where it may be unpractical. The methodology is applied to examine the impact of internal and external r&d on labour productivity in an unbalanced panel of innovating firms