This paper compares the role of innovation and economic performance across European and Latin American countries, using firm-level data from France, Spain, Switzerland, Argentina, Brazil and Mexico. We implement a standard structural model linking R&D intensity, innovation and productivity. We find evidence revealing structural differences between Europe and Latin America, but also the presence of heterogeneity within each. In particular, firms tend to engage in innovation activities in order to achieve better economic performance on a similar basis among countries, but their interaction with national systems is weaker in developing countries. The fact of being a foreign subsidiary of a foreign multinational is found to have a heterogeneous effect on innovativity, whereas it leads to increased productivity in every country.R&D, innovation, productivity, developing countries, MNEs,

Whereas recent scholarly research has provided many insights about universities engaging in commercial activities, there is still little empirical evidence regarding the opposite phenomenon of companies disseminating scientific knowledge. Our paper aims to fill this gap and explores the motivations of firms that disclose research outcomes in a scientific format. Besides considering an internal firm dimension, we focus particularly on knowledge sourcing from academic institutions and the appropriability regime using a cost-benefit framework. We conduct an econometric analysis with firm-level data from the fourth edition of the French Community Innovation Survey (CIS4) and matched scientific publications for a sample of 2,512 R&D performing firms from all manufacturing sectors. The analysis provides evidence that the access to important scientific knowledge imposes the adoption of academic disclosure principles, whereas the mere existence of collaborative links with academic institutions is not a strong predictor. Furthermore, the results suggest that overall industry conditions are influential in shaping the cost-benefit rationale of firms with respect to scientific disclosure.

a b s t r a c tPatent statistics represent a critical tool for scholars, statisticians and policy makers interested in innovation and intellectual property rights. Many analyses are based on heterogeneous methods delineating the inventors' or firms' patent portfolios without questioning the quality of the method employed. We assess different heuristics in order to provide a robust solution to automatically retrieve inventors in large patent datasets (PATSTAT). The solution we propose reduces the usual errors by 50% and casts doubts on the reliability of statistical indicators and micro-econometric results based on common matching procedures. Guidelines for researchers, TTOs, firms, venture capitalists and policy makers likely to implement a names game or to comment on results based on a names game are also provided.

R obotics technology and the increasing sophistication of artificial intelligence are breakthrough innovations with significant growth prospects. They have the potential to disrupt existing socioeconomic facets of everyday life. Yet few studies have analysed the development of robotics innovation. This paper closes this gap by analysing current developments in innovation in robotics; how it is diffused, and what role is played by intellectual property (IP). The paper argues that robotics clusters are mainly located in the US and Europe, despite a growing presence in South Korea and China. The robotics innovation ecosystem builds on cooperative networks of actors, including individuals, research institutions, and firms. Governments play a significant role in supporting robotics innovation through funding, military demand, and national robotics strategies. Robotics competitions