In this paper we investigate the nexus between rm labor diversity and innovation using data on patent applications led by rms at the European Patent Oce and a linked employer-employee database from Denmark. Exploiting the information retrieved from these comprehensive data sets and implementing proper instrumental variable strategies, we estimate the contribution of workers' diversity in cultural background, education and demographic characteristics to valuable rm's innovation activity. Specically, we nd evidence supporting the hypothesis that ethnic diversity may facilitate rms' patenting activity in several ways by: (a) increasing the propensity to (apply for a) patent, (b) increasing the overall number of patent applications and (c) by enlarging the breadth of patenting technological elds, conditional on patenting. Several robustness checks corroborate the main ndings.

Using a matched employer-employee data-set, we analyze how workforce diversity associates with the productivity of rms in Denmark, following two main econometric routes. In the rst one, we estimate a standard Cobb-Douglas function, calculate the implied total factor productivity and relate the latter to diversity statistics in a second stage. This reduced-form approach allows us to identify which types of labor heterogeneity appear to descriptively matter. In the second approach, we move toward a richer production function specication, which takes dierent types of labor as inputs and that allows for exible substitution patterns, and possible quality dierences between types. Both methods show that workforce diversity in ethnicity is negatively associated with rm productivity. The evidence regarding diversity in education is mixed.JEL Classication: J24, J61, J82, L20.

International audienceThis study analyzes the effect of public R&D subsidies on private R&D expenditure in a sample of French firms during the period 1993–2009. We evaluate whether there is any input additionality of public R&D subsidies by distinguishing between R&D tax credit recipient and non-recipient firms. In addition, combining difference-in-differences with propensity score and exact (both simple and categorical) matching methods, we assess the effect of R&D subsidies between treated (subsidy recipients) and controls (subsidy non-recipients) as well as between differently treated (small, medium and large subsidy recipient) firms. Furthermore, we implement a dose–response matching approach to determine the optimality of public R&D subsidy provisions. We find evidence of either no additionality or substitution effects between public and private R&D expenditure. Crowding-out effects appear to be more pronounced for medium-high levels of public subsidies, and generally under the R&D tax credit regime. A number of robustness checks corroborate our main findings