Endogeneizing know-how flows through the nature of R&D investments

In this paper we carefully link knowledge flows to and from a firms innovation process with this firms investment decisions. Three types of investments are considered: investments in applied research, investments in basic research, and investments in intellectual property protection. Only when basic research is performed, can the firm effectively access incoming knowledge flows and these incoming spillovers serve to increase the efficiency of own applied research.. The firm can at the same time influence outgoing knowledge flows, improving appropriability of its innovations, by investing in protection. Our results indicate that firms with small budgets for innovation will not invest in basic research. This occurs in the short run, when the budget for know-how creation is restricted, or in the long-run, when market opportunities are low, when legal protection is not very important, or, when the pool of accessible and relevant external know-how is limited. The ratio! of basic to applied research is non-decreasing in the size of the pool of accessible external know-how, the size and opportunity of the market, and, the effectiveness of intellectual property rights protection. This indicates the existence of economies of scale in basic research due to external market related factors. Empirical evidence from a sample of innovative manufacturing firms in Belgium confirms the economies of scale in basic research as a consequence of the firms capacity to access external knowledge flows and to protect intellectual property, as well as the complementarity between legal and strategic investments.

The link between public support and private R&D effort: What is the optimal subsidy?

The effectiveness of R&D subsidies can vary substantially depending on their characteristics. Specifically, the amount and intensity of such subsidies are crucial issues in the design of public schemes supporting private R&D. Public agencies determine the intensities of R&D subsidies for firms in line with their eligibility criteria, although assessing the effects of R&D projects accurately is far from straightforward. The main aim of this paper is to examine whether there is an optimal intensity for R&D subsidies through an analysis of their impact on private R&D effort. We examine the decisions of a public agency to grant subsidies taking into account not only the characteristics of the firms but also, as few previous studies have done to date, those of the R&D projects. In determining the optimal subsidy we use both parametric and nonparametric techniques. The results show a non-linear relationship between the percentage of subsidy received and the firms’ R&D effort. These results have implications for technology policy, particularly for the design of R&D subsidies that ensure enhanced effectiveness.

The determinants of YIc's R&D activity

This paper examines the determinants of young innovative companies’ (YICs) R&D activities taking into account the autoregressive nature of innovation. Using a large longitudinal dataset comprising Spanish manufacturing firms over the period 1990-2008, we find that previous R&D experience is a fundamental determinant for mature and young firms, albeit to a smaller extent in the case of the YICs, suggesting that their innovation behaviour is less persistent and more erratic. Moreover, our results suggest that firm and market characteristics play a distinct role in boosting the innovation activity of firms of different age. In particular, while market concentration and the degree of product diversification are found to be important in boosting R&D activities in the sub-sample of mature firms only, YICs’ spending on R&D appears to be more sensitive to demand-pull variables, suggesting the presence of credit constraints. These results have been obtained using a recently proposed dynamic type-2 tobit estimator, which accounts for individual effects and efficiently handles the initial conditions problem.

Local Distance-Based Generalized Linear Models using the dbstats package for R

This paper introduces local distance-based generalized linear models. These models extend (weighted) distance-based linear models firstly with the generalized linear model concept, then by localizing. Distances between individuals are the only predictor information needed to fit these models. Therefore they are applicable to mixed (qualitative and quantitative) explanatory variables or when the regressor is of functional type. Models can be fitted and analysed with the R package dbstats, which implements several distancebased prediction methods.

News from compositions, the R package

The R-package “compositions”is a tool for advanced compositional analysis. Its basicfunctionality has seen some conceptual improvement, containing now some facilitiesto work with and represent ilr bases built from balances, and an elaborated subsys-tem for dealing with several kinds of irregular data: (rounded or structural) zeroes,incomplete observations and outliers. The general approach to these irregularities isbased on subcompositions: for an irregular datum, one can distinguish a “regular” sub-composition (where all parts are actually observed and the datum behaves typically)and a “problematic” subcomposition (with those unobserved, zero or rounded parts, orelse where the datum shows an erratic or atypical behaviour). Systematic classificationschemes are proposed for both outliers and missing values (including zeros) focusing onthe nature of irregularities in the datum subcomposition(s).To compute statistics with values missing at random and structural zeros, a projectionapproach is implemented: a given datum contributes to the estimation of the desiredparameters only on the subcompositon where it was observed. For data sets withvalues below the detection limit, two different approaches are provided: the well-knownimputation technique, and also the projection approach.To compute statistics in the presence of outliers, robust statistics are adapted to thecharacteristics of compositional data, based on the minimum covariance determinantapproach. The outlier classification is based on four different models of outlier occur-rence and Monte-Carlo-based tests for their characterization. Furthermore the packageprovides special plots helping to understand the nature of outliers in the dataset.Keywords: coda-dendrogram, lost values, MAR, missing data, MCD estimator,robustness, rounded zeros

Endogeneizing know-how flows through the nature of R&D investments

In this paper we carefully link knowledge flows to and from a firm s innovation process with this firm s investment decisions. Three types of investments are considered: investments in applied research, investments in basic research, and investments in intellectual property protection. Only when basic research is performed, can the firm effectively access incoming knowledge flows and these incoming spillovers serve to increase the efficiency of own applied research. The firm can at the same time influence outgoing knowledge flows, improving appropriability of its innovations, by investing in protection. Our results indicate that firms with small budgets for innovation will not invest in basic research. This occurs in the short run, when the budget for know-how creation is restricted, or in the long-run, when market opportunities are low, when legal protection is not very important, or, when the pool of accessible and relevant external know-how is limited. The ratio of basic to applied research is non-decreasing in the size of the pool of accessible external know-how, the size and opportunity of the market, and, the effectiveness of intellectual property rights protection. This indicates the existence of economies of scale in basic research due to external market related factors. Empirical evidence from a sample of innovative manufacturing firms in Belgium confirms the economies of scale in basic research as a consequence of the firm s capacity to access external knowledge flows and to protectintellectual property, as well as the complementarity between legal and strategic investments.

A territorial approach to R&D subsidies: Empirical evidence for Catalonian firms

Using a database of 2,263 responses to R&D public calls in Catalonia, during the period 2007–2010, this paper proceeds to analyse the potential interaction of the territorial and policy dimensions with the propensity to apply for, and be awarded, a public R&D subsidy. Controlling for characteristics at the firm and project level, we estimate models using a twostep procedure. In the first step, our results suggest that large firms which export and which belong to high-tech manufactures are more likely to participate in a public R&D call. Furthermore, both urban location and past experience of such calls have a positive effect. Our territorial proxy of information spillovers shows a positive sign, but this is only significant at intra-industry level. Membership of one of the sectors prioritized by the Catalan government, perhaps surprisingly, does not have a significant impact. In the second step, our results show that cooperative projects, SMEs or old firms shows a positive effect on the probability of obtaining a public subsidy. Finally, the cluster policy does not show a clear relationship with the public R&D call, suggesting that cluster policies and R&D subsidies follow different goals. Our results are in line with previous results in the literature, but they highlight the unequal territorial distribution of the firms which apply and the fact that policymakers should interlink the decision criteria for their public call with other policies.

The Transatlantic Productivity Gap : Is R&D the Main Culprit?

The literature has pointed to different causes to explain the productivity gap between Europe and United States in the last decades. This paper tests the hypothesis that the lower European productivity performance in comparison with the US can be explained not only by a lower level of corporate R&D investment, but also by a lower capacity to translate R&D investment into productivity gains. The proposed microeconometric estimates are based on a unique longitudinal database covering the period 1990-2008 and comprising 1.809 US and European companies for a total of 16.079 observations. Consistent with previous literature, we find robust evidence of a significant impact of R&D on productivity, however – using different estimation techniques - the R&D coefficients for the US firms always turn out to be significantly higher. To see to what extent these transatlantic differences may be related to the different sectoral structures in the US and the EU, we differentiated the analysis by sectors. The result is that both in manufacturing, services and high-tech sectors US firms are more efficient in translating their R&D investments into productivity increases.

A territorial approach to R&D subsidies: Empirical evidence for Catalonian firms

Using a database of 2,263 responses to R&D public calls in Catalonia, during the period 2007–2010, this paper proceeds to analyse the potential interaction of the territorial and policy dimensions with the propensity to apply for, and be awarded, a public R&D subsidy. Controlling for characteristics at the firm and project level, we estimate models using a two-step procedure. In the first step, our results suggest that large firms which export and which belong to high-tech manufactures are more likely to participate in a public R&D call. Furthermore, both urban location and past experience of such calls have a positive effect. Our territorial proxy of information spillovers shows a positive sign, but this is only significant at intra-industry level. Membership of one of the sectors prioritized by the Catalan government, perhaps surprisingly, does not have a significant impact. In the second step, our results show that cooperative projects, SMEs or old firms shows a positive effect on the probability of obtaining a public subsidy. Finally, the cluster policy does not show a clear relationship with the public R&D call, suggesting that cluster policies and R&D subsidies follow different goals. Our results are in line with previous results in the literature, but they highlight the unequal territorial distribution of the firms which apply and the fact that policymakers should interlink the decision criteria for their public call with other policies. Keywords: Evaluation, R&D policies, territorial approach, clusters JEL Classifications: L53, L25, O38

Cooperation in R&D, firm size and type of partnership: Evidence for the Spanish automotive industry

This paper aims to analyse cooperation in R&D in the automobile industry in Spain. It first examines to what extent firms cooperate with external actors in the field of technological innovation, and if so, with what type of cooperation partner, paying special attention to the differentiation according to the size of the firms. Second, it aims to study how the firm’s size may affect not only the decision of cooperating but also with which type of partner, while controlling for other determinants that have been considered in the literature as main drivers of collaborative activities in R&D. We use data provided by the Technological Innovation Panel in the 2006-2008 period for firms in the automotive sector. We estimate a bivariate probit model that takes into account the two types of cooperation mostly present in the automotive industry, vertical and institutional, explicitly considering the interdependencies that may arise in the simultaneous choice of both.

Cooperation in R&D, firm size and type of partnership: Evidence for the Spanish automotive industry

This paper aims to analyse cooperation in R&D in the automobile industry in Spain. It first examines to what extent firms cooperate with external actors in the field of technological innovation, and if so, with what type of cooperation partner, paying special attention to the differentiation according to the size of the firms. Second, it aims to study how the firm’s size may affect not only the decision of cooperating but also with which type of partner, while controlling for other determinants that have been considered in the literature as main drivers of collaborative activities in R&D. We use data provided by the Technological Innovation Panel in the 2006-2008 period for firms in the automotive sector. We estimate a bivariate probit model that takes into account the two types of cooperation mostly present in the automotive industry, vertical and institutional, explicitly considering the interdependencies that may arise in the simultaneous choice of both.