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We examine firms' propensity to adapt their R&D collaboration portfolio by establishing new types of R&D collaboration with different kinds of partners (suppliers, customers, competitors and universities & public research institutions). We argue that existing R&D collaboration with one of the two value chain partners (suppliers or customers) is associated with the formation of new R&D collaboration with the other value chain partner to ensure temporal alignment in innovation within the value chain. In contrast, issues related to governance and unintended knowledge spillovers suggest that 'horizontal' R&D collaboration with competitors only spurs R&D collaboration with other partner types if such competitor R&D collaboration has been discontinued earlier ('delayed temporal alignment').We posit that persistent prior R&D collaboration with institutional partners is an antecedent to the establishment of new R&D collaboration with industrial partners, and that discontinuation of a particular type of R&D collaboration is likely to lead to a restart of such R&D collaborative effort. Strong prior innovative performance is expected to increase the probability that firms establish R&D collaborations with new partner types, except for R&D collaboration with competitors, since the most innovative firms may fear leakage of proprietary knowledge to rivals. We find broad support for these predictions in a large panel of Spanish innovating firms (2004Spanish innovating firms ( -2011. Our findings highlight that it is not just the configuration of R&D collaborations with existing partner types that predicts tie formation with new partner types, but also the intertemporal pattern of prior R&D collaboration and managerial discretion provided by past innovation success.

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This paper examines the determinants of social spending in Latin America during the period 1990-2012 and how they differed between the years of the Washington Consensus (1990Consensus ( -2000 and the period that followed (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012). Special attention is also paid to the evaluation of convergence towards a common upper-bounded steady state (absolute beta convergence) or to specific steady states conditioned by their country's specific determinants (conditional beta convergence). We estimate a panel error-correction version of an autoregressive distributed lag model to identify the long-term relationships between social expenditure and its determinants. Generalised methods of moments estimators are used to control the endogeneity of the regressors. Results indicate that Latin American social spending follows a conditional beta convergence process over the Washington consensus period that was mainly driven by structural differences in fiscal burdens and external debt, while during the second period it was explained by conjunctural differences in the fiscal burden, GDP per capita and the growth of trade and capital openness.

This paper evaluates the impact of the most common innovation linkages by type of innovation activity on firms' innovation inputs and outputs. In order to estimate the casual effects, we employ Inverse Probability Weighting, while focusing on exclusive cooperative agreements to prevent our results from being affected by the presence of additional relationships in other activities or with other types of partners. Results indicate that cooperation in non-R&D innovation activities positively affects the introduction of new-to-the-firm product, marketing and organizational innovations, while cooperation in both R&D and non-R&D activities also affects R&D intensity and new-to-the-market product innovation. Furthermore, firms that cooperate exclusively in obtaining information, which is mainly carried out with suppliers and customers, are more likely to introduce new-to-the-firm product and organizational innovations.Keywords: non-R&D cooperation; technological capabilities; impact assessment.Abstract: This paper evaluates the impact of the most common innovation linkages by type of innovation activity on firms' innovation inputs and outputs. In order to estimate the casual effects, we employ Inverse Probability Weighting, while focusing on exclusive cooperative agreements to prevent our results from being affected by the presence of additional relationships in other activities or with other types of partners. Results indicate that cooperation in non-R&D innovation activities positively affects the introduction of new-to-the-firm product, marketing and organizational innovations, while cooperation in both R&D and non-R&D activities also affects R&D intensity and new-to-the-market product innovation. Furthermore, firms that cooperate exclusively in obtaining information, which is mainly carried out with suppliers and customers, are more likely to introduce new-to-the-firm product and organizational innovations.