The influence of public programs on inter-firm R&D collaboration strategies: project-level evidence from EU FP5 and FP6

Inter-firms R&D collaborations are often seen as an effective mean to access new resources, to innovate and/or to enter new markets in a turbulent environment characterized by fierce competition. However, all R&D partnerships do not have the same strategic importance. We analyze the strategic features of two types of partnerships that are seldom compared in the academic literature on R&D alliances: EU-sponsored inter-firms collaborations on the one hand, and non-sponsored, spontaneous inter-firm collaborations on the other. We compare their incentives and coordination mechanisms, and derive theoretical propositions that we test empirically. Our econometric analysis uses original data on (sponsored and non-sponsored) projects conducted by participants in the 5th and 6th European R&D Framework Programs. Our empirical findings support our main propositions. EU-funded collaborations are more exploratory and more focused on peripheral competences than spontaneous R&D collaborations. They are also less flexible, due to rigid monitoring rules which are nevertheless crucial to the projects?? success. However, there is no major difference between the different types of EU-sponsored collaborations, which pleads for a simplification of these policy instruments.     

Understanding Interaction Models: Improving Empirical Analyses

William Roberts Clark University of Michigan, Center for Political Studies, ISR 4202 Box 1248, 426 Thompson Street, Ann Arbor, MI 48106-1248 Matt Golder Florida State University, Department of Political Science, 531 Bellamy Building, Tallahassee, FL 32306-2230 e-mail: thomas.brambor{at}nyu.edu e-mail: wrclark{at}umich.edu e-mail: matt.golder{at}nyu.edu (corresponding author) Multiplicative interaction models are common in the quantitativepolitical science literature. This is so for good reason. Institutionalarguments frequently imply that the relationship between politicalinputs and outcomes varies depending on the institutional context.Models of strategic interaction typically produce conditionalhypotheses as well. Although conditional hypotheses are ubiquitousin political science and multiplicative interaction models havebeen found to capture their intuition quite well, a survey ofthe top three political science journals from 1998 to 2002 suggeststhat the execution of these models is often flawed and inferentialerrors are common. We believe that considerable progress inour understanding of the political world can occur if scholarsfollow the simple checklist of dos and don'ts for using multiplicativeinteraction models presented in this article. Only 10% of thearticles in our survey followed the checklist.     

Presidential Coattails and Legislative Fragmentation

Considerable evidence suggests that legislative fragmentation can negatively affect the survival of democratic presidential regimes. While there is a vast literature examining the determinants of legislative fragmentation, one factor that has traditionally been overlooked is the impact of presidential elections. Do presidential elections increase or decrease legislative fragmentation? Does it matter if presidents are elected by plurality rule or by runoff? Using a new dataset that covers all democratic legislative and presidential elections between 1946 and 2000, I find that presidential coattails can reduce, increase, or have no effect on legislative fragmentation depending on the number of presidential candidates. I also find strong evidence that social heterogeneity increases the number of presidential candidates when runoff systems are employed. Taken together, these results suggest that the widespread adoption of runoffs by newly democratic presidential regimes will likely increase legislative fragmentation, thereby putting their democratic survival at increased risk.