The paper analyzes the existence and impact of financing constraints as a possibly serious obstacle to innovation by .rms. Direct measures of financing constraints are employed using survey data collected by the Banque de France and the European Commission, which overcomes the problems with the traditional approach of trying to deduce the existence and impact of financing constraints through the significance of firm wealth variables. The econometric framework employed for this study is the simultaneous bivariate probit with mutual endogeneity. The paper discusses the important identification issue of coherency conditions in such LDV models with endogeneity and flexible temporal and contemporaneous correlations in the unobservable error terms. Conditions for coherency as discussed in the existing literature are reviewed and shown to be rather esoteric. Two novel methods for establishing coherency conditions are presented, which have intuitive interpretations. Finally, the paper presents alternative approaches for achieving coherency in models hitherto classified as incoherent through the use of prior sign restrictions on model parameters. This allows us to obtain estimates of the interaction between financing constraints and a firm’s decision and ability to innovate without forcing the econometric models to be recursive. Thus, direct as well as reverse interaction effects are obtained for the first time.Keywords: Limited Dependent Variable Models, Coherency ConditionsJEL Classifications: C51, C52, C15
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