We evaluate a Generalized Structural Equation Model (GSEM) approach to the estimation of the relationship between R&D, innovation and productivity that focuses on the potentially crucial heterogeneity across technology and knowledge levels. The model accounts for selectivity and handles the endogeneity of this relationship in a recursive framework. Employing a panel of Swedish firms observed in three consecutive Community Innovation Surveys, our maximum likelihood estimates show that many key channels of influence among the model's components differ meaningfully in their statistical significance and magnitude across sectors defined by different technology levels.