This paper reviews the principal econometric models used to measure the effects of public support for firm R&D investment. A taxonomy classifying papers according to the estimation method used (system of equations versus reduced-form), type of data (cross-sectional versus longitudinal), and type of policy variable (binary versus continuous) is provided. Through a historical reconstruction of the literature, the review starts by exploring the main features of early structural models and their recent refinements, by paying special attention to the issue of subsidy endogeneity. Subsequently, it discusses the second generation of the structural approach, the Selection-models, pointing out their ability in properly describing the two-player form of an R&D incentive scheme. It then goes on by treating and discussing more data-driven approaches, such as those based on Control-function and, more specifically, Matching. Finally, we address evaluation methods rooted in dynamic models of imperfect competition, considered as a novel promising stream of research within the last generation of ‘harder’ structural approaches. A discussion of features, advantages and drawbacks of each approach in a comparative perspective is offered to the reader, as well as suggestions for future improvements in this field of economic research.