The influence of research and development policy: the case of Estonia in the EU

Purpose – The purpose of this paper is to evaluate the international position of Estonia among the member states of the EU and countries closely associated with the EU, from the perspective of the effect of research and development (R & D) policy on innovation activities in the business sector. Design/methodology/approach – Based on existing scientific research literature on the relationships between R & D policy and business sector R & D activities and innovation performance, a set of indicators describing R & D policy measures was created for the business sector. Using principal component analysis (PCA) method, independent robust dimensions of R & D policy were brought out. After eliminating the problem of multicollinearity in R & D policy indicators, robust multiple regression models were conducted to present a comprehensive empirical description of the shaping of business sector R & D and innovation activities in the sample of investigated countries. Findings – Based on the literature, the influences of R & D policy measures on business sector R & D activities and innovation performance were systemised; public R & D policy dimensions were empirically defined; the intensity of R & D policy influence on business sector R & D activities was estimated; the differences between real and prognostic values of business sector performance indicators in Estonia were calculated in order to characterise the efficiency of Estonian R & D policy and the influence of the socioeconomic environment. Research limitations/implications – The lack of comparable data describing R & D policy and R & D activities and innovation performance in the business sector limits the comprehensiveness of the analysis (i.e. the number of analysed indicators). Practical implications – The assessment and comparative analysis of the influence of R & D policy components on business sector R & D activities and innovation performance in different countries makes it possible to identify directions for increasing the efficiency of R & D policy under the specific influence of the socioeconomic environment, especially in new member states of the EU. Originality/value – Using the PCA method significantly increased the robustness of the macro-quantitative description of R & D policy dimensions. By combining the set of new synthetic R & D policy indicators created by the PCA with the multiple regression analysis method, a significant increase in the robustness of model coefficients (i.e. the assessments of influence intensity) was achieved. These robust models create the basis for reliable empirical assessment of the influence of R & D policy and a comparative analysis of the results.