Due to a growing concern about climate change and sustainable development, it is necessary to develop and implement an effective policy for promoting of bio-economy. Latvia, as many other countries, lacks fossil energy resources; however, abundant bio-resources can be found on the land and in the water as well in residues and waste. More efficient promotion and rendering of bio-resources is one of the possibilities to promote sustainable development. It also helps to reduce an impact on the climate change and promotes adaptation to it, as well as reduces an import dependence on various resources and materials. Latvia faces a number of shortcomings, such as a lack of funding for education, research and development, insufficient cooperation between universities and industry, which drags the effective use of bio-resources. In order to develop an effective bio-economy sector, there is a need for coupling of human resources with relevant skills and knowledge with adequate institutional capacity, including infrastructure and financial resources. It is necessary to understand an interaction of the above mentioned elements as well as time required in order to develop an effective bio-economy policy, and an aim of the study was to create a model which helps to design such a policy. System dynamics modeling was chosen as a method in the study since it is well suited for analysis of complex and dynamic systems with nonlinearities, i.e. feedbacks, accumulation and delays. Until now, most of system dynamics models have been developed separately for education and innovation issues, moreover innovation subjects have been discussed on the level of individual companies. In this study, the system dynamics model has been built up by combining science, innovation and education elements, and assessment of different funding scenarios has been carried out. The results show that, under assumptions made, the scenario with the highest share of funding for research infrastructure, as well as research and development projects, could be more efficient in terms of potential to generate high value added products than the scenario with the highest share of funding allocated to education.