SYSTEM DYNAMICS FOR EVALUATION OF PUBLIC POLICIES

Nowadays it is very difficult to make effective strategic decisions based on evidence. The design and evaluation of public policies is one field in which this process becomes complicated. In some context in which agents act according to linear rules traditional methodologies are enough. However, social systems are determined by heterogeneous agents who act according to non-linear rules, so in these cases traditional tools do not offer enough support for the evaluation. We propose social simulation using System Dynamics (SD) simulation technique as an alternative which better fits the requirements of this research. This paper evaluates two selected programs of the Department of Economic, Rural and Territorial Development of the Regional Government of Gipuzkoa (GFA). Previously an ex-ante evaluation of those policies was done; in this research the ex-post evaluation was developed in SD to measure the impact of these policies in our region. Policy makers set objectives to support economic, environmental and social sustainability, and define funding and assistance programs to meet those objectives. In this study, we selected the objective of the Department of Economic, Rural and Territorial Development "improve competitiveness through fostering collaborative networks". Such networks could be created between different agents, such as SMEs, public institutions, universities and research centers. The results suggest that social simulation techniques can support the evidence-based decision making process at a policy level. Moreover, we conclude that the importance of collaborations between different agents in the industrial sector cannot be underestimated. Collaborations are directly linked to competitiveness, and organizations need to be competitive in order to survive in this changing society. This system of study, an evaluation tool through simulation, can help the design and evaluation of public policies. Moreover, the factors, behaviors and situations of SMEs and public institutions, which influence collaboration networks, have been identified through this research.