New Decisional Support Systems (DSS) are necessary at regional (local) level. DSS have to be able to estimate and control intangible capitals as the main source of wealth creation. Traditional analysis of internal accounting based on economic and financial models for companies, or supported by the economic analysis of income and employment, provides a short-term picture. In other words, the long term is not at the forefront and the value of the entity being studied is not conveniently quantified. Therefore, tools and approaches that provide a full future vision of any organization or institution should be a strategic priority for economic development. In this line, both the Lisbon Strategy and Leipzig Charter (2007) on Sustainable European Cities recognize that cities are 'centers of knowledge and sources of growth and innovation'. The exploitation of this knowledge depends on factors such as: training, existence of social and cultural networks, cultural excellence in research centers and the networks of exchange between science and industry. For this reason, integrated urban development policies are necessary. These policies support communication networks and optimize location structures as strategies that provide opportunities for social and democratic participation for the citizens. In order to achieve the above objectives, it is necessary to have tools to measure a territory's knowledge, that is, to design models to identify measure and monitor the different elements of this knowledge. This work proposes a approach to measure and evaluate this knowledge using the concept of intellectual capital for territories, but applied to cities. The measure of this intellectual capital enables us to determine what we must take into account to make cities a source of wealth, prosperity, welfare and future growth. Furthermore, local intellectual capital provides a measure of hidden wealth of the city and a new indicator with a long run vision. This capital is essential for the economic growth of cities, but estimation in cities depends on the level of information available. Thus, in this paper we develop and explain how to implement a model to estimate intellectual capital in cities. In this sense, our proposal is to provide a model for measuring and managing intellectual capital using socio-economic indicators for cities. These indicators offer a long term picture supported by a comprehensive strategy for those who occupy the local space, infrastructure for implementation and management of the environment for its development.
