Knowledge and space in models of regional development

Abstract

New knowledge is recognized as an important resource of positive dynamics of the territory development. As a result knowledge becomes an element of economic models that try to summarize regularities of economic growth and development of regions, cities and countries. The article provides structured analysis of the well known models to research regional development, which combines factors of knowledge and space. It studies ways of including knowledge and space in models, where the object of observation is territorial social and economic system, enterprise or agent possessing knowledge. Models of balanced growth, econometric ones and models with maximization aim are shown. At the same time space autocorrelation analysis and space regressive models can be used that help assess heterogeneity of innovation development in regions and identify influence zones. As a result methods of modeling general (industry) knowledge for territories with different level, global and local external effects, geographic identity of research of different types, maximization of research through alternative costs, monopoly industrial effects, impact of industrial competition and diversity, as well as knowledge ‘filter’ are revealed. Space characteristics of knowledge proliferation can be modeled through functions of activity and resistance, flexibility parameter, function of distance fading, parameter of transaction costs for knowledge transfer.