Megatrend Revija (Jan 2016)

Structural modelling of economic growth: Technological changes

  • Sukharev Oleg

DOI
https://doi.org/10.5937/megrev1601053s
Journal volume & issue
Vol. 13, no. 1
pp. 53 – 82

Abstract

Read online

Neoclassical and Keynesian theories of economic growth assume the use of Cobb-Douglas modified functions and other aggregate econometric approaches to growth dynamics modelling. In that case explanations of economic growth are based on the logic of the used mathematical ratios often including the ideas about aggregated values change and factors change a priori. The idea of assessment of factor productivity is the fundamental one among modern theories of economic growth. Nevertheless, structural parameters of economic system, institutions and technological changes are practically not considered within known approaches, though the latter is reflected in the changing parameters of production function. At the same time, on the one hand, the ratio of structural elements determines the future value of the total productivity of the factors and, on the other hand, strongly influences the rate of economic growth and its mode of innovative dynamics. To put structural parameters of economic system into growth models with the possibility of assessment of such modes under conditions of interaction of new and old combinations is an essential step in the development of the theory of economic growth/development. It allows forming stimulation policy of economic growth proceeding from the structural ratios and relations recognized for this economic system. It is most convenient in such models to use logistic functions demonstrating the resource change for old and new combination within the economic system. The result of economy development depends on starting conditions, and on institutional parameters of velocity change of resource borrowing in favour of a new combination and creation of its own resource. Model registration of the resource is carried out through the idea of investments into new and old combinations.

Keywords