Knowledge Diffusion and Learning by Doing

Economic growth based on innovation is stimulated by two major factors. The most important is learning by doing which has many facets. The other is the interaction effect through spillovers. Young (1991) discussed in detail the different aspects of learning by doing and how it brings about technical and managerial advances in knowledge economies, which spill over from one sector or product to another. The learning by doing may be simply characterized by an equation C n = A E n − b $${C_n} = AE_n^{ - b}$$ , where C n is the cost of production of the n-th unit, E n is the cumulative output up to and including the n-th unit and A is the cost of the first unit and b is the elasticity of technical progress. In Arrow’s (1962) learning by doing, E n may denote cumulative experience that may be proxied by cumulative investment or total capital including both physical and knowledge capital. In this formulation b > 0 and productivity gains from learning by doing are unbounded. Young (1991) argues that this may not hold empirically unless there comes a stream of new Schumpeterian innovations. The spillover or externality effect not only helps the development of new productive technologies but also stimulates the process of rapid learning by doing. Both the diffusion and the learning by doing methods of technology transfer have a stochastic component, since there are inherent uncertainties associated with R&D and the fact remains that producers using newly produced technologies rarely achieve commercial viability until after they experience a prolonged period of learning by doing.