Endogenous Growth: A Sequential Stochastic Search Model for New Technology

Endogenous growth theories developed initially along two broad trends: one emphasizes knowledge and dynamics, with explicit modeling of knowledge accumulation; the other takes a broader view of capital and encompasses human capital in its definition. The scale effect critique initiated another trend that looks deeper inside the black box of technological change and its interactions with capital accumulation. This paper follows the last trend and builds upon the sequential search model of Bental and Peled (1996). Considering the uncertainty inherent in any search process, the model presents a dynamic stochastic system in which new technology and capital accumulation are bounded complements they complement each other to a point, but beyond this the impact of each factor is constrained by the level of the other. As a result, both technological progress and capital accumulation are necessary for sustained growth, but neither on its own is sufficient. Technological advancement stimulates capital accumulation by raising the marginal product of capital. Rapid capital accumulation stimulates R&D investments by raising the expected profitability of innovation. This paper discusses different possible regimes that an economy may find itself in as a result of the interactions between capital accumulation and technological innovations and has important implication for growth-promoting policies, knowledge spillover, and international flow of capital.