Endogenous Technological Change Adapted to the CGE Framework

Abstract

We introduce endogenous technological change in a multi-sector recursive dynamic Computable General Equilibrium (CGE) model. We consider the optimization problem faced by technology firms in choosing the optimal level of R&D intensity given market conditions. R&D intensity determines the number of innovations and the speed of technological change in each sector. In addition, firms can choose the direction of technological change; for instance, when designing, they may opt for less energy-intensive but more capital-intensive production when the price of energy increases. We also differentiate between local innovations whose outcomes are constrained by the global technology frontier and innovations that transcend this frontier. The incorporation of endogenous technological change has a significant impact on policy simulations. Once it is considered, the model predicts that climate policy (in the form of a carbon tax) has a significantly larger impact on emissions in the long-run than in the short run. Finally, we demonstrate how intertemporal knowledge spillovers lead to path dependency. The introduction of a carbon tax at an early stage induces early low-carbon R&D and early know-how accumulation, which in turn leads to higher productivity in low-carbon sectors and lower long-run costs of decarbonization when compared to the scenario of postponed carbon tax.