Policy simulation results of Computable General Equilibrium (CGE) models largely hinge on the choices of substitution elasticities among key input factors. Currently, most CGE models rely on the common elasticities estimated from aggregated data, such as the GTAP model elasticity parameters. Using firm level data, we apply the control function method to estimate CES production functions with capital, labor and energy inputs and find significant heterogeneity in substitution elasticities across different industries. Our capital-labor substitution elasticities are much lower than the GTAP values while our energy elasticities are higher. We then incorporate these estimated elasticities into a CGE model to simulate China's carbon pricing policies and compare with the results using GTAP parameters. Our less elastic K-L substitution lead to lower base case GDP growth, but our more elastic energy substitution lead to lower coal use and carbon emissions. In the carbon tax policy exercises, we find that our elasticities lead to easier reductions in coal use and carbon emissions.
Multi-sector general equilibrium models are used to simulate the effects of environmental policies on industry output and consumption at disaggregated levels. The specification of household demand in such models often use simpler forms such as CES or Linear Expenditure Systems since there are few estimates of more flexible systems. We estimate a 2-stage translog utility function that explicitly accounts for detailed energy expenditures to allow us to capture the price and income effects more accurately than these simpler forms. We incorporate this into a China growth model to simulate the effects of a carbon price to achieve the government targets for the Climate Change (Paris) agreements.
Final Manuscript in DASH.
An edited volume dedicated to Prof. Dale W. Jorgenson by his students and collaborators.