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Estimation of Key Parameters for CGE Models

Estimation of Key Parameters for CGE Models. Azusa OKAGAWA JSPS Research Fellow National Institute for Environmental Studies. 1. Outline. Introduction Estimation of substitution elasticities What is the substitution elasticity? Econometric model and data Estimation results

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Estimation of Key Parameters for CGE Models

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  1. Estimation of Key Parameters for CGE Models Azusa OKAGAWA JSPS Research Fellow National Institute for Environmental Studies 1

  2. Outline • Introduction • Estimation of substitution elasticities • What is the substitution elasticity? • Econometric model and data • Estimation results • Simulations with estimated parameters • Summary 2

  3. Introduction • Many literatures on climate policy based on CGE modeling analysis • The simulation results and conclusions of them depend on the size of some parameters. • Substitution elasticities between production factors • The key parameters in CGE models should have empirical evidence. • Too high (low) elasticities lead to under- (over) estimates of the effects of climate policy. • The empirical foundation for the key parameters is lacking. • Based on old studies • Borrowing from famous models 3

  4. Research problem & contribution Research problem: We need more econometric analyses which specify the key parameters of CGE models to get more reliable simulation results. We estimated nested CES production functions using a panel data for OECD countries. Contribution: Our study improves the reliability of CGE models for climate policy by estimating nested CES production functions. 4

  5. What is the substitution elasticity? In most cases, we assume nested CES functions as production structures.

  6. Production structure & substitution elasticities KE-L form KL-E form Intermediate Inputs Intermediate Inputs Labor Energy Capital Energy Labor Capital Substitution elasticity between capital (K) and Energy (E) If changes by 1%, would change by %.

  7. Econometric model & data Firm’s cost minimization problem s.t. CES production function The model to be estimated Data: Panel data for 19 OECD countries with 18industries (1970-2004), formed by the EU-KLEM project of the European Commission. 7

  8. Estimation results 8

  9. Simulations by 4 models • 4 CGE models • KE-L model with conventional parameters • KE-L model with new parameters • KL-E model with conventional parameters • KL-E model with new parameters The goal of simulations: CO2 reduction by 13% to meet the Kyoto Target 9

  10. Comparison of simulation results We could over-estimate necessary carbon tax rate by 43% more if we use conventional values of key parameters for the KE-L models.

  11. Industrial output (%) 11

  12. CO2 emissions (%)

  13. Summary • We specified key parameters of CGE models by the econometric analysis. • Higher elasticities for energy intensive industries • Lower elasticities for non-energy intensive industries • If we use conventional parameters, we could over-estimate the impacts of the climate policy. • 43% higher reduction costs for 1t of CO2 emissions • Distribution of reduction costs of CO2 emissions between industries 13

  14. Thank you! Comments are welcome. okagawa.azusa@nies.go.jp 14

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