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Register a new userThe role of money and the financial sector in energy-economy models used for assessing climate policy
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Jean-Francois Mercure
Publication date
2015
fields
Financial
and research's language is
English
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This paper outlines a critical gap in the assessment methodology used to estimate the macroeconomic costs and benefits of climate policy. It shows that the vast majority of models used for assessing climate policy use assumptions about the financial system that sit at odds with the observed reality. In particular, the models assumptions lead to `crowding out of capital, which cause them to show negative impacts from climate policy in virtually all cases. We compare this approach with that of the E3ME model, which follows non-equilibrium economic theory and adopts a more empirical approach. While the non-equilibrium model also has limitations, its treatment of the financial system is more consistent with reality and it shows that green investment need not crowd out investment in other parts of the economy -- and may therefore offer an economic stimulus. The implication of this finding is that standard CGE models consistently over-estimate the costs of climate policy in terms of GDP and welfare, potentially by a substantial amount. These findings overly restrict the range of possible emission pathways accessible using climate policy from the viewpoint of the decision-maker, and may also lead to misleading information used for policy making. Improvements in both modelling approaches should be sought with some urgency -- both to provide a better assessment of potential climate policy and to improve understanding of the dynamics of the global financial system more generally.
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In this paper, we formulate a method for minimising the expectation value of the procurement cost of electricity in two popular spot markets: {it day-ahead} and {it intra-day}, under the assumption that expectation value of unit prices and the distributions of prediction errors for the electricity demand traded in two markets are known. The expectation value of the total electricity cost is minimised over two parameters that change the amounts of electricity. Two parameters depend only on the expected unit prices of electricity and the distributions of prediction errors for the electricity demand traded in two markets. That is, even if we do not know the predictions for the electricity demand, we can determine the values of two parameters that minimise the expectation value of the procurement cost of electricity in two popular spot markets. We demonstrate numerically that the estimate of two parameters often results in a small variance of the total electricity cost, and illustrate the usefulness of the proposed procurement method through the analysis of actual data.
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