Elsevier

Energy Economics

Volume 34, Supplement 1, November 2012, Pages S15-S28
Energy Economics

“Investments and public finance in a green, low carbon, economy”

https://doi.org/10.1016/j.eneco.2012.08.036Get rights and content

Abstract

The paper evaluates the impacts on investments and public finance of a transition to a green, low carbon, economy induced by carbon taxation. Four global tax scenarios are examined using the integrated assessment model WITCH. Taxes are levied on all greenhouse gases (GHGs) and lead to global GHG concentrations equal to 680, 560, 500 and 460 ppm CO2-eq in 2100. Investments in the power sector increase with respect to the Reference scenario only with the two highest taxes. Investments in energy-related R&D increase in all tax scenarios, but they are a small fraction of GDP. Investments in oil upstream decline in all scenarios. As a result, total investments decline with respect to the Reference scenario. Carbon tax revenues are high in absolute terms and as share of GDP. With high carbon taxes, tax revenues follow a “carbon Laffer” curve. The model assumes that tax revenues are flawlessly recycled lump-sum into the economy. In all scenarios, the power sector becomes a net recipient of subsidies to support the absorption of GHGs. In some regions, with high carbon taxes, subsidies to GHG removal are higher than tax revenues at the end of the century.

Highlights

► Costs, investments and tax revenues induced by carbon taxes are only loosely related. ► Investments in power generation increase only with stabilization targets below 550 ppm CO2-eq. ► The carbon taxes induce an overall contraction of investments. ► Tax revenues can be as high as 20% of GDP and follow a “carbon” Laffer curve. ► Subsidies for absorption of GHG may be higher than carbon taxes at the end of the century.

Introduction

A large literature has assessed the macroeconomic cost of stabilising Greenhouse Gas (GHG) concentrations, with various assumptions on the environmental stringency of the adopted policy tool, on the technologies available, on the cost of those technologies, on the timing and on the degree of international cooperation (Cf. Barker et al., 2007, Clarke et al., 2009, Edenhofer et al., 2009, Edenhofer et al., 2010 for some overviews). The macroeconomic cost of a climate policy – e.g. the discounted loss of Gross Domestic Product (GDP) – is an important indicator and it certainly deserves an important place in both the academic and the policy debate on climate change mitigation. However, this is not the only piece of information on the economic implications of climate policy that policy makers and the business community would need to better plan future investments and policy decisions. For example, there is a large and growing demand for estimates of investments, particularly in the power sector, needed to cut GHG emissions and for estimates of the financial implications of climate policy, both at the national and international levels.1 Policy makers and the business community are indeed interested in knowing when and where investments should flow and how large they should be. A transition to a green economy may indeed require excessive financial resources and crowd out productive investments.

It is important to stress that estimates of macroeconomic costs and investment needs inform on two very different aspects of climate policy and should not be confused. Investments are expenditures that increase productive capital. They imply a financial transfer from one agent to another, from one sector of the economy to another sector, or from one generation to the next. If investments are re-distributed among capital assets that have the same productivity (i.e. that yield the same output per unit of investment) the level of macroeconomic activity is not affected. Macroeconomic costs arise when investments are redistributed from more productive uses to less productive uses. This loss of productivity generates a lower level of output, which is the true net cost of climate policy for the economy as a whole.

The Integrated Assessment Modeling community has been prolific in providing estimates of the macroeconomic costs of climate policy but has virtually neglected investment needs. For example, among the large set of papers collected in two recent Special Issues published by Energy Economics – one on the Energy Modeling Forum (Clarke et al., 2009) and the other on the Asia Modeling Exercise (Calvin et al., forthcoming) – none presents estimates of investment needs.

There is only a handful of studies that estimate investments flows and their distribution and financial implications using large-scale, sophisticated, energy-economy models (Edenhofer et al., 2009, IEA, 2010, IEA, 2011, Riahi et al., 2012). Among those, only Riahi et al. (2012) use the full potential of an Integrated Assessment Model (MESSAGE) to provide information on investment needs with a high technological detail under a mix of climate and energy policies which are consistent with a 2 °C above pre-industrial level in 2100. Edenhofer et al. (2009) provide little information on aggregate investments in the power sector. IEA (2010) and IEA (2011) provide estimates with high technological detail but the analysis is limited to 2030.2

This paper contributes to this embryonic literature by providing a detailed assessment of investment needs and public finance in four representative green economy scenarios generated using the Integrated Assessment Model WITCH (Bosetti et al., 2006, Bosetti et al., 2007, Bosetti et al., 2009a).3 The transition to a green, low carbon, economy is induced by four tax scenarios stabilising GHG concentrations in the atmosphere to 680, 560, 500 and 460 ppm CO2-equivalent (ppm CO2-eq) by the end of the century. As a consequence, global mean temperature increases in 2100 between 3.2 °C and 2 °C above pre-industrial levels. We examine the impact of climate policy on investments and current expenditures in the power sector, on investments in Research and Development (R&D) in the energy sector, on investments in the oil sector and on other aggregate non-energy investments. Investments in the power and in the oil sectors are endogenous in the model, as are energy demand and fuel prices. R&D investments are also endogenous. We complete our assessment of climate finance by providing estimates of carbon tax revenues and their implications on public finance.

With respect to Riahi et al. (2012), this paper analyses four climate policy targets instead of one. By focusing on climate policy alone instead than on a mix of climate and energy policies, we can establish a relationship between the stringency of the tax (the long-term concentration target) and investment needs. We also provide estimates of R&D investments in the energy sector and an assessment of carbon tax revenues, which are not part of the analysis of Riahi et al. (2012). Finally, we present separate results for OECD and non-OECD countries. Unfortunately, we cannot provide estimates of investments in demand side energy efficiency and in power transmission and distribution as in Riahi et al. (2012), because they are not modelled in WITCH.

The rest of the paper is organised as follows. Section 2 presents an overview of the WITCH model. Section 3 introduces the scenario design and presents basic facts of the Reference scenario and of the policy scenarios. Section 4 discusses the relationship between macroeconomic costs, investments and carbon tax revenues in a green, low carbon, economy. Section 5 illustrates changes in the optimal mix of investments and current expenditures in the power sector, investments in the oil upstream sector and in other sectors of the economy. Section 6 deals with investments in innovation. Section 7 examines revenues from carbon taxes. The final section provides a brief summary of our findings.

Section snippets

An overview of the WITCH model

WITCH – “World Induced Technical Change Hybrid” – is a regional integrated assessment model structured to provide normative information on the optimal responses of world economies to climate damages (cost–benefit analysis) or on the optimal responses to climate mitigation policies (cost-effectiveness analysis) (Bosetti et al., 2006, Bosetti et al., 2007, Bosetti et al., 2009a).

WITCH has a peculiar game-theoretic structure that allows modelling both cooperative and non-cooperative interactions

Scenarios

The international community has taken a precautionary stance by formally introducing the objective to keep global mean temperature increase below 2 °C in 2100 in the Cancun Agreements signed at the 16th UNFCCC Conference of Parties in 2010. However, this ambitious target has not been followed by either binding or informal adequate commitments to reduce GHG emissions. This leaves wide uncertainty on future mitigation efforts and consequent GHG concentrations by the end of the century. Hence, in

Macroeconomic costs, investments and tax revenues

Climate policy is costly in all four scenarios (Fig. 2). Carbon taxes direct investments towards more expensive technologies and push energy efficiency beyond the optimal level found in the Reference scenario. This drives the economy away from the most productive allocation of resources and reduces GDP (without accounting for the environmental benefit). Costs – measured as the difference between the discounted sum of Gross World Product (GWP) in the tax scenarios and the Reference scenario over

Investments in a low-carbon economy

In Section 3.2 we briefly mentioned that climate policy first induces energy savings and then a decarbonization of energy supply. Unfortunately, investments in end-use technologies cannot be assessed because the model does not have such level of detail. We can instead provide a close-up on the power sector, oil upstream investments and overall macroeconomic investments.

Zero – or low-carbon – generation technologies have investment costs per unit of installed capacity higher than the traditional

Investments in innovation

A key component of the optimal response to a carbon tax is innovation. WITCH endogenously determines the technological frontier in three sectors: aggregate end-use energy efficiency, a power sector backstop technology and a backstop substitute for oil in final consumption. Investments in energy efficiency R&D increase the stock of energy-related knowledge, which enhances the productivity of final energy in end uses. Investments in backstop R&D increase a sector-specific knowledge stock that

Carbon tax revenues

The four climate policy scenarios examined in the previous sections reveal that carbon taxes generate substantial fiscal revenues in OECD economies.16 The amount of the revenues depends on the level of the tax and on the tax base: they vary from a minimum of US$ 31 billion in 2015 for the 560 scenario to US$ 3.8 trillion in 2100 for the 560 scenario (Fig. 10a). In terms of GDP, tax revenues vary from a fraction of percentage point to

Conclusions

The Integrated Assessment Modeling community has been prolific in providing estimates of the macroeconomic costs of climate policy, but has virtually neglected investment needs and the distribution of investments over regions, sectors and time. This is however a crucial information to assess the finance side of climate policy. This paper aims at filling this gap in the literature by providing a detailed assessment of investment needs in four representative carbon tax scenarios generated using

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