The role of money and the financial sector in energy-economy models used for assessing climate and energy policy: Climate Policy: Vol 18, No 2

	Park SJ 🌹朴勝俊 Anti-Austerity 反緊縮・脱原発・環境税・反安倍政権 (@psj95708651)
2019/11/14 16:32 @erickqchan Cambridge Econometricsの友人に聞いてみました。E3MEモデルは確かに、内生的貨幣を導入しているとのことです（私はまだ理解できてません）。関連論文がこれ。 tandfonline.com/doi/full/10.10… 依託があれば、グリーンニューディールの分析もできるよう準備しているそうです。すごいな。

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The role of money and the financial sector in energy-economy models used for assessing climate and energy policy: Climate Policy: Vol 18, No 2

https://www.tandfonline.com/doi/full/10.1080/14693062.2016.1277685?scroll=top&needAccess=true

The role of money and the financial sector in energy-economy models used for assessing climate and energy policy

This article outlines a critical gap in the assessment methodology used to estimate the macroeconomic costs and benefits of climate and energy policy, which could lead to misleading information being used for policy-making. We show that the Computable General Equilibrium (CGE) models that are typically used for assessing climate policy use assumptions about the financial system that sit at odds with the observed reality. These assumptions lead to ‘crowding out’ of capital and, because of the way the models are constructed, negative economic impacts (in terms of gross domestic product (GDP) and welfare) from climate policy in virtually all cases.

In contrast, macro-econometric models, which follow non-equilibrium economic theory and adopt a more empirical approach, apply a treatment of the financial system that is more consistent with reality. Although these models also have major limitations, they show that green investment need not crowd out investment in other parts of the economy – and may therefore offer an economic stimulus. Our conclusion is that improvements in both modelling approaches should be sought with some urgency – both to provide a better assessment of potential climate and energy policy and to improve understanding of the dynamics of the global financial system more generally.

POLICY RELEVANCE

This article discusses the treatment of the financial system in the macroeconomic models that are used in assessments of climate and energy policy. It shows major limitations in approach that could result in misleading information being provided to policy-makers.

1. Introduction

1.1. The world can meet the 2°C target – but who will pay?

There is a gradually emerging consensus that a global emissions pathway that is consistent with the target of keeping emissions concentrations below 450ppm, and thus of having a 50% chance of limiting anthropogenic climate change to 2°C above pre-industrial levels, is technologically feasible (IPCC, 2014). The question of whether the 2°C target will be met or not is therefore a political one to do with the allocation of scarce resources; essentially to determine who will pay if the world is to meet its collective target.

It seems beyond doubt that targets for emissions levels will not be met without the introduction of new policy. As outlined in Grubb, Neuhoff, and Hourcade (2014), there are three main forms this policy could take: 

• Policies to improve the use of energy with existing technologies, such as enforcing efficiency standards through regulation.

• Policies to ensure an efficient allocation of resources given existing technologies, for the main part through market-based mechanisms (market-pull policies).

• Incentives to develop new technologies, for example through providing tax credits on R&D expenditure (technology-push policies).

These policies differ substantially in scope, and their responsibility may not even fall under the same government departments, but they do have some common characteristics. While all of them will involve a reallocation of economic resources compared to what would have happened without government intervention, most will also involve substantial amounts of investment. The effects of the policies will therefore be felt both in the real economy and across the financial system; understanding the interaction of investors in low-carbon technologies with the banks and other financial institutions that provide the necessary credit and the companies that produce or install the equipment will be key to assessing overall impacts.

In summary, all of these types of policy will lead to economic winners and losers, with financial consequences at both the micro and macro levels. In a modern economy, all must therefore be justified prior to implementation. Quantitative models contribute to this process by providing evidence of the likely costs and benefits of potential policy.

1.2. The role of E3 models and IAMs in policy analysis

The emphasis placed on computer modelling in climate and energy policy has been increasing steadily as data have improved and additional computer power has allowed the development of more complex tools. Large-scale climate models and Integrated Assessment Models (IAMs) are central to the analysis carried out by the Intergovernmental Panel on Climate Change (IPCC) both to estimate the current emissions trajectory and paths with which there is a reasonable chance of staying within the 2°C target.

When it comes to assessing the implications of climate and energy policy on the wider society, E3¹ (Energy-Environment-Economy) models are applied to estimate impacts on indicators such as gross domestic product (GDP), welfare and employment. The terminology is not always used consistently, but in this article E3 models are defined as essentially macroeconomic models that have been extended to include some physical relationships. Their use has been well-established since at least the IPCC’s second assessment report (IPCC, 1995) and the relative weight placed on model results has increased over the past decade. For example, the European Commission’s Better Regulation Guidelines (European Commission, 2015, p. 32) state that for any policy assessment: 

Where possible, sensitivity and/or scenario analysis should be conducted to help test robustness of the analysis.

with a footnote added to the text that takes the reader directly to a description of the main quantitative methods that can be applied.

The Better Regulation guidelines note that not all impacts can be quantified but require that all quantitative evidence is assessed. The EU’s previous Impact Assessment guidelines were even clearer: 

If quantification/monetisation is not feasible, explain why. European Commission (2009, p. 39).

Taken together, and given the often-disparate effects of climate policy on the economy, the message is quite clear – for any new climate or energy policy proposals to be accepted at European level it is necessary to provide model-based evidence of the macroeconomic impacts.

1.3. Different types of macroeconomic models

In many cases policy makers’ understanding of macroeconomic models has not kept pace with the more prominent role that the models play in policy analysis. This is unfortunate as it is not possible to interpret properly the results from the models without understanding the underlying mechanisms; and, furthermore, there are substantial differences between the ways the models work. It is recognized in the field that there is an inherent difficulty in communicating an understanding of complex tools to time-pressured policy makers who may not come from a quantitative or economic background. There are efforts to address this, for example in providing specialized training.

The models that are used to assess the macroeconomic impacts of climate and energy policy fall broadly into two groups. These are²: 

• Computable General Equilibrium (CGE) models that are usually described as being based on neoclassical microeconomic assumptions. These models assume that agents (e.g. firms, households) optimise their behaviour so as to maximise their personal gains. Well-known international CGE models include GEM-E3 (Capros, Van Regemorter, Paroussos, & Karkatsoulis, 2013), GTAP (Hertel, 1999), and the Monash model (Dixon & Rimmer, 2002). The Handbook of Computable General Equilibrium Modeling (Dixon & Jorgensen, 2012) describes in detail how these models work. Model intercomparison exercises, such as those carried out by the Energy Modelling Forum (e.g. Weyant & de la Chesnaye, 2006) typically compare the results from different CGE models.

• Macro-econometric models that are derived from a post-Keynesian economic background.³ These models do not assume that agents optimize their behaviour, but instead derive behavioural parameters from historical relationships using econometric equations (which allow for ‘bounded rationality’). Well-known international macro-econometric models include E3ME (Cambridge Econometrics, 2014) and GINFORS (Lutz, Meyer, & Wolter, 2010; Meyer & Lutz, 2007).

The aim of this article is not to describe in detail the differences between the modelling approaches.⁴ The focus of this article is instead on describing how the different models represent the global investment that will be required to meet the 2°C target, how such representations influence model results, and how this information can be interpreted by decision makers. Closely tied to this issue is the question of how the models treat banks, money and the financial sector, which is introduced below.

1.4. Why is the treatment of money and finance important in macroeconomic models?

It is beyond doubt that substantial investment will be required to meet the 2°C target. The IEA (2014, p. 93) estimates that at global level $2.4trn (2013 prices) ‘clean energy investment’ must be made annually in its 450ppm scenario. All of this investment must be financed somehow; although some could be diverted from investment in developing fossil fuel resources, the investment-intensive nature of low-carbon technologies (e.g. renewables, nuclear, energy efficiency) means that any policy scenario in which emissions are reduced is likely to require an increase in energy-sector investment. The question of how the investment is financed, and whether more investment resources can be mobilized, is therefore key to understanding the economics of a low-carbon transition.

There are, however, also other reasons to focus attention on finance. As was made painfully aware by the financial crisis and subsequent recession, even sophisticated macroeconomic models have only a rudimentary treatment of finance.⁵ While there have been attempts outside mainstream economics to build macroeconomic models with better links to finance (originating from Minsky, 1982), these are not developed enough to apply to climate or energy policy.⁶ The treatment of banks and the financial sector is therefore done largely by assumption. Furthermore, as is demonstrated below, these assumptions vary enormously between the different modelling approaches. The goal of this article is to review the state of the art in theory and modelling, and make the reader aware of how the choice of model type influences the outcomes of policy assessments, and for what specific reasons.

The main modelling approaches are described in Section 3. First, however, we describe the underlying theory and how it relates to the different schools of economic thought. In Section 4 we turn attention to the lessons for policy makers from our analysis. Section 5 concludes.