Abstract
The role of climate finance policies and instruments in scaling up and derisking low-carbon investments has received growing research attention. However, financial actors’ reaction to climate finance initiatives, and their implications on decarbonization of the economy and on inequality, has not been assessed yet. Our manuscript contributes to address this knowledge gap by analysing under which conditions government’s climate finance policies and investors’ climate risk adjustment can affect the success of the low-carbon transition and the ability to close the green investment gap. We further develop the EIRIN Stock-Flow Consistent behavioural model with a financial market, an energy market and investors’ portfolio choice of financial contracts, for the European Union. First, we study the macroeconomic impacts of government’s green subsidies that can be financed either by introducing an unanticipated carbon tax or by issuing green sovereign bonds. Then, we assess how investors adjust firms’ risk assessment in reaction to the carbon tax introduction, and how this affects firms’ low-carbon investment decisions. We find that both a carbon tax and green bonds financing can give rise to trade-offs in terms of decarbonization of the economy (absolute emission reductions), distributive effects and public debt sustainability. The channels of transmission differ and are policy and instrument specific. Green subsidies that are financed by green sovereign bonds issuance generate positive spillovers on GDP growth and less distributive effects than a carbon tax. Nevertheless, due to the relative decoupling of the economy, GDP growth impairs emission reduction efforts. Finally, investors’ climate risk adjustment helps to smooth this trade-off, contributing to a full decoupling.
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Notes
In our analysis, we consider scenarios of a disorderly transition, i.e. the riskier scenario for the economy and investors, characterized by an unanticipated introduction of a carbon tax.
In the EIRIN market economy, the capital good producer is never rationed in its production due to imports of raw materials from the foreign sector. As such, raw materials affect unit costs of production (and can be subject to price volatility and adjustments) but constitute no binding constraint for production. The assumption allows us to focus on the core of our analysis, i.e. the role of investment costs and access to finance for the renewable energy sector.
For the sake of simplicity, in the scenarios presented in this study, stocks are only owned by the capitalist household.
The symbol † is used to differentiate the prices of securities on the financial market from the prices of goods as traded otherwise in the economy. The symbol HCode \(\hat {}\) over a variable denotes that it is an expected value.
The average money wage w is subject to a growth between two consecutive simulation steps given by Δw/w = −γ1 + γ2 e, where γ1 and γ2 are positive parameters subject to the condition γ2 > γ1, and e is the employment rate. See Monasterolo and Raberto (2018) for a detailed description of the money wage setting in EIRIN.
The design of government’s policies to derisk private investments in the low-carbon transition is informed by the role of public authorities in Public Private Partnerships (PPP, such as the approach of the European Investment Bank (EIB)) and contributes to decrease investment risk for private investors, while they gain experience in green energy markets.
For an extensive sensitivity analysis of different degrees of policy combinations between tax financing, green bond financing and investors’ reactions please be referred to Section 6.2 of this paper.
A more detailed description of the Monte Carlo simulation is included in Appendix A
This comes at no surprise since all climate policy scenarios benefit from the same level of green subsidies by the government
In our analysis, we consider scenarios of disorderly transition, i.e. the riskier scenario for the economy and investors, characterized by an unanticipated introduction of a carbon tax.
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Acknowledgements
All authors are grateful to Marco Raberto (University of Genoa) for support and comments on the model development. All authors want to thank Stefano Battiston (UZH), Asjad Naqvi (IIASA), the two anonymous reviewers and the editors of this special issue; the participants of the EAEPE conference 2019 and 2020, the 18th International Conference on Credit Risk Evaluation 2019, and the University of Zurich’s Finexus conference 2020 for their useful comments and discussion of results. IM, ND, AM acknowledge the support of the ACRP 11th call project GreenFin “Scaling up green finance to achieve the climate and energy targets: An assessment of macro-financial opportunities and challenges for Austria” (KR18AC0K14634). IM acknolwedges the financial support from the European Union’s Horizon 2020 research and innovation programme [CASCADES, grant number 821010] and the European Investment Bank Institute [EIBURS project ESG-Credit.eu]. The findings, interpretations and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. The usual disclaimer applies.
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Appendix A: Monte Carlo simulation results
Appendix A: Monte Carlo simulation results
In this section, we include the results of the Monte Carlo simulation, showing the mean and the standard deviation of the main model’s outcomes over 20 seeds for the pseudo-random number generator. Table 7 highlights that the presented results are robust over different seeds showing a low standard deviation for all the considered variables. The main reason relies on the fact that the only source of stochasticity in the model is related to the desired weight (or fraction) of financial wealth that each investor is willing to allocate to stocks and bond asset classes (see Eq. 3). Therefore, while the random component affects financial and real variables, the magnitude of the impact does not crucially affect the macro-financial outcomes.
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Monasterolo, I., Dunz, N., Mazzocchetti, A. et al. Derisking the low-carbon transition: investors’ reaction to climate policies, decarbonization and distributive effects. Rev Evol Polit Econ 3, 31–71 (2022). https://doi.org/10.1007/s43253-021-00062-3
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DOI: https://doi.org/10.1007/s43253-021-00062-3
Keywords
- Climate finance
- Carbon tax
- Green bonds
- Decarbonization
- Climate risk adjustment
- Distributive effects
- Stock-Flow Consistent model