Climate sentiments, transition risk, and financial stability in a stock-flow consistent model☆
Introduction
The transition to a low-carbon economy, and the achievement of carbon neutrality, requires both the scaling-up of low-carbon investments and the divestment from carbon-intensive investments (HLEG, 2018, NGFS, 2019). In the European Union (EU), it was estimated that reaching the EU 2030 climate and energy targets requires circa EUR 180 billion per year of new investments in renewable energy and energy efficiency (European Commission, 2018, HLEG, 2018). At the global level, the investments needed to achieve the low-carbon transition are estimated to be in the range of USD 1.6–3.8 trillion annually until 2050 for supply-side energy system investments alone (IPCC, 2018). However, despite a record high of USD 612 billion in 2017, global climate finance flows are still far from closing the green investment gap (CPI, 2019). On the one hand, the climate misalignment of investments hampers the feasibility to achieve the climate targets. On the other hand, it could drive new sources of risk for asset price volatility and financial stability, at the individual and systemic level (Monasterolo et al., 2017). Indeed, a disorderly low-carbon transition, i.e. the sudden introduction of climate policies and lack of full investors’ anticipation (Battiston et al., 2017), could lead to a fast revaluation of carbon-intensive assets and thus of portfolios’ performance (NGFS, 2019).
Already in 2015, the Governor of the Bank of England, Mark Carney, in his talk about the “Tragedy of the horizons” (Carney, 2015), pointed out that climate change could affect the performance of financial companies whose portfolios are exposed to climate risks, and could eventually trigger financial instability. Climate risk could impact the financial sector via two main channels of transmission, climate physical risk, i.e. climate-led extreme events leading to physical capital destruction, and climate transition risk, i.e. a disorderly introduction of climate policies that leads to an abrupt revaluation of entire pools of asset classes (Batten et al., 2016). These concerns were quantitatively assessed by Battiston et al. (2017)’s Climate Stress-test, which showed that individual investors’ exposure to losses stemming from climate transition risks are large and could be amplified by network effects. In particular, climate transition risk could emerge in the credit market and cascade to economic agents via financial contracts (e.g. loans), with implications on firms and households’ debt performance and banks’ financial stability (Stolbova et al., 2018).
Nevertheless, there is growing awareness of the fact that investors are not yet pricing climate risks in the value of financial contracts, thus potentially increasing their exposure to such risks (Morana and Sbrana, 2018, Monasterolo and de Angelis, 2020). Main barriers for aligning investments to the low-carbon transition are represented by the deep uncertainty that characterizes the introduction of climate policies, and the characteristics of climate risks (i.e. forward-looking behavior, non-linear transitions, deep uncertainty and endogeneity), which makes it a new type of risk for economic analysis (Monasterolo, 2020). In this regard, it has been recently recognized that traditional climate economics and financial pricing models are not able to incorporate climate risk characteristics because they are constrained by equilibrium conditions, reliance on average values and most-likely shocks assumptions of complete information and lack of arbitrage (Battiston and Monasterolo, 2019a).
Academics, financial supervisors, and investors have advocated the introduction of stable and coherent fiscal policies to signal the market and to address the mispricing of climate-related financial risks. A global carbon tax (CT), i.e. a tax on the contribution of carbon-intensive activities to the production of CO2 emissions (Stiglitz et al., 2017, IMF, 2019), is among the most debated policies. The CT would increase the production costs for carbon-intensive companies but most governments have delayed the introduction of a CT so far (Monasterolo and Raberto, 2018, Monasterolo and Raberto, 2019, Bovari et al., 2018, Mercure et al., 2018, Rausch et al., 2011, Zachmann et al., 2018). To overcome this gridlock, the role of monetary policies and prudential regulations has been considered. The European Commission has proposed the revision of the microprudential banking framework, i.e., the introduction of a green supporting factor (GSF) aimed to lower capital requirements for green investments (Dombrovskis, 2018). This proposal was subject to criticisms with regard to its potential implications on financial stability (Thomä and Hilke, 2018, Dafermos et al., 2018a).
The IPCC report 1.5 degrees C (IPCC, 2018) pointed out that the time window left for policymakers to implement the low-carbon transition is narrowing fast. Thus, understanding the conditions under which a CT or a GSF could represent an opportunity for scaling up green investments, while preventing unintended effects on financial stability, is crucial. In addition, it is fundamental to consider how the banking sector could react to the policy announcement showing climate sentiments and affect the outcome of the policy implementation. Indeed, if the banking sector expects and/or trusts the climate policy introduction, it could anticipate it by revising its lending conditions, i.e., by decreasing (increasing) the risk pricing associated to green (brown) loans. This change in lending conditions would directly affect green and brown firms’ profitability and investments, respectively by improving and worsening them. In contrast, if the banking sectors’ climate sentiments will not play out, i.e. if the banking sector decides to ignore the information of the policy announcement thus not pricing it in its lending contracts, the policy itself might not achieve its goals (CISL, 2015, Trucost, ESG Analysis, 2018, Bank of England, 2018). Given the role that access to credit and credit conditions play in firms’ investment decisions, a steep revision in interest rates could affect firms’ profitability and their ability to repay loans. This, in turn, would affect Non-Performing Loans (NPL), banks’ financial stability, and the country’s economic performance.
In this context, two main knowledge gaps remain. First, our understanding of the conditions under which the CT or the GSF could contribute to scale up new green investments or, in contrast, introduce new sources of risk for macroeconomic (e.g. countries’ GDP) and financial stability, is poor. Second, we don’t know yet how banks’ climatesentiments could affect the outcomes of the climate policy implementation and of the low-carbon transition. These two elements are interconnected and potentially self-reinforcing. On the one hand, the way in which climate policies are implemented in the economy, and their credibility, could impact investors’ performance by revising of firms’ costs and profitability (e.g. banks’ lending). On the other hand, the way in which investors respond to the information about the climate policy could determine the success of the low-carbon transition, as well as its implications for the financial sector.
We contribute to fill this gap by developing a stylized one high-income region, Stock-Flow Consistent (SFC) macroeconomic behavioral model that embeds an adaptive forecasting function of the banking sector’s climate sentiments. We focus on the conditions for climate transition risk to emerge from the interplay between climate-aligned policies’ implementation and banks’ behaviors. The SFC model represents several sectors of the economy and the credit market as a network of interconnected balance sheets where accounting identities hold irrespective of agents’ behavioral rules (Monasterolo and Raberto, 2018). Agents’ behavioral functions are derived from standard economic literature. Thus, the model simulations results are determined by agents’ behavioral functions and the balance sheet constraints proper of the SFC approach.
The model presents three main innovations on the state-of-the-art. First, we adopt a forward-looking approach to the pricing of climate risks in banks’ lending contracts and firms’ credit risk. This allows to account for the characteristics of climate transition risks in macroeconomic models, where the risk assigned to the firm (and thus the interest rate) by the banking sector is usually based on the firm’s past performance. Second, we explore the interplay between banking sectors’ climate sentiments and the climate policies’ implementation. In our model, the banking sector’s expectations about the effects of the policy implementation consider the future profitability of the brown and green firms. We build on traditional investors’ sentiments analysis (Greenwood and Shleifer, 2014, Lopez-Salido et al., 2017) and extend it in the context of climate transition risk, in a modeling framework that allows to consider endogenously generated behaviors and financial frictions. Third, we assess the transmission channels of two main policies and regulations under discussion, i.e. CT and GSF, on banks’ lending behavior (e.g. new green loans), the greening of firms’ investments in the economy, and on banking sector’s financial stability (consistently with Basel III (BIS, 2011)). As such, our approach allows us to identify the risk transmission channels from specific climate-aligned policies to economic and financial actors, the drivers of reinforcing feedbacks and the conditions for cascading losses via loans contracts.
We use the model to answer three research questions that are relevant for climate financial policies; (i) under which conditions a CT or GSF can foster green loans and investments in the economy, (ii) to what extent could trade-offs for financial stability emerge, and (iii), what role (if any) banking sectors’ climate sentiments may play in fostering or hindering the expected effect of the policies on the green economy and on financial stability.
The paper is organized as follows. Section 2 provides a review of the state-of-the-art on climate risks and financial stability, with a focus on investors’ climate sentiments and SFC models. Section 3 introduces the model, while Section 4 describes the three climate-aligned policy scenarios and their transmission channels. The results of the model’s simulations are discussed in Section 5. Section 6 concludes discussing economic and financial stability trade-offs associated to the climate-aligned policies, and provides insights for research steps ahead.
Section snippets
Banks’ stability after the Great Financial Crisis
In the aftermath of the 2008 Great Financial Crisis (GFC), academics and financial regulators have analyzed the drivers of financial risk, considering financial interconnectedness and complexity (Battiston et al., 2012, 2016).2
The model
In this section we present the framework of the Stock-Flow Consistent (SFC) model, the main accounting and behavioral equations of its sectors, and the non-linear adaptive forecasting function of the banking sector’s climate sentiments.
Model scenarios
We simulate and compare the impacts on green new investments, labor market, GDP and banking sector’s financial stability conditions of three policy scenarios characterized by (i) the introduction of a GSF; (ii) the introduction of a CT with or without banking sector’s climate sentiments and (iii) a Business as usual (BAU) scenario characterized by no change in climate-aligned policy and regulation.
Discussion of results
This section presents the main results of the model’s scenario simulations in Figs. 7–10.
Conclusion
In this paper we have developed a Stock-Flow Consistent (SFC) macroeconomic model to analyze under which conditions government’s fiscal policies (i.e. a Carbon Tax CT) and financial regulations (i.e. a Green Supporting Factor GSF) can contribute to foster the transition to a low-carbon economy, by signaling the banking sector. In addition, we analyzed to what extent unintended effects could emerge on economic competitiveness and banking sector’s financial stability.
Our model introduces a main
Acknowledgements
This paper is published as part of the Special Issue “Climate risks and financial stability,” which was co-edited by Stefano Battiston (University of Zurich and Ca' Foscari Univ. of Venice), Yannis Dafermos (SOAS University of London), and Irene Monasterolo (Vienna University of Economics and Business) and was kindly supported by the Joint Research Centre (JRC) of the European Commission, the Journal of Financial Stability, and the Center for Research in Contemporary Finance and the Gabelli
References (145)
- et al.
How does credit supply respond to monetary policy and bank minimum capital requirements?
Eur. Econ. Rev.
(2016) Macro effects of capital requirements and macroprudential policy
Econ. Model
(2014)- et al.
Identifying excessive credit growth and leverage
J. Financ. Stab.
(2018) - et al.
A model of investor sentiment
J. Financ. Econ.
(1998) - et al.
Financial networks and stress testing: challenges and new research avenues for systemic risk analysis and financial stability implications
J. Financ. Stab.
(2018) - et al.
Basel III and bank-lending: evidence from the United States and Europe
J. Financ. Stab.
(2018) The financial cycle and macroeconomics: what have we learnt ?
J. Bank. Financ.
(2014)- et al.
Coping with collapse: a stock-flow consistent monetary macrodynamics of global warming
Ecol. Econ.
(2018) - et al.
Forecasting economic and financial time-series with non-linear models
Int. J. Forecast.
(2004) - et al.
Climate change, financial stability and monetary policy
Ecol. Econ.
(2018)
Improving time series forecasting: an approach combining bootstrap aggregation, clusters and exponential smoothing
Int. J. Forecast.
Asymmetric information and the structure of the banking industry
Eur. Econ. Rev.
Credit provision and banking stability after the Great Financial Crisis: the role of bank regulation and the quality of governance
J. Int. Money Financ.
Challenges for financial stability in Europe
J. Financ. Stab.
Banking-industry specific and regional economic determinants of non-performing loans: evidence from US states
J. Financ. Stab.
Environmental macroeconomics
Carbon taxes
Directed technical change
Rev. Econ. Stud.
The environment and directed technical change
Am. Econ. Rev.
Curbing the credit cycle
Econ. J.
Neural Network Time Series Forecasting of Financial Markets
The price of complexity in financial networks
Proc. Natl. Acad. Sci. USA
A climate stress-test of the financial system
Nat. Clim. Change
The climate target gap is widening. can we close it by including climate finance in SSPs?
SSRN Electron. J.
A climate risk assessment of sovereign bonds’ portfolio
SSRN Electron. J.
DebtRank: too central to fail? Financial networks, the FED and systemic risk
Sci. Rep.
International Convergence of Capital Measurement and Capital Standards: A Revised Framework
Key determinants of non-performing loans: new evidence from a global sample
Open Econ. Rev.
A stock-flow consistent input-output model with applications to energy price shocks, interest rates, and heat emissions
N. J. Phys.
Basel III: A Global Regulatory Framework for More Resilient Banks and Banking Systems
Diagnostic expectations and credit cycles
J. Finance
Large potential reduction in economic damages under UN mitigation targets
Nat. Lett.
Stranded Assets and the Environment: Risk, Resilience, and Opportunity
Climate change challenges for central banks and financial regulators
Nat. Clim. Change
Resolving the Climate Paradox: Speech given by Governor of the Bank of England Chair of the Financial Stability Board
Arthur. Burn. Meml. Lect.
Market Models: A Guide to Financial Data Analysis
Unhedgeable Risk: How Climate Change Sentiment Impacts Investment
Comparative numerical analysis of two stock-flow consistent post-Keynesian growth models
Eur. J. Econ. Econ. Policies Interv.
Global Landscape of Climate Finance 2019
Fiscal policy and ecological sustainability: a post-Keynesian perspective
How can green differentiated capital requirements affect climate risks? A dynamic macrofinancial analysis
Journal of Financial Stability
Being Stranded on the Carbon Bubble? Climate Policy Risk and the Pricing of Bank Loans
Cited by (70)
Twenty-year tango: Exploring the reciprocal influence of macro-financial instability and climate risks
2024, Journal of Economic Behavior and OrganizationThe double materiality of climate physical and transition risks in the euro area
2024, Journal of Financial StabilityOver with carbon? Investors’ reaction to the Paris Agreement and the US withdrawal
2024, Journal of Financial StabilityFlood, farms and credit: The role of branch banking in the era of climate change
2024, Journal of Corporate FinanceClimate transition risk and bank risk-taking: The role of digital transformation
2024, Finance Research Letters
- ☆
ND, AN, IM want to thank Stefano Battiston (University of Zurich), Luca de Angelis (University of Bologna); the two anonymous reviewers and the editors of this special issue; the participants of the EAEPE conference 2019, the CliMath Workshop 2019, and the University of Zurich’s Sustainable Finance conference 2020 for their useful comments and discussion. IM acknowledges the support of the Austrian Climate Research Program’s (ACRP) 10th call project RiskFinPorto (KR17AC0K13647). ND, AN, IM 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). The usual disclaimer applies.
- 1
All authors contributed equally to this paper.