Climate risk and financial stability in the network of banks and investment funds

Highlights

• Study effects on financial stability of climate transition risk and market conditions.

• Extend the climate stress-test framework to the network of banks and investment funds.

• Derive analytical results to identify key drivers for climate transition risk.

• Application to a unique supervisory dataset (Mexico) in a wide range of scenarios.

• Strong market conditions allow to reach ambitious climate targets at low risk level.

Abstract

We analyze the effects on financial stability of the interplay between climate transition risk and market conditions, such as recovery rate and asset price volatility. To this end, we extend the framework of the climate stress-test of the financial system by including an ex-ante network valuation of financial assets which accounts for asset price volatility as well as for endogenous recovery rate on interbank assets. Moreover, we also consider the dynamics of indirect contagion of banks and investment funds, which are key players in the low carbon transition, via exposures to the same asset classes. We derive some analytical results and we apply the model to a unique supervisory dataset in a range of climate policy scenarios and market conditions. In the event of a disorderly low-carbon transition, stronger market conditions allow to reach more ambitious climate policies at the same level of financial risk.

Introduction

The current scientific knowledge about climate change provides strong evidence on climate risk, i.e. on the potential adverse effects of climate change on society and the economy in coming decades (Allen et al., 2018). In contrast, prices of assets are currently not reflecting such scientific knowledge. One set of arguments about this state of affairs has to do with the inability of financial markets to internalize externalities (Stiglitz et al., 2017, Stiglitz, 2019), in particular on time horizons longer than a few years.

Moreover, standard financial risk metrics (e.g. value-at-risk) are backward-looking, i.e. they are computed from historical time series of those prices. However, climate risk cannot be assessed based on past events, since they are not good predictors of the future in this respect. Therefore, standard financial risk metrics have to be enhanced in order to encompass forward-looking climate risk (Battiston et al., 2017, Battiston, 2019).

Given the interconnectedness of today’s business, these enhanced metrics of risk and impact need to be based on network models of investment chains (Vitali et al., 2011, Battiston et al., 2012).

In the aftermath of the Paris Agreement, the relationship between climate risk and financial stability has taken center stage in the policy debate (Carney, 2015, Bank of England, 2018). Several financial supervisors have conducted preliminary assessments of climate-related financial risk in their financial stability reviews. For instance, the European Central Bank (ECB) reported preliminary estimates of aggregate exposures of financial institutions to the Climate Policy Relevant Sectors (CPRS)¹ relative to their total debt securities holdings, as ranging between 1% for banks to about 9% for investment funds (ECB, 2019). Using the same methodology, the European Insurance and Occupational Pensions Authority (EIOPA) reported aggregate exposures of insurance companies at about 13% of their total securities holdings (EIOPA, 2018). Further analyses on the EU securities holdings report several relevant facts. Among financial investments in bonds issued by non-financial corporations, EU institutions hold exposures to CPRS ranging between 36.8% for investment funds to 47.7% for insurance corporations; similar figures for equity holdings range from 36.4% for banks to 43.1% for pension funds (Alessi et al., 2019). An analysis of climate transition risk (carried out as a collaboration between financial supervisors (EIOPA), researchers in climate economics and researchers in climate finance) indicate that losses on EU insurance portfolios of sovereign bonds could reach up to 1%, in conservative scenarios (Battiston et al., 2019a).

Building on the recent concept of climate stress-test of the financial system (Battiston et al., 2017), the importance of climate stress-testing for financial stability is now widely recognized by financial supervisors (Allen et al., 2020, Bolton et al., 2020, NGFS, 2020). Yet, several issues remain unaddressed.

In particular, the impact on financial stability of the interplay between climate policy shocks and market conditions (e.g. asset price volatility, recovery rate coefficients and asset liquidity, see Definition 1 in Section 5) has not been analysed so far. Thus, the main contribution of this paper is to try and fill this gap in the literature by providing an analytical understanding of the interplay between climate policy shocks and market conditions and an operational framework for climate stress-testing in this perspective. To this end, we combine in a novel way and for the first time, the Climate Stress-test framework (Battiston et al., 2017) with the NEVA framework for Network Valuation of Financial Assets (Barucca et al., 2020). In particular, we develop a component of the model to describe the impact of transition risk on both banks and investment funds, via a mechanism of common asset contagion, building on (Greenwood et al., 2015, Battiston et al., 2016). Climate stress-testing requires to combine knowledge and models from several domains. Despite the many aspects involved and the several components of the model, our investigation establishes some analytical results on the relations among climate transition risk, climate policy shocks and market conditions.

The second contribution is the application of the developed Climate Stress-test methodology to the Mexican financial system by using supervisory data from Banco de México. The data used to perform this exercise includes exposures of banks and investment funds to climate policy relevant sectors, interbank exposures and exposures among investment funds and banks. México is an interesting case study for two main reasons: (i) it is a large emerging economy, which is considered to be “vulnerable to the impacts of climate change” as well as an “important player in terms of GHG emissions” (SEMARNAT-INECC, 2016) and (ii) Banco de México has collected over time high-granularity financial data which can be used to perform sophisticated climate risks stress-tests. Our empirical results provide an assessment of climate transition risk in México, conditional to a range of climate policy shock scenarios. Notice that, while the numerical results are specific to the economy of México and, possibly, to other Latin American countries, the analytical results, and thus most of the policy implications, are more general.

The results have three policy implications discussed in Section 8. One key message from the findings is that, conditional to a disorderly transition, while an earlier transition poses lower transition risk, the level of climate policy ambition can be higher, at the same level of risk, if market conditions are strengthened enough.

The rest of the paper is structured as follows. Section 2 describes the main streams of literature that are relevant for the paper. 3 The model structure, 4 Climate module, 5 Financial contagion modules describe the methodology we have developed to carry out the extended climate stress-test analysis and the analytical results. Section 6 describes our data set. Section 7 reports on the results of the empirical exercise, and Section 8 concludes. A list of symbols is provided in Appendix A.