Climate Transition Risk and Development Finance: A Carbon Risk Assessment of China's Overseas Energy Portfolios

• Published date: 01 November 2018
• Date: 01 November 2018
• Author: Stefano Battiston,Irene Monasterolo,Jiani I. Zheng
• DOI: http://doi.org/10.1111/cwe.12264

©2018 Institute of World Economics and Politics, Chinese Academy of Social Sciences

China & World Economy / 116–142, Vol. 26, No. 6, 2018

116

*Irene Monasterolo (corresponding author), Assistant Professor, Vienna University of Economics and Business,

Austria and Visiting Fellow, Boston University, USA. Email: irenemon@bu.edu; Jiani I. Zheng, PhD Candidate,

Department of Banking and Finance, University of Zürich, Switzerland. Email: isabelle.zheng@bf.uzh.ch;

Stefano Battiston, SNF Professor, Department of Banking and Finance, University of Zürich, Switzerland.

Email: Stefano.battiston@uzh.ch. Monasterolo and Battiston acknowledge financial support from the Global

Development Policy Center at Boston University. Battiston acknowledges financial support from the Swiss

National Fund Professorship (No. PP00P1-144689) and the EU H2020 project ISIGrowth (No. 649186).

Battiston and Zheng acknowledge the support of the Institute of New Economic Thinking through the Task Force

in Macroeconomic Efciency and Stability led by Nobel Laureate Joseph Stiglitz.

Climate Transition Risk and Development Finance:

A Carbon Risk Assessment of China’s Overseas

Energy Portfolios

Irene Monasterolo, Jiani I. Zheng, Stefano Battiston*

Abstract

The role of development finance institutions in low-income and emerging countries

is fundamental to provide long-term capital for investments in climate mitigation and

adaptation. Nevertheless, development nance institutions still lack sound and transparent

metrics to assess their projects’ exposure to climate risks and their impact on global climate

action. To attempt to fill this gap, we develop a novel climate stress-test methodology for

portfolios of loans to energy infrastructure projects. We apply the methodology to the

portfolios of overseas energy projects of two main Chinese policy banks. We estimate their

exposure to economic and financial shocks that would result in government inability to

introduce timely 2°C-aligned climate policies and from investors’ inability to adapt their

business to the changing climate and policy environment. We nd that the negative shocks are

mostly concentrated on coal and oil projects and vary across regions from 4.2 to 22 percent

of the total loan value. Given the current leverage of Chinese policy banks, these losses could

induce severe nancial distress, with implications on macroeconomic and nancial stability.

Key words: climate-nance, climate policy scenarios, climate stress-test, climate transition

risk, climate VaR, energy infrastructure loans.

JEL codes: G01, G11, G32, G33

I. Introduction

There is growing awareness among development finance institutions of the need to

©2018 Institute of World Economics and Politics, Chinese Academy of Social Sciences

Climate Transition Risk and Development Finance 117

factor climate change into the nancial risk assessment of their portfolios (Bonnel and

Swann, 2015; AfDB et al., 2016). Indeed, climate change could negatively impact the

value of their investments and their portfolios’ performance (Carney, 2015; ESRB, 2016;

Battison et al., 2017; Draghi, 2017). Given the complexity of the international network

of nancial exposure (Battiston et al., 2012, 2016a,b) and the interconnectedness of the

nancial system, introducing climate risks into nancial risk metrics is fundamental to

identify and control potential nancial systemic risk (Battiston et al., 2017). In addition,

development banks have also recognized the importance of assessing the opportunities

generated by their projects in terms of the impact on climate action (mitigation and

adaptation), and their alignment to the Paris Agreement and Sustainable Development

Goals (SDGs). However, development nance institutions continue to apply in-house,

tailored metrics to mainstream climate risk assessment across the phases of project

selection and evaluation. This gap represents a barrier to delivery of their mandate and

for scaling up private investments into low-carbon sectors.

The energy sector plays a key role for a smooth low-carbon transition. On the one

hand, the burning of coal, natural gas and oil for electricity and heat is the largest single

source of global greenhouse gas (GHG) emissions, equal to 35 percent of the total in

2010 (IPCC, 2014). On the other hand, investments in fossil fuel-based energy sectors

constrain the beneciary country to a high carbon path, representing a risk of carbon-

stranded assets in the economy and nancial solvability to investors in the transition to a

low-carbon economy.

Academic research has made progress in developing measures of financial

portfolios’ exposure to GHG emissions considering investors’ market share in carbon-

intensive sectors that could become stranded assets (Monasterolo et al., 2017). Progress

has also been made in modeling the macroeconomic and distributive impacts of climate

policies (Dafermos et al., 2018; Monasterolo and Raberto, 2018) and assessing the

possible amplification of climate policy shocks resulting from feedback loops within

the nancial system (in the presence of a high leverage and recovery rate lower than 1)

and the cascade effects on the economy (Stolbova et al., 2018). Recent research has

highlighted the role of network analysis to assess the impact of carbon-stranded assets

across nancial and economic sectors (Campiglio et al., 2017). However, theoretical and

empirical applications of these insights into development nance are missing.

In an attempt to ll this gap, we develop the rst climate stress-test methodology

targeted to development nance institutions by building on Battiston et al. (2017), and

apply it to the overseas energy loans of two major Chinese policy banks: the China

Development Bank (CDB) and the Export–Import Bank of China (CEXIM). With the

climate stress-test, we can evaluate today the expected value of a loan exposed to a