Gimar special topic edition the impact of climate change on the financial stability of the insurance sector

Graph 13:
Stress factors for sovereign bonds
Source: Bloomberg, ND-GAIN and own IAIS calculations
Graph 12:
ND-GAIN index versus five-year CDS spreads
Source: ND-GAIN, Bloomberg and WorldGovernmentBonds
DZA
AGO
ARG
AUS
AUT
AZE
BGD
BEL
BOL
BWABRA
BRN
BGR
CMR
CAN
CHL
CHN
COL
CRI
HRV
CYP
CZE
DNK
DOM
ECU
EGY
SLV
EST
FIN
FRA
GAB
DEU
GHA
GRC
GTM
HND
HUN
ISL
IND
IDN
IRL
ISR
ITA
JAM
JPN
JOR
KAZ
KEN
KWT
LVA
LBN
LTU
LUX
MKD
MWI
MYS
MLT
MRT
MUS
MEX
MDA
MNG
MNE
MAR
MOZ
NAM
NLD
NZL
NIC
NGA
NOR
OMN
PAK
PAN
PNG
PRY
PER
PHL
POL
PRT
QAT
ROU
RUS
RWA
SAU
SEN
SRB
SGP
SVK
SVN
ZAF
KOR
ESP
LKA
SWE
CHE
TZA
THA
TTO
TUN
UGA
UKR
ARE
GBR
USA
URY
VNM
ZMB
30
35
40
45
50
55
60
65
70
75
80
-
100
200
300
400
500
600
700
ND
-G
A
IN
index
5year CDS (in basis points)

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34
The real estate factors in this report contain:
»
 
A transition risk-related component calculated
using the Readiness ND-GAIN Index and five-
year country CDS spread in a statistical model:
»

A physical risk-related component calculated

using the WRI
42
and an assumed recovery rate 
of 40%:
43
As noted in section 3, a physical risk component 
is added using WRI data because the Readiness 
ND-GAIN Index may not be a comprehensive 
proxy for the climate-related risks associated 
with real estate within a particular jurisdiction. 
These stress factors are principally driven by 
physical exposure to natural catastrophes such 
as earthquakes, storms, flooding, droughts and 
sea level rise. The WRI data focuses specifically 
on natural catastrophe events most relevant for 
physical risks to real estate.
Similarly to the sovereign stress factors, various 
shocks to real estate prices were considered for 
the scenarios: the median (50th percentile) estimate 
of the models described above is applied in the 
orderly scenario for the transition component and 
in the hot house scenario for the physical risk 
component; and the 99.5th percentile is applied 
for the disorderly scenario and the “too little, too 
late” scenario. Graph 14 shows the range of factors 
resulting from the model for all 108 countries where 
information was available. As with the sovereign 
bonds, for most countries in the scope of this 
report, the factors may again be more modest, eg 
the median for the “too little, too late” scenario is 
6.3% compared to 12.6% for the full sample.