Supplementary Guide to GPIF ESG Report 2020

Analysis of Climate Change-Related Risks andOpportunities in the GPIF Portfolio

For All Generations

Introduction: Challenges to Address and Key Points of This Report ｜ Foreword

Introduction: Challenges to Address and Key Points of This Report

Foreword
Climate change risk (particularly policy risk) affects all asset classes and securities simultaneously,
and cannot be completely eliminated through diversification. Throughout the world, the realization is
growing that physical and other climate risks are highly likely to materialize over the long-run. It is withthis understanding that GPIF published a series of climate-related financial disclosures in line with therecommendations of the TCFD for the first time in our ESG Report 2018. Here, in addition to measuring
our carbon footprint1 and carbon intensity2, we conducted a scenario analysis where we provided theresults of a transition pathway assessment, which is one way to analyze transition risk.
In our ESG Report 2019 published the following year, in addition to enhancing those disclosures,
we also compiled the “Analysis of Climate Change-related Risks and Opportunities in the GPIF
Portfolio,” in which we described analysis results in even greater detail and provided a number ofdifferent supplemental analyses. In the 2019 report, we used the Climate Value-at-Risk (CVaR)
methodology to comprehensively assess the impact of climate change on corporate value through not
only “policy risks,” but also “technology opportunities,” as evaluated by environmental technologyrelated patents, as well as “physical risks and opportunities.” TCFD recommendations encourage themeasurement of climate change risks and opportunities in terms of their financial impact, and in thissense, we feel the CVaR analysis is a dramatic step forward.
In this year’s ESG Report 2020, we expanded the scope of the greenhouse gas analysis toencompass the entire supply chain and newly included some alternative assets (domestic real estate)in the group of assets analyzed. We also added an assessment of the anticipated inter-industry
transfer of risks and opportunities inherent in the transition to a low-carbon society.
In particular, including “downstream Scope 3” emissions (i.e. indirect emissions generated by the
consumption and usage of goods and services sold) in the analysis resulted in a somewhat shockingly
large gap with the results obtained last year. On the other hand, these results may actually make more
sense as outcomes will naturally vary widely based on how much a given company bears the cost of(i.e. has responsibility for) transition risk, and to what extent they can pass these costs on to
manufacturers and sellers.
As we could not adequately describe these extremely complicated and subtle points in the ESG
Report 2020, we are once again publishing a supplemental guide and introducing them here.

1
A measurement of CO2 and other greenhouse gas (GHG) emissions generated by corporate activity. Generally refers to GHG
emitted by investee companies in this report.
2
In this report, generally refers to carbon footprint divided by corporate earnings, GDP or real estate floor area. Measured in GHG
emissions per unit.

Copyright © 2021 Government Pension Investment Fund All rights reserved.

Introduction: Challenges to Address and Key Points of This Report ｜ Foreword

While the analyses in this report focus mainly on how climate change directly impacts our portfolio,
since GPIF is a universal owner that invests not only in domestic listed companies but also in major
companies across the globe, the report provides valuable insight into the challenges and risks all
Japanese companies, all foreign companies, and by extension, countries all around the world facewith respect to climate change. Conversely, the report also examines how valuable the technologies
required to solve these challenges are, and the potential business opportunities that arise as a result.
We therefore believe this report can act as a useful reference not only for investors but also for otherstakeholders as well. Accurately assessing how the climate will change and what the inherent risks
and opportunities will be several decades into the future in a practical sense is an incredibly difficult
task, and the analysis results need to be interpreted as occurring within a wide spectrum. We hope,
however, that the report serves as an importance resource for investors and issuers alike as they think
about their own exposure to climate risks and opportunities.

Copyright © 2021 Government Pension Investment Fund All rights reserved.

Introduction: Challenges to Address and Key Points of This Report ｜ Composition and Analysis Highlights

Composition and Analysis Highlights
This paper is divided into an introduction and the main body. The main body consists of four chapters.
In "Chapter 1: Carbon Footprint," we measure the carbon footprint (greenhouse gas emissions[GHG]) and carbon intensity (GHG emissions per unit of revenue) of the Government Pension
Investment Fund (GPIF) portfolio using S&P Trucost data. This year, our analysis has been expanded
to include the entire supply chain. This broader view confirmed that the carbon footprint of portfolios
with a high weighting of companies in the Industrials, Energy, and Consumer Discretionary sectors
varies significantly depending on whether the analysis includes Scope 3 emissions (Figure 0-1). It is
possible that companies within these sectors can be significantly more competitive by reducing their
GHG emissions across the entire supply chain. Compared with the previous year, the total amount of
Scope1, Scope 2 and Scope 3 carbon footprint of the GPIF portfolio decreased in fiscal 2020, while
the carbon intensity increased.
Further, this report includes new analyses that were not included in the ESG Report 2020, such asa review of greenhouse gas emissions (GHG) disclosure and analysis of corporate GHG emission
reduction targets. Although domestic equities (domestic companies) lagged in disclosing greenhousegas emissions data compared to foreign equities (foreign companies), this gap has been quickly
shrinking in recent years. On the other hand, in terms of GHG emissions reduction targets, while ahigher percentage of domestic companies set targets compared to foreign companies, our analysis
showed that many companies currently failed to keep up the pace of emissions reduction with their
ongoing targets (Figure 0-2).
Figure 0-1 Carbon Footprint by Scope

Figure 0-2 Percentage of Companies Setting GHG
Emissions Reduction Targets and Feasibility(CO2 equivalent 10,000 tons)
Industrials(84)100Consumer
Discretionary(77)90Materials(56)80Energy(81)70Information
Technology(65)Consumer
Staples(28)

(%)

64.8
52.3

60

Utilities(40)Scope 150

Scope 240

Scope 3 Upstream

Financials(63)Scope 3 Downstream

Health Care(21)0Communication
Services(35)

0

5,000

10,00015,00020,000

33.9

25.6

29.9

MSCI Japan Index

MSCI Kokusai Index

20
10Real Estate(63)

26.7

30

Not on track with any ongoing targets
On track with at least one ongoing target

Note: Numbers in brackets are ratio of Scope 3 Downstream emissions to
the total emissions.
Source: S&P Trucost Limited©Trucost2021

On track with all ongoing targets
Ratio of the companies that set reduction target
Source: Reproduced by permission of MSCI ESG Research LLC©2021

Copyright © 2021 Government Pension Investment Fund All rights reserved.

3

Introduction: Challenges to Address and Key Points of This Report ｜ Composition and Analysis Highlights"Chapter 2: Scenario Analysis of Risks and Opportunities," also conducted the previous fiscal year,
analyzes how climate change related risks and opportunities could financially impact GPIF's portfolio(impacts on asset value), using MSCI's Climate Value-at-Risk (CVaR) model. The model enhancement,
including the expansion of analytical coverage to Scope 3, drove down aggregated CVaR dramatically.
However, at the portfolio level, aggregate CVaR improved year-over-year when comparing the 2019and 2020 portfolios based on the new model.
Likewise, similar to last year’s results, domestic equities showed a higher (positive) CVaR value inthe 1.5℃ temperature rise scenario compared to the 2℃ scenario, and the 2℃ scenario CVaR was
higher than the 3℃ scenario. This is due to the fact that heightened climate change regulations could
increase the value of domestic companies’ low carbon technology patents. No such trend has been
identified for other asset classes. (Figure 0-3).
Figure 0-3 Comparisons of CVaR by Temperature Rise Scenario
40

Scope 1+2
Technological Opportunities
Aggregated CVaR

（%）

30
20
10

0.6

0
-10

-4.2
-8.5

-20

Scope 3
Physical Risks

-11.4

-7.5

-3.7
-11.6

-5.3

-1.7

-7.2

-4.1

-0.7

-30
-40
1.5℃
2℃
3℃
1.5℃
2℃
3℃
1.5℃
2℃
3℃
1.5℃
2℃
3℃
Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario
Domestic Equities

Foreign Equities

Domestic Bond

Foreign Bond

Note1: Physical risks are analyzed under assumptions corresponding to a 4°C–6°C scenario.
Note2: "Scope 1+2" and "Scope 3" indicate policy risks associated with these scopes.
Source: Reproduced by permission of MSCI ESG Research LLC©2021

This year, amongst alternative assets, we conducted a CVaR analysis covering domestic real estate
assets in which we invest through private placement funds. Domestic real estate assets were exposed
to typhoons and flooding risks, but the impact on asset prices were limited for GPIF’s portfolio as awhole. (Figure 0-4). However, significant emissions reductions are required to achieve a 1.5 ℃
scenario.
In “Chapter 3: Analysis of Inter-Industry Transfer of Transition Risks and Opportunities,” weinvestigate how risks and opportunities will potentially shift between industries amidst the transition toa low-carbon society. While the CVaR analysis by MSCI in Chapter 2 assumes that these risks andopportunities will be redistributed amongst companies in the same sector (industry), the analysis

Copyright © 2021 Government Pension Investment Fund All rights reserved.

4

Introduction: Challenges to Address and Key Points of This Report ｜ Composition and Analysis Highlights

performed in this chapter by Astamuse assumes that low-carbon technologies will contribute to lower
CO2 emissions across sectors through supply chains, leading to a shift in profit and demand between
sectors. Results show that the opportunities far outweigh the risks for the energy, social infrastructure
and chemicals industries in the transition to a low carbon society. The analysis also found thatJapanese companies in these industries have many promising low-carbon technologies.
Figure 0-4 Real Estate CVaR

Figure 0-5 Inter-Industry Transfer of Risks andOpportunities in 2050

80

(%)

Ratio to total asset
68

70
60

Physical Risk

50

Regulatory Risk
41

40
30

24 23

22

20

14

10
0

0 0

4

4

0

0
No Risk

Very Low

Low

MediumHigh

Very High

Source: Reproduced by permission of MSCI ESG
Research LLC©2021

In “Chapter 4: Other Analysis,” we analyze the revenue opportunities and risks associated with
Sustainable Development Goals (SDGs). The SDG Additionality Analysis examines which products
and services contribute to the achievement of the SDGs when provided in specific countries andregions and aggregates the results for each company according to its revenue composition. Apart fromclimate change-related targets, the countries furthest from achieving the SDGs are emerging
economies, such as China and India, and developing countries in Africa. The results seem to reflectthat domestic companies have contributed less to these regions than overseas companies

Copyright © 2021 Government Pension Investment Fund All rights reserved.

5

Table of Contents

Analysis of Climate Change-Related Risks and Opportunities in the GPIF Portfolio
Table of Contents
Introduction: Challenges to Address and Key Points of This Report ....................................................... 1
Chapter 1: Analysis of Portfolio Greenhouse Gas Emissions
Features of GPIF’s Portfolio .......................................................................................................................... 7
Scope of Equities and Corporate Bonds Analyses ...................................................................................... 10
Carbon Footprint (GHG Emissions) Analysis ............................................................................................... 12
Carbon Intensity Analysis ............................................................................................................................ 14
Performance and Attribution Analysis of Changes in Carbon Footprint ....................................................... 16
Corporate Disclosure of GHG Emissions..................................................................................................... 20
Analysis of Corporate GHG Emissions Reduction Targets .......................................................................... 22
Features of GPIF’s Government Bond Portfolio .......................................................................................... 25
Carbon Intensity of the Government Bond Portfolio .................................................................................... 26
Exposure to Fossil Fuel Activities ................................................................................................................ 27(Appendix) Coverage and Scope of Equities and Corporate Bonds Analysis .............................................. 29(Appendix) About Scope 3 Data Calculation ................................................................................................ 30
Chapter 2: Scenario Analysis on Risks and Opportunities
Enhancement of Climate Value-at-Risk (CVaR) Analytical Methodology ..................................................... 33
CVaR by Temperature Increase Scenario .................................................................................................... 35
Technological Opportunities......................................................................................................................... 37
Policy Risks ................................................................................................................................................. 39
Physical Risks ............................................................................................................................................. 42
Climate Value-at-Risk Analysis of Government Bond Portfolio .................................................................... 45
Analysis of Portfolio Global Warming Potential ............................................................................................ 49
Analysis of Real Estate Portfolio Using Climate Value-at-Risk .................................................................... 53(Appendix) CVaR: Methodology Descriptions .............................................................................................. 58
Chapter 3: Analysis of Inter-Industry Transfer of Transition Risks and Opportunities ........................... 66
Chapter 4: Other Analysis
Energy Mix ................................................................................................................................................... 82
EU Taxonomy Analysis ................................................................................................................................ 83
Analysis of SDGs-Related Revenue Opportunities and Risks ..................................................................... 87

Copyright © 2021 Government Pension Investment Fund All rights reserved.

6

Chapter 1: Analysis of Portfolio Greenhouse Gas Emissions ｜ Features of GPIF’s Portfolio

Chapter 1: Analysis of Portfolio Greenhouse Gas Emissions
Features of GPIF’s Portfolio
Breakdown of GPIF Portfolio by Asset, Sector and GHGs
The analysis looked mainly at four asset classes in GPIF’s portfolio: domestic bonds, foreign bonds,
domestic equities and foreign equities. Some alternative assets3 (domestic real estate in which GPIF
invests through private funds, were also analyzed. In the sections that follow, we analyze GHG
emission volumes (carbon footprint), transition risks4, physical risks5, and opportunities relating tothese asset classes using data as of March 31, 2021. Because analysis results are heavily influenced
by the investment amount and sector weighting of each asset class, it is important to understand thecharacteristics of our portfolio prior to interpreting these results. The GPIF portfolio is composed ofroughly half bonds and half equities by overall market value (Figure 1-1). As of March 31, 2021, on the
fixed income side, domestic bonds accounted for 25.92% of all holdings while foreign bonds accounted
for 24.61%. For equities, domestic issues comprise 24.58% of the total portfolio and overseas issues
24.89%. The majority of bond holdings, both domestic and foreign, consist of government bonds(Figure 1-2).
When examining GPIF’s equity portfolio by sector, there is a difference in the composition of thedomestic and foreign equity portfolios (Figure 1-3). The domestic equity portfolio has a higher
proportion invested in the high-emitting Industrials and Consumer Discretionary, while the foreign
equity portfolio has a high proportion in the low-emitting Information Technology (IT), Financials, andHealthcare.6
In the corporate bond portfolio, the largest sector for both domestic and foreign bonds is Financials(Figure 1-4). Among domestic corporate bonds, the proportion of Utilities and Industrials is greaterthan that for foreign corporate bonds. Since Utilities includes electric power companies, this sector ischaracterized by higher GHG emissions than other sectors. In the foreign corporate bond portfolio, theproportion of energy companies, which have relatively high GHG emission volumes, is greater thanthat for domestic corporate bonds. On the other hand, the proportion of corporate bonds issued bytelecommunication services and healthcare companies, which have lower emissions, is also high.
When we compare the Scope 1+2+3 GHG emissions per million yen of revenue (i.e., carbon

3
Alternative assets account for around 0.7% of the pension reserve fund. Alternative assets are generally allocated to the four main
portfolio asset types according to their characteristics.
4
Transition risks are risks that arise from policy, technological innovation, demand change, etc. that accompany the transition to a
low-carbon economy.
5
Physical risks are risks from direct damage to an asset, supply chain disruption, etc. resulting from climate change.
6
Please refer to Figure 1-7 on P.11 for GHG emission.features by sector.

Copyright © 2021 Government Pension Investment Fund All rights reserved.

7

Chapter 1: Analysis of Portfolio Greenhouse Gas Emissions ｜ Features of GPIF’s Portfolio

intensity) of domestic and foreign portfolios for each sector, we find a lower carbon intensity inJapanese companies, suggesting that Japanese companies are more carbon efficient than theirforeign counterparts (Figure 1-5)
It is important to bear in mind this sector bias in GHG emissions when examining the results of thefollowing analysis. Around 90% of equity investments and 70% of bond investments by GPIF are
passive investments, which means our investment is virtually identical to the sector ratios of eachbenchmark.

Figure 1-1 Breakdown of Portfolio Asset Types

Figure 1-2 Breakdown by Category in GPIF Bond

(Total for GPIF’s Pension Reserves)

Portfolio

As of the end of March 2021

(%)
100%

Domestic Bonds

89.1% 86.2%

Foreign Bonds

80%

Foreign
Equities
24.89%

Domestic
Bonds
25.92%

As of the end of March 2021

60%
40%
20%

6.1%

7.9%

4.8%

5.9%

0%

Domestic
Equities
24.58%

Source: GPIF

ForeignBonds
24.61%

Government
bonds,
Governmentrelated bonds

Corporate
bonds

Other

Note: "Other" includes securitized products.
Source: GPIF

Copyright © 2021 Government Pension Investment Fund All rights reserved.

8

Chapter 1: Analysis of Portfolio Greenhouse Gas Emissions ｜ Features of GPIF’s Portfolio

Figure1-3 Breakdown of GPIF Equity Portfolio by

Figure1-4 Breakdown of GPIF Bond Portfolio by

Sector Based on Total Market Value (%)

Sector Based on Total Market Value (%)

25%

(%)

Domestic Equities

50%

Foreign Equities

20%

Domestic Bonds
Foreign Bonds

40%

As of the end of March 2021

15%

(%)

As of the end of March 2021

30%

EnergyInformation
Technology

Materials

Health Care

Consumer Staples

Real EstateCommunication
Services
Consumer
Discretionary

Utilities

Industrials

Financials

EnergyUtilities

Real Estate

Materials

Communication Services

Consumer Staples

Health Care0%

Financials

0%
Information Technology

10%Consumer Discretionary

20%

5%
Industrials

10%

Note: Among Domestic and Foreign Bonds, only corporate bonds areanalysed.
Source: GPIF, S&P Trucost Limited©Trucost 2021

Source: GPIF, S&P Trucost Limited©Trucost 2021

Figure 1-5 Carbon Intensity by Sector
Greenhouse Gas Emissions per million yen of sales(CO2 equivalent tons/ million yen)Domestic Equities

Foreign Equities

Domestic Bonds

ScopesScopesScopesScopesScopesScopesForeign Bonds
ScopesScopes

1+2+3
1+2
1+2+3
1+2
1+2+3
1+2
1+2+3
1+2
Communication Services
1.22
0.22
1.09
0.26
1.30
0.35
1.02
0.28
10.25
0.38
7.57
0.53
9.27
0.34
9.97
0.55
Consumer Discretionary
Consumer Staples
4.77
0.59
6.27
0.57
9.57
0.46
10.07
0.69
25.02
2.41
35.54
3.83
23.31
2.32
34.62
3.51
EnergyFinancials
0.85
0.04
1.28
0.19
1.00
0.05
1.22
0.05
Health Care
1.13
0.27
1.17
0.14
1.13
0.22
0.88
0.21
Industrials
15.91
0.79
18.98
1.10
9.91
1.23
9.96
1.91
5.59
0.49
3.08
0.43
4.32
0.57
3.08
0.27
Information Technology
Materials
20.20
5.71
27.93
8.46
25.09
9.05
32.15
7.75
Real Estate
3.25
0.33
5.34
0.84
2.77
0.53
3.98
0.58
Utilities
23.50
10.52
29.46
17.14
25.01
15.26
31.75
23.08
Note: Top 3 carbon intensive sectors are highlighted in gray. Among Domestic and Foreign Bonds, only corporate
bonds are analysed. Data is as of the end of March 2021.
Source: S&P Trucost Limited©Trucost 2021

Copyright © 2021 Government Pension Investment Fund All rights reserved.

9

Chapter 1: Analysis of Portfolio Greenhouse Gas Emissions ｜ Scope of Equities and Corporate Bonds Analyses

Scope of Equities and Corporate Bonds Analyses
Expansion of analysis scope to Scope 3
The scope of GHGs analyzed in this chapter has been expanded from last year and now includes
indirect emissions from the consumption and use of products and services (Scope 3 downstream) in
addition to direct GHG emissions by companies (Scope 1), indirect emissions from purchased
electricity (Scope 2) and indirect emissions from procured products and services other than purchased
electricity (Scope 3 upstream) (Figure 1-6). By expanding the scope of our analysis to include Scope
3 downstream, we aimed to account for GHG emissions across the entire supply chain.7
Because the priority was obtaining a more complete understanding of GHG emissions throughout
the entire supply chain, the analysis was conducted based on the sum total of Scope 1, 2, and 3
emissions, though it should be stated that including Scope 3 emissions in the analysis of the portfolio's
carbon footprint raises the possibility of duplicate GHG emissions (e.g., Scope 1 emissions of one
company are included in Scope 3 emissions of another company).

Variations in GHG emissions by sector
By expanding the calculation scope to include indirect emissions from the consumption and use ofsold products and services (Scope 3 downstream), the emissions features by sectors are different
from the last year’s analysis. Looking at GPIF’s equity portfolio emissions by sector and scope, Scope
3 downstream accounts for 50% or more of total emissions for 7 of the 11 sectors. This means thatanalysis result interpretations vary greatly depending on whether Scope 3 downstream emissions are
considered (Figure 1-7). The same trend can be seen in the bond portfolio. Both the equity and bondportfolios have a high ratio of Scope 3 downstream emissions in the Industrials, Energy, and Consumer
Discretionary sectors. In the Industrials sector, which includes industrial and construction machinery,
and the Consumer Discretionary Sector, which includes automobiles and home appliances, the GHGs
emitted when products and services are consumed are greater than those emitted in the
manufacturing process. This trend is even more evident in the Energy sector: Scope 1 and 2 emissions
for oil, coal and gas, such as drilling and refining, are relatively small, whereas GHG emissions fromthe consumption of these products and services account for more than 80% of the total emissions. For
portfolios with a higher weight of Industrials, Energy, and Consumer Discretionary sectors in particular,
the results of the analysis change dramatically depending on whether Scope 3 is included in thecalculation.
7

Please refer to P.30 for details on Scope 3 data calculation.

Copyright © 2021 Government Pension Investment Fund All rights reserved.

10Chapter 1: Analysis of Portfolio Greenhouse Gas Emissions ｜ Scope of Equities and Corporate Bonds Analyses

Figure 1-6 Greenhouse Gas Emissions by Scope

Figure 1-7 CO2 Emissions by Sector in Equity and Bond Portfolios＜ CO2 Emissions by Sector in Equity Portfolio＞(CO2 equivalent 10,000 tons)

Industrials(84)Consumer Discretionary(77)Materials(56)Energy(81)Information Technology(65)Consumer Staples(28)Utilities(40)Financials(63)Health Care(21)Real Estate(63)Communication Services(35)
0

2,000

4,000

6,000

8,000

10,00012,000＜CO2 Emissions by Sector in Bond Portfolio＞

14,00016,000(CO2 equivalent 10,000 tons)

Utilities(28)Energy(83)Materials(60)Industrials(66)Consumer Discretionary(75)Consumer Staples(37)Financials(73)Information Technology(63)Communication Services(33)Real Estate(59)Health Care(9)0Scope 1

100

200
Scope 2300

400

Scope 3 Upstream

500

600

700

800

Scope 3 Downstream

Note: Numbers in brackets are ratio of Scope 3 Downstream emissions to the total emissions
Source: S&P Trucost Limited©Trucost 2021

Copyright © 2021 Government Pension Investment Fund All rights reserved.

11

Chapter 1: Analysis of Portfolio Greenhouse Gas Emissions ｜ Carbon Footprint (GHG Emissions) Analysis

Carbon Footprint (GHG Emissions) Analysis
Carbon Footprint (GHG Emissions)This analysis measures the carbon footprint8 of GPIF’s equity and corporate bond portfolios for
Scopes 1 through 3, based on the characteristics of Scope 3 downstream emissions. Looking at total
emissions by asset class, domestic equities were found to have the highest level of emissions,followed by foreign equities, foreign corporate bonds, and domestic corporate bonds (Figure 1-8). This
result is roughly the same as last year’s, but does not necessarily mean that domestic companies havemore or less carbon emissions than foreign companies. Rather, it reflects the relative size and sector
holding of each asset class within GPIF’s portfolio.
The breakdown of the portfolio’s carbon footprint shows that the combined emissions of Scopes 3
Upstream and Downstream for assets excluding domestic bonds account for about 80% of the total
emissions, and about 65% for domestic bonds. As such, calculating emissions across the entire supply
chain and enhancing the transparency of these emissions and the potential for reducing them is crucial
for companies to take efficient emission reduction measures.
Figure 1-9 shows long-term greenhouse gas emission trends for Scopes 1, 2, and 3, using 100 for
fiscal 2017 emissions as a base. The results indicated for Domestic Equities, Foreign Equities andDomestic Bonds, fiscal 2020 saw large reduction of emissions in the four years since fiscal 2017. Thismay be attributable to the impact of changes in the companies held in GPIF’s portfolio and invested
amounts, as well as the methodology change in calculating apportioned carbon emissions 9 and
COVID-19 etc. Emissions related to foreign bonds increased significantly between fiscal 2018 and2019. This is likely due to the decrease in the weight of domestic corporate bonds in the portfolio andcorresponding increase in the weight of foreign corporate bonds in fiscal 2019. In fiscal 2020,
emissions related to foreign corporate bonds also fell greatly.
In addition to analyzing the Scope 1, 2 and 3 emissions, we also calculated the data for Scope 1
and 2 only, and confirmed the differences in the trends of carbon footprints (Figure 1-10). The carbon
footprint of domestic equities and domestic bonds decreased more in Scope 1 and 2 than in Scope 1,
2 and 3 combined compared with fiscal 2017.

8
The carbon footprint is apportioned based on the percentage of the equity and bond holdings. The apportion is calculated using
the Enterprise Value Including Cash (EVIC) as the denominator at the time of analysis. That is, if an investor owns 1% of acompany's equity or bonds, then they also “own” 1% of the company's GHG emissions. We also use Trucost's Environmentally
Extended Input-Output (EEIO) model to reduce the double-counting of emissions.
9
Change in methodology is based on the latest guidance from the Partnership for Carbon Accounting Financials (PCAF). In
contrast to the previous years when apportioned carbon footprint was calculated using the Enterprise Value (EV) as denominator,
this year Enterprise Value including Cash EVIC) is applied.

Copyright © 2021 Government Pension Investment Fund All rights reserved.

12

Chapter 1: Analysis of Portfolio Greenhouse Gas Emissions ｜ Carbon Footprint (GHG Emissions) Analysis

Figure 1-8 Carbon Footprint by Scope
35(10 million tCO2e)
Scope 3 Downstream

30
Scope 3 Upstream

25
20

Scope 215
Scope 1105Foreign Bonds (Corporate)

Domestic Bonds (Corporate)

Domestic Equities

Reference: MSCI ACWI
(exJapan, exChina A-shares)

GPIF Portfolio

Reference: TOPIX

GPIF Portfolio

0Foreign Equities

Bonds

Source: S&P Trucost Limited©Trucost2021

Figure 1-9 Greenhouse Gas Emission Trends (Scope

Figure 1-10 Greenhouse Gas Emission Trends

1+2+3)(Scope 1+2)

180

180

160

(FY2017=100)

160

140

140

120

120

100

100

80

80

60

60

40

(FY2017=100)

40
2017

2018

2019

Domestic Equities

TOPIX

Foreign Equities
Domestic Bonds(Corporate)
Source: S&P Trucost Limited©Trucost2021

2020

2017

2018

2019

(FY)

2020
(FY)

Domestic Equities

TOPIX

MSCI ACWI(exJapan, exChina A)

Foreign Equities

MSCI ACWI(exJapan, exChina A)

Foreign Bonds(Corporate)

Domestic Bonds(Corporate)

Foreign Bonds(Corporate)

Source: S&P Trucost Limited©Trucost2021

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13

Chapter 1: Analysis of Portfolio Greenhouse Gas Emissions ｜ Carbon Intensity Analysis

Carbon Intensity Analysis
Carbon intensity by asset
Carbon intensity can be calculated in a variety of ways; for this analysis we adopted the weighted
average carbon intensity (WACI) approach for equities and bonds, in line with the Task Force on
Climate-related Financial Disclosure (TCFD) recommendations. WACI is calculated by multiplying
each company’s carbon emissions to revenue (tCO2e/ million yen) by the weight of that company inthe portfolio, then taking the sum of those products to get the weighted average of carbon intensity.
Out of GPIF’s equity and corporate bond portfolios, the WACI was particularly high for domestic
equities and foreign bonds (Figure 1-11). For the former, Scope 3 downstream emissions accounted
for around 74% of WACI, largely due to relatively high allocations to Industrials, Consumer
Discretionary and Materials – all sectors with high indirect emissions (Figure 1-12). Foreign corporate
bonds, on the other hand, in addition to having higher allocations to several carbon intensive sectors
than domestic corporate bonds, also had a higher level of investment in the Financials sector, which
has a low carbon intensity.

Copyright © 2021 Government Pension Investment Fund All rights reserved.

14

Chapter 1: Analysis of Portfolio Greenhouse Gas Emissions ｜ Carbon Intensity Analysis

Figure 1-11 Weighted Average Carbon Intensity (WACI) for Equities
and Corporate Bonds
12

Scope 1
Scope 2
Scope 3 Upstream
Scope 3 Downstream

10(WACI, tCO2e)

8
6
4
2
0
Domestic Equities Foreign Equities Domestic bonds(corporate)

Foreign bonds(corporate)

Source: S&P Trucost Limited© Trucost 2021

Figure 1-12 Breakdown of WACI by Sector for Domestic and Foreign Equities
5

4.70(WACI, tCO2e)4

Domestic Equities

32

Foreign Equities
1.75

1.66

1.36
0.29

Energy

0.21
0.13

0.20
0.12

Financials

0.85
0.33

Health Care

0.61
0.37

Utilities

0.62

1

0.47
0.70

Consumer Staples

1.40
1.14

0.09
0.10
0.12
0.08

0

Real EstateCommunication
Services

Information
Technology

Materials

Consumer
Discretionary

Industrials

Source: S&P Trucost Limited©Trucost 2021

Copyright © 2021 Government Pension Investment Fund All rights reserved.

15

Chapter 1: Analysis of Portfolio Greenhouse Gas Emissions ｜ Performance and Attribution Analysis of Changes in Carbon Footprint

Performance and Attribution Analysis of Changes in
Carbon Footprint
Performance drivers of portfolio footprint changes
This section highlights potential drivers of change for both the carbon footprint and carbon intensity
in GPIF’s portfolios, covering Scope 1, 2 and 3. There are two main factors that drive changes in the
carbon footprint of a portfolio: changes in the quantity of GHG emitted by investees and changes in
the proportion of investees owned or financed by the investor.
The results of the carbon footprint performance analysis are shown in Figure 1-13. The analysis
breaks down the causes of the carbon footprint change between fiscal 2019 and fiscal 2020 into (1)changes in the quantity of GHG emissions of investees (absolute emissions) only; (2) changes in the
proportion of each investee owned or financed by the investor (ownership) only; and (3) the interactionof changes in both absolute emissions and ownership together. The total carbon footprint for the overall
portfolio decreased by 17.3% year on year, and the most significant cause of this is attributed toownership changes. GHG emissions of the companies that make up the portfolio are allocatedaccording to the percentage of shares or bonds held by the investor (ownership ratio). In other words,
an investor who owns 1% of a company's equity or bonds is considered to own 1% of the GHG
emissions of that company. Until last year, the calculation of percentage of the shares were based onEnterprise Value (EV). However, this year, the calculation method has been changed to use Enterprise
Value Including Cash (EVIC) as the denominator for listed companies10. Therefore, in contrast to theprevious years when EV was the denominator, applying EVIC as the denominator, the number
increases, the ownership ratio will naturally decrease. As a result, carbon footprint of the GPIF portfolio
may have decreased.
Finally, we analyzed the changes in carbon intensity across the equity and corporate bond portfolio
as a whole from 2019-2020 and what the primary drivers of those changes were (Figure 1-14). The
performance drivers for change were broken down into four categories for analysis: (1) corporate
profits; (2) companies’ emissions volumes; (3) weight of each company in the portfolio; and (4) otherfactors. The carbon intensity of GPIF’s equity and corporate bond portfolio increased by 7.9% in thespace of a year. The largest contribution was from the change in the weight of each company in theportfolio.The change in the methodology for calculating the percentage of holdings described above
will also affect the apportioning of corporate revenues used to calculate carbon intensity. Therefore,
the increase in carbon intensity may be due to factors such as the change from EV to EVIC and theshift to a new basic portfolio from fiscal 2020 that reduced the weight of domestic bonds, which tends

10

Change in methodology is based on the latest guidance from Partnership for Carbon Accounting Financials (PCAF).

Copyright © 2021 Government Pension Investment Fund All rights reserved.

16

Chapter 1: Analysis of Portfolio Greenhouse Gas Emissions ｜ Performance and Attribution Analysis of Changes in Carbon Footprint

to have a low carbon intensity, and increased the weight of foreign bonds, which tends to have a highcarbon intensity.

Figure1-13

BreakdownofCarbonFootprint

Performance Drivers for the Total Aggregate Portfolio

Figure

1-14

BreakdownofCarbonIntensity

Performance Drivers for the Total Aggregate Portfolio

Copyright © 2021 Government Pension Investment Fund All rights reserved.

17

Chapter 1: Analysis of Portfolio Greenhouse Gas Emissions ｜ Performance and Attribution Analysis of Changes in Carbon Footprint

Figure

1-15

BreakdownofCarbonFootprint

Performance for Equities

Figure1-17

Breakdown

Figure 1-16 Breakdown of Carbon Intensity Performance
Drivers for the Equities

ofPerformance for Corporate Bonds

CarbonFootprint

Figure 1-18 Breakdown of Carbon Intensity Performance
Drivers for Corporate Bonds

Copyright © 2021 Government Pension Investment Fund All rights reserved.

18

Chapter 1: Analysis of Portfolio Greenhouse Gas Emissions ｜ Performance and Attribution Analysis of Changes in Carbon Footprint

Difference in carbon intensity11 from benchmark
The factors that cause the carbon intensity to differ from the benchmark’s carbon intensity can be
broken down into two main areas: (1) sector allocation and (2) company selection. If sectors with highemissions are overweight in comparison to the benchmark, the overall carbon intensity of the portfolio
also has the possibility to be higher than the benchmark. However, selecting companies with thehighest levels of carbon efficiency (low carbon intensity) among the high emitting sectors may resultin a lower carbon intensity for the entire portfolio compared to the benchmark.
Figure 1-19 shows the effect of sector allocation (industry effect) and company selection on thebenchmark for each portfolio (individual company effect).
In fiscal 2020, the domestic equity portfolio has higher carbon intensity compared to its benchmark,while the foreign equity portfolio has lower carbon intensity. In the domestic equity portfolio, the effectof company selection in the high-emitting Industrials sector had the greatest impact. Meanwhile, forthe foreign equity portfolio, both sector allocation and company selection positively contributed to thedecrease in the carbon intensity.
Figure 1-19 Attribution Analysis of Domestic and Foreign Equities and their Respective Benchmarks
6%
5%
4%
3%
2%
1%
0%
-1%
-2%
-3%

(%)
Performance Attribution (Portfolio versus their respective benchmark)

2016

2017

2018
Domestic Equities

2019

2020
(FY)

2016

Sector Attribution
Company Selection

2017

2018
Foreign Equities

2019

2020
(FY)

Note: Sector allocation effects are determined using the 11 GICS Sector classifications, and the analysis uses the Carbonto-Revenue intensity metric. A positive value in the figure indicate a lower carbon intensity. In other words, the portfolio has ahigher carbon efficiency.
Source: S&P Trucost Limited©Trucost 2021

11

The scope used to calculate the carbon intensity is Direct Emissions+ First Tier Indirect Emissions. Trucost defines Direct
Emissions as the sum of Scope 1 emissions from the GHG Protocol and other emissions from a wide range of GHGs associatedwith a company's business activities. First Tier Indirect Emissions are defined as the sum of the GHG Protocol's Scope 2 emissions
and the emissions of the company's uppermost upstream supply chain (direct suppliers).

Copyright © 2021 Government Pension Investment Fund All rights reserved.

19

Chapter 1: Analysis of Portfolio Greenhouse Gas Emissions ｜ Corporate Disclosure of GHG Emissions

Corporate Disclosure of GHG Emissions
Disclosure rates based on the number of companies, the value of holdings, and theabsolute GHG emissions
The following analysis examines the status of corporate disclosures of Scope 1 GHG emissions foreach asset class held by the GPIF. For each asset class, the following ratios were reviewed: (1)disclosure ratio based on the number of companies (Figure 1-20); (2) disclosure ratio weighted by thevalue of the company’s holdings (Figure 1-21); and (3) disclosure ratio weighted by the company’s
GHG emissions (Figure 1-22).
In fiscal 2020, the percentage of companies disclosing information on GHG emissions in terms ofthe number of companies was: domestic bonds (51%), foreign equities (49%), foreign bonds (44%),and domestic equities (13%). When partial disclosures are included, the numbers change: domestic
bonds (76%), foreign equities (66%), foreign bonds (55%), and domestic equities (28%). The
disclosure ratio for domestic equities, including partial disclosure, remained considerably lower thanfor other assets.
In fiscal 2020, the disclosure ratio weighted by the percentage of GPIF’s value of holdings was:foreign equities (73%), domestic bonds (62%), foreign bonds (58%) and domestic equities (58%).
When partial disclosures are included, the number roughly doubles: foreign equities (84%), domestic
equities (83%), domestic bonds (82%), and foreign bonds (75%). The holdings weighted disclosure
ratios are much higher than the ratio for the disclosure rates as a percentage of companies, because
companies with larger market capitalizations are more likely to disclose information. The disclosure
ratio by value of holdings for domestic equities is comparable to that of other assets.
Analyzing the disclosure ratios weighted by corporate GHG emissions in fiscal 2020 resulted in thefollowing ratios: domestic bonds (93%), foreign equities (80%), domestic equities (72%) and foreign
bonds (62%). Once again, when including partial disclosure, the percentages increase: domestic
bonds (98%), foreign equities (98%), foreign bonds (93%), and domestic equities (87%). The
disclosure ratio calculated this way is generally higher than ratios using market capitalization, because
companies with higher GHG emissions are more likely to disclose information.

Copyright © 2021 Government Pension Investment Fund All rights reserved.

20

Chapter 1: Analysis of Portfolio Greenhouse Gas Emissions ｜ Corporate Disclosure of GHG Emissions

Figure 1-20 Disclosure Rates Based on Number of

Figure 1-21 Change in Value of Holdings-based

Companies

Disclosure Rates from FY2016 to FY2020
90%

Domestic
Equities（%）

85%

Foreign
Equities

80%75%

Domestic
Bonds

Domestic Equities

70%

Foreign Equities

Foreign
Bonds

Domestic Bonds

65%

0%

20%

40%

60%

80%

60%

(%）
Full Disclosure

Partial Disclosure

Foreign Bonds

100%
2016

Modelled

2017

2018

2019

2020
(FY）

Note: Includes "Partial Disclosure"
Source: S&P Trucost Limited©Trucost 2021

Note: Data is as of the end of March 2021.
Source: S&P Trucost Limited©Trucost 2021

Figure 1-22 Disclosure Rates Based on Absolute
GHG Emissions
Domestic
Equities

Foreign
Equities

Domestic
Bonds

Foreign
Bonds
0%

20%
Full Disclosure

40%

60%

Partial Disclosure

80%
Modelled

100%

(%）

Note: Data is as of the end of March 2021.
Source: S&P Trucost Limited©Trucost 2021

Copyright © 2021 Government Pension Investment Fund All rights reserved.

21

Chapter 1: Analysis of Portfolio Greenhouse Gas Emissions ｜ Analysis of Corporate GHG Emissions Reduction Targets

Analysis of Corporate GHG Emissions Reduction Targets
Setting of Corporate Greenhouse Gas Reduction Targets
This section examines corporate GHG emissions reduction target-setting and the progresscompanies have made in achieving the targets. Figure 1-23 shows that the number of constituents in
the MSCI ACWI index that set GHG emissions reduction targets increased from the year 2015 onward.
As of the end of 2020, 34.8% of the 2,982 constituents in the MSCI ACWI index set some type ofemissions reduction target. Further, an increasing number of companies set long-term targets to bring
their GHG emissions to net-zero (net-zero target) over the long term, which amounted to 14.8% of
newly set targets in 2020.
Figure 1-23

Number of Companies that Set Emissions Reduction Targets and Ratio of Net-Zero Targets to

Reduction Targets Among the MSCI ACWI Index Constituents
1,200(number of companies)

(%)

90

Decarbonization targets

1,000

1,038

Ratio of net-zero targets (right axis)

800
791
600

850

80
70

904

60
50

685

40

544

400

100

30
14.8

200
2.0

2.2

3.6

7.8

20
10

1.7

0

0
2015
2016
2017
2018
2019
Note: Ratio of net-zero targets is counted based on the newly set decarbonization targets for each year
Source: Reproduced by permission of MSCI ESG Research LLC©2021

2020(year)

Analysis of GHG Emissions Reduction Targets for Domestic Equities
Looking at domestic companies in the MSCI Japan index, 64.7% set some type of emissions
reduction target as of the end of March 2021 (Figure 1-24, on the right-hand side). The ratio ofJapanese companies setting targets was higher than that of foreign companies in the MSCI Kokusai
index 12 (52.3%, Figure 1-26, right-hand side). Some companies set targets to reduce Scope 1
emissions only, while others set emissions reduction targets that cover Scope 2 and Scope 3. Targetsetting also differed by sector. Using the Global Industry Classification Standard (GICS®) sector
classifications, the ratio of Japanese companies setting targets was higher in the energy, real estateand consumer staples sectors than the communication services and utilities sectors (Figure 1-24).
MSCI also assessed the progress companies in the MSCI Japan index made in achieving their
12

A representative equity index that indicates equity price trends in developed countries excluding Japan.

Copyright © 2021 Government Pension Investment Fund All rights reserved.

22

Chapter 1: Analysis of Portfolio Greenhouse Gas Emissions ｜ Analysis of Corporate GHG Emissions Reduction Targets

emissions reduction targets based on the track record of their emissions performance (Figure 1-25).
Such assessments showed that 25.6% of companies made progress in lowering emissions on trackwith meeting all their targets and 26.7% were on track with at least one of their targets. On the other
hand, 47.7% of companies were not on track to meet any targets and may be challenged to achieve
them going forward. While many companies actively set emissions reduction targets, actuallyachieving them will likely require many to make further efforts to lower emissions.
Figure 1-24

Carbon Emissions by Sector and Targets Among MSCI Japan Constituents
Percentage of constituents with targets

Sector average of carbon emissions per Scope
33.3

46.4

Utilities n=9

30.4

67.0

Materials n=23

80.6

Real Estate n=18

11.0
43.5

27.8

Energy n=3

86.3

Industrials n=70

87.1

17.1

Consumer Staples n=32

88.2

28.1

33.3
66.7

90.1

12.5

90.8

6.3

Information Technology n=35

91.1

5.7

28.6

Consumer Discretionary n=44

94.8

11.4

18.2

97.3

14.8

86.8
0

Scope120

40

Scope2

80

100

29.2

6.3
37.1
22.7
40.7

7.4

28.9

0

(%)

Scope 3

28.1

25.0
18.8

16.9

60

14.3

21.9

Communication Services n=16

Financials n=27

33.3

32.9

Health Care n=24

MSCI Japan Index n=301

22.2

20
Scope1

18.9
40

60

Scope 1+2

80

Scope1+2+3

100

No Target(%)

Note: Since emissions are not consistently reported by the issuers, we used either reported or estimated baseline and present emissions
for this analysis
Source: Reproduced by permission of MSCI ESG Research LLC©2021

Figure 1-25

Feasibility of Reduction Targets by Sector Among MSCI Japan Constituents

MSCI Japan Index(195)

26.7

25.6

Financials(17)

47.7
17.6

58.8

Consumer Discretionary(23)Information Technology(25)

43.5
48.0

24.0

Communication Services(5)

28.0
80.0

20.0

Health Care(16)

18.8

37.5

Consumer Staples(25)

43.8

20.0

4.0

Industrials(45)

23.5

39.1

17.4

76.0
31.1

28.9

Energy(3)

40.0
100.0

Real Estate(15)

53.3

20.0

26.7

Materials(17)

70.6

17.6

11.8

Utilities(4)

25.0

75.0
0

10

20

30

40

On track with all ongoing targets
Not on track with any ongoing targets

50

60

70

80

90

On track with at least one ongoing target

100

(%)

Note: Numbers in ( ) after sector name means number of issuers with targets
Source: Reproduced by permission of MSCI ESG Research LLC©2021

Copyright © 2021 Government Pension Investment Fund All rights reserved.

23

Chapter 1: Analysis of Portfolio Greenhouse Gas Emissions ｜ Analysis of Corporate GHG Emissions Reduction Targets

Analysis of GHG Reduction Targets for Foreign Equities
Among the constituents of the MSCI Kokusai index, as of the end of March 2021, 52.3% have set
some type of emissions reduction target (Figure 1-26, on the right-hand side). The ratio of foreigncompanies setting targets was higher in sectors such as utilities, consumer staples, material and realestate, while sectors including information technology and healthcare had relatively low ratios.
According to MSCI’s evaluation, 29.9% of companies that have set targets were expected to achieve
all of them, while 33.9% were expected to achieve at least one. On the other hand, 36.2% (Figure 127) of companies were unlikely to achieve any target. Although the ratio of companies setting reduction
targets was lower than that of domestic equities, the ratio of companies that were expected to achieve
their targets was higher than that of domestic equities.
Figure 1-26

Progress in Establishing Sector-Specific Carbon Emissions and Reductions Targets Among

MSCI Kokusai constituents
Percentage of constituents with targets

Sector average of carbon emissions per Scope
47.5

Utilities n=77

44.2
19.4

Real Estate n=81

77.1

13.6

27.2

Industrials n=184

80.4

17.4

22.8

Energy n=48

85.4

29.2

Communication Services n=86

87.2

11.6

90.0

8.1 14.0
5.3

18.6
51.2

19.1

26.7
8.2

19.4

Health Care n=134

93.7

8.2

Information Technology n=147

93.7

6.1 10.9

Financials n=202

97.6

10.9

20.3

13.8

19.6

20
Scope140

60

Scope280

Scope 3

0

100

16.3
11.4

20

(%)

14.6

12.5

90.3

0

22.2
17.4

19.8

Consumer Staples n=86

83.0

14.3

29.6

Consumer Discretionary n=131

MSCI Kokusai Index n=1,274

20.8

18.2

73.4

Materials n=98

Scope1

18.8
40

Scope 1+2

60

80

Scope1+2+3

100

No Target(%)

Note: Since emissions are not consistently reported by the issuers, we used either reported or estimated baseline and present emissions for this analysis
Source: Reproduced by permission of MSCI ESG Research LLC©2021

Figure 1-27

Feasibility of Sector-Specific Reductions Targets for MSCI Kokusai Constituents

MSCI Kokusai Index(666)Financials(86)Consumer Discretionary(49)Information Technology(48)Communication Services(67)Health Care(63)Consumer Staples(43)Industrials(27)Energy(106)Real Estate(51)Materials(62)Utilities(64)

29.9

33.9

44.2

32.7
33.3
28.4

20.4
18.8

46.9
47.9
49.3

15.9

42.9
37.2

34.9
44.4

25.9

30.2

46.2
41.2
30.6

35.3
40.3

39.1
10

22.4

41.3

27.9
29.6
23.6
23.5
29.0
0

36.2
30.2

25.6

42.2

20
30
40
On track with all ongoing targets

50

18.8

60
70
80
90
On track with at least one ongoing target

100

(%)

Note: Numbers in ( ) after sector name means number of issuers with targets
Source: Reproduced by permission of MSCI ESG Research LLC©2021

Copyright © 2021 Government Pension Investment Fund All rights reserved.

24

Chapter 1: Analysis of Portfolio Greenhouse Gas Emissions ｜ Features of GPIF’s Government Bond Portfolio

Features of GPIF’s Government Bond Portfolio
Analysis of GPIF Government Bond Portfolio
The carbon footprint and other analyses covered so far have examined the equities and corporate
bonds issued by companies in which GPIF invests. This section, meanwhile, analyzes sovereign
bonds issued by national governments. Considering how the many risks related to climate change willaffect government bond prices is an extremely complex problem. These risks, however, undeniably
have the potential to affect GPIF’s portfolio considering the fiscal burden and other impacts from theresponse to climate change-related transition and physical risks. There are basically two ways ofanalyzing climate change risk for government bonds: one is to consider only greenhouse gas
emissions produced by the government sector of the nation issuing the bond, while the other takes
into account the entire sphere of influence of the nation as a whole, including greenhouse gas
emissions generated by the activities of that country’s corporations and individuals. The analysis
conducted for this report adopts the latter approach.
In the analysis of government bonds, just as when analyzing equities and corporate bonds, it isimportant to understand that results are greatly influenced by factors such as which specific sovereign
bonds make up the portfolio. The overall GPIF portfolio of foreign and domestic government bonds(hereinafter, “GPIF’s overall government bond portfolio”) is made up of about half foreign and half
domestic government bonds (Figure 1-28).Based on data as of the end of March 2021, comparing thecountry weights of the top 20 countries (by amount invested in GPIF’s overall government bondportfolio) to a weighted average benchmark of foreign and Japanese government bonds, Japan, theU.K., Germany, and several other countries were underweighted. In contrast, Italy and the U.S., among
other countries, were overweighted (Figure 1-29). However, the difference from the benchmark is
relatively small in all cases.
Figure 1-28 Weight by Country in GPIF Government
Bond Portfolio
UK, 3.0%

Figure 1-29 Top 20 Exposure Countries’ Portfolio
Weights Compared to Benchmark (%pt)

Other, 9.4%

As of the end of March 2021

1.0%

0.5%

(%pt) ↑：overweight

0.5%↓：underweight

0.0%

Spain,3.3%-0.5%

Germany, 3.6%

-1.0%

Japan,
47.5%

Italy, 5.3%

-1.5%
-2.0%
-2.5%

-2.5%
Italy

USA

Spain

MexicoIndonesia

Malaysia

FranceBelgium

Singapore

Ireland

PolandAustria

Denmark

Finland

CanadaNetherlands

Australia

Germany

Source: GPIF, S&P Trucost Limited©Trucost2021

-3.0%

UK

USA, 22.7%

Japan

France, 5.4%

Source: GPIF, S&P Trucost Limited©Trucost2021

Copyright © 2021 Government Pension Investment Fund All rights reserved.

25

Chapter1: Analysis of Portfolio Greenhouse Gas Emissions ｜ Carbon Intensity of the Government Bond Portfolio

Carbon Intensity of the Government Bond Portfolio
Measuring Carbon Intensity
This section examines the carbon intensity 13 for government bond portfolios, calculated as theamount of GHG emissions divided by the Gross Domestic Product (GDP). While it is also possible tomeasure the carbon footprint by the absolute level of GHG emissions in an entire country, this measuredoes not factor in the size and population of each country, making it difficult to correctly understandthe actual implications with a simple comparison. Therefore, we conducted an analysis of carbon
intensity standardized by GDP.
In measuring the carbon footprint of government bonds, the scope of GHG emissions is defined as
domestic and import emissions related to intra-regional demand, plus export emissions associatedwith domestic production to meet overseas demand. To calculate the WACI, we use a weighted
average of the country's GHG emissions per million yen of GDP, depending on the percentage of theportfolio held. Below, we show the carbon intensity of (1) the GPIF's entire government bond portfolio;(2) the benchmark, which is a composite of the benchmark of Japanese government bonds and foreign
government bonds in proportion to the base portfolio; and (3) the top 20 countries in terms of theamount invested in the GPIF’s government bond portfolio.In this analysis, the WACI for GPIF’s overall
government bond portfolio was found to be slightly higher than the aggregated benchmark (Figure 131). This was partly because the portfolio is overweight in bonds issued by countries where GHG
emissions are relatively high, such as Indonesia, Malaysia, Poland, Mexico, Singapore and Belgium,
indicating that the carbon intensity value of each country and the ratio of each country's holdings
greatly affect the carbon intensity results of the portfolio.
Figure 1-30 Carbon Intensity of Sovereign Portfolio
4(tCO2e/million yen)Domestic

Export3

ImportFigure 1-31 Carbon Intensity by Country25(tCO2e/ million yen)

Overweight to benchmark
Indonesia20
15Austria
Underweight to benchmark

10
5

2

0
Ireland

UK

FranceDenmark

Italy

Finland

Japan

Spain

USA

Sovereign Portfolio

Austria

Germany

Australia

Netherlands

Belgium

CanadaSingapore

BenchmarkMexicoGPIF Sovereign Portfolio
Source: GPIF, S&P Trucost Limited©Trucost2021

Poland0

Malaysia

Indonesia

1

Source: GPIF, S&P Trucost Limited©Trucost2021

13

There are several approaches in calculating carbon intensity. The common approaches are (1) Weighted Average Carbon
Intensity (WACI), (2) Carbon to Revenue Intensity (C/R) and (3) GHG emissions divided by GDP.

Copyright © 2021 Government Pension Investment Fund All rights reserved.

26

Chapter 1: Analysis of Portfolio Greenhouse Gas Emissions ｜ Exposure to Fossil Fuel Activities

Exposure to Fossil Fuel Activities
Share of apportioned revenues derived from fossil fuel activities
In this section, Trucost data is used to assess the portfolio's exposure to fossil fuels. Figure 1-32
demonstrates the portfolio’s level of revenue dependency on fossil fuel-related activities by sector. As
reflected in the chart, domestic bonds have the highest exposure to companies engaging in fossil fuelrelated activities. This is due to the high exposure to the Utilities and Energy sectors within thedomestic bond portfolio, where the share of total revenue coming from fossil-fuel activities totaled
approximately 6.7% in fiscal 2020. Among the different types of fossil fuel activities investee
companies engaged in, the portfolio has the highest exposure to natural gas power generation at 4.1%,
followed by coal power generation at 1.9% and crude petroleum and natural gas extraction at 0.3%.
Although higher than that of other asset classes, the fossil fuel-related income as a percentage ofrevenue in the portfolio companies of the domestic bond portfolio decreased by about 0.6 percentage
points compared with the previous fiscal year.

Risk of stranded assets
Potential future GHG emissions from fossil fuel reserves will far exceed the amount of GHG
emissions allowed to achieve the international goal of limiting the increase of global warming to lessthan 2 degrees, as outlined in the Paris Agreement. Assets that may be subject to unexpected
impairments, diminished asset values, or liabilities resulting from this transition toward a low-carbon
society are called stranded assets. The risk of stranded assets in a portfolio company's fossil fuelrelated assets is analyzed from a different perspective by using a measure of the capital expenditures14that have been made for future fossil fuel exploration and extraction projects. This indicator is basedon the information disclosed by the investee.
Figure 1-33 shows the total amount of capital investment in fossil fuel-related businesses by fueltype. The largest fossil fuel-related capital investment was in the foreign equity portfolio. Capital
investment in the fossil fuel-related businesses in GPIF’s foreign equity portfolio has been on a
downward trend since fiscal 2018, with a noticeable decline in fiscal 2020 compared with fiscal 2019.
This may be because the foreign equity portfolio has a higher exposure to companies engaged in fossil
fuel-related businesses than other asset classes, and the fact that Japanese companies do notdisclose much information related to their reserves.

14

Capital expenditures are expenditures for the purchase or renovation/upgrade of the physical assets of companies involved incoal, oil, and gas exploration: properties, plants, and equipment. Depreciation of physical assets is not considered.

Copyright © 2021 Government Pension Investment Fund All rights reserved.

27

Chapter 1: Analysis of Portfolio Greenhouse Gas Emissions ｜ Exposure to Fossil Fuel Activities

Figure 1-32 Fossil Fuel Related Revenues as a Share of Total Apportioned Revenues
12%

(%)

10%
8%
6%
4%
2%
0%
2016 2017 2018 2019 2020 2016 2017 2018 2019 2020 2016 2017 2018 2019 2020 2016 2017 2018 2019 2020
Domestic Equities(FY)

Foreign Equities(FY)

Extractives Bituminous coal mining
Extractives Crude petroleum and natural gas extraction
Extractives Natural gas liquid extraction
Energy Coal Power Generation
Energy Natural Gas Power Generation

Domestic Bonds(corporates)

(FY)

(FY)

Foreign Bonds(corporates)

Extractives Tar sands extraction
Extractives Drilling oil and gas wells
Extractives Support activities for oil and gas operation
Energy Petroleum Power Generation

Source: S&P Trucost Limited© Trucost 2021

Figure 1-33 Apportioned Capital Expenditure on Fossil Fuel Related Activities
1,600(100 million yen)

1,400

Coal

Oil

Gas

Oil and/or Gas

1,200
1,000
800
600
400
200
0
2016 2017 2018 2019 2020 2016 2017 2018 2019 2020 2016 2017 2018 2019 2020 2016 2017 2018 2019 2020
Domestic Equities(FY)

Foreign Equities(FY)

Domestic Bonds(corporate)(FY)

Foreign Bonds(corporate)(FY)

Note: Total apportioned capital expenditure on fossil fuel related activites, broken down by reserve type.
Source: S&P Trucost Limited© Trucost 2021

Copyright © 2021 Government Pension Investment Fund All rights reserved.

28

Chapter 1: Analysis of Portfolio Greenhouse Gas Emissions ｜ (Appendix) Coverage and Scope of Equities and Corporate Bonds Analysis(Appendix) Coverage and Scope of Equities andCorporate Bonds Analysis
Coverage of Equities and Corporate Bonds
The analysis of the carbon footprint and carbon intensity of the GPIF portfolio is based on data fromS&P Trucost as of the end of March 2021. For equities, the analysis is based on issuer companies
included in the Trucost database and have adequate environmental and financial data for the mostrecent three years. The data coverage ratio was 99.8% for domestic equities and 98.7% for foreign
equities on a portfolio weight basis (Figure 1-34).
For bonds, the analysis was conducted for the issuer of the relevant bond (or the listed parent
company if the issuing company is unlisted) and the data coverage ratio was 95.7% for domestic
bonds and 85.8% for foreign bonds, based on market capitalization.

Figure 1-34 Coverage Rate for GPIF’s Portfolio Analysis
VOH
Domestic Equities

99.8%

Foreign Equities

98.7%

Domestic Bonds(corporate)

95.7%

Foreign bonds(corporate)

85.8%

Source: S&P Trucost Limited©Trucost 2021

Copyright © 2021 Government Pension Investment Fund All rights reserved.

29

Chapter 1: Analysis of Portfolio Greenhouse Gas Emissions ｜ (Appendix): About Scope 3 Data Calculation(Appendix) About Scope 3 Data Calculation
Scope 3 Upstream Data
Although the disclosure of information on GHG emissions directly caused by a company's business
operations (Scope 1) and those caused by purchased electricity (Scope 2) is relatively advanced, only
a limited number of companies aggregate and disclose Scope 3 upstream and downstream emissions.
This section will explain how Scope 3 (upstream and downstream) emissions are aggregated in
Trucost's carbon footprint and other analyses.
Scope 3 upstream emissions mainly refer to those emitted by procured products and services(excluding Scope 2 emissions) (Figure 1-35). Most of the Scope 3 upstream emissions are estimatedbased on Trucost's EEIO model. The model quantifies the economic transactions for over 450 sectors
between (1) sectors that produce goods (outputs) and (2) industries that procure goods (inputs)
produced by other sectors in the process of producing outputs. It calculates the amount of expenditure
required by other sectors throughout the supply chain, from the procurement of raw materials to thecompany's business activities. This is then combined with information on the environment to arrive at
an estimate of Scope 3 upstream for all transactions between industries in the supply chain. Taking
the automotive industry as an example, the manufacture of a single car requires inputs from otherindustries such as energy, steel, and tire manufacturing. In addition, the energy, steel, and tire
manufacturing industries also need inputs, and these goods are exchanged throughout the supply
chain. Emissions are calculated by estimating the economic transactions required to manufacture a
car across the entire supply chain and considering the environmental information on the expenditures
between individual industries.

Scope 3 downstream data
Scope 3 downstream emissions include the processing, use, and disposal of products sold, as wellas emissions from leased assets, franchises, and investments (Figure 1-35). Scope 3 downstream
data is calculated by different approaches to Scope 3 upstream, and may use data disclosed bycompanies. In this case, emissions reported by companies in the Carbon Disclosure Project (CDP)
climate change questionnaire may be used. However, to ensure quality, disclosed data is notnecessarily used as is, and only data that has been verified by a third party and can be confirmed tohave been accurately calculated in-house is accepted. To use the data disclosed by companies to the
maximum extent possible, data gaps that are not included in the scope of aggregation are filled inusing the top-down or bottom-up approach described below (Figure 1-36).

Copyright © 2021 Government Pension Investment Fund All rights reserved.

30

Chapter 1: Analysis of Portfolio Greenhouse Gas Emissions ｜ (Appendix): About Scope 3 Data Calculation

The top-down approach is used when (1) no Scope 3 data is reported at all; (2) no third-party
certification of disclosed data is obtained; or (3) only partial data is disclosed. To calculate an estimate
using the top-down approach, the verified data available from the CDP is attributed to each of the 158
industry subgroups for each of the Scope 3 categories.15 This approach makes it possible to estimate
emissions when all or part of the Scope 3 data is not disclosed, by using the factor calculated with the
public CDP data.
For major sectors, the bottom-up approach may be applied. For example, the annual CO ₂
emissions of a car are calculated as the product of the emission intensity of all vehicles sold by the
manufacturer (gCO₂/km), the number of vehicles sold, and the total distance driven (km/service life).
Note that if a company discloses downstream emissions related to Use of Products Sold, Trucost will
use the higher of the disclosed data and estimates. This is to avoid underestimating the risk of Scope
3 downstream emissions.

Limitations in the quantification of Scope 3 emissions
As previously mentioned, one of the biggest challenges in quantifying a company's Scope 3
emissions is the lack of disclosed information. The Trucost approach makes the most of available dataand calculates estimates based on disclosed information, but this approach has its limitations. For
example, in the top-down approach, estimates are determined by the companies that report Scope 3
data, so if the disclosed companies have low emissions, the emission factors used in the top-down
approach may be biased. This reporting bias is inevitable because companies with low Scope 3
emissions have more incentive to disclose their figures than companies with high Scope 3 emissions.
Improved modeling of Scope three emissions will require Scope 3 disclosure from more companies.

15

Scope 3 consists of categories 1-15; 1-8 are classified as upstream of Scope 3, and 9-15 are classified as downstream of Scope3.

Copyright © 2021 Government Pension Investment Fund All rights reserved.

31

Chapter 1: Analysis of Portfolio Greenhouse Gas Emissions ｜ (Appendix): About Scope 3 Data Calculation

Figure 1-35 Activities in Scope 3 Upstream and Downstream

Source: S&P Trucost Limited©Trucost 2021

Figure 1-36 Quantifying Scope 3 Downstream Emissions

Source: S&P Trucost Limited©Trucost 2021

Copyright © 2021 Government Pension Investment Fund All rights reserved.

32

Chapter 2 Scenario Analysis on Risks and Opportunities ｜ Enhancement of CVaR Analytical Methodology

Chapter 2:

Scenario Analysis on Risks and Opportunities

Enhancement of Climate Value-at-Risk (CVaR) Analytical Methodology
Impact of Enhancement of CVaR Analytical Models
Following on from last fiscal year, GPIF analyzed the impact of climate-change risks/opportunities
on GPIF’s portfolios using CVaR16. CVaR is a model for measuring the impact of climate change risks
and opportunities on enterprise value (EV) and security values. It consists of two components:“transition risks,” which is a combination of "policy risks" that measure the impact of regulations on
greenhouse gas emissions, and "technology opportunities" that measure profit opportunities fromtechnologies that become more advantageous as regulations are tightened; and "physical risks," which
identify the impact of natural environment changes and disasters associated with climate change.
This fiscal year's analysis model has been significantly revamped since last year. Here, we examine
the main changes and the resulting impact on the analysis results.
Major changes include:
1. Expansion of the scope of analysis to Scope 3 in analyzing policy risk CVaR
2. Addition of "fluvial flooding" to the analysis of physical risk CVaR.
3. Change in methodology to weight sector-level profit margins by revenue instead of market
capitalization
To understand the impact of this analytical method enhancement, we examined how CVaR changes
for GPIF's portfolios (aggregate of equities and corporate bonds) using the new and old models (Figure
2-1 (a) and (b)). By applying the new and old models to the data as of March 2020, we find that overall
CVaR in the 2°C scenario worsened by 8.3 percentage points, from +1.7% down to ▲6.6%. Looking
at the breakdown, both policy risks and technology opportunities decreased, while physical risks
remained broadly the same (Figure 2-2).
The most significant impact of these changes was technology opportunities. A breakdown by factor
showed that the most significant impact (▲4.3%) was caused by using revenue to calculate weighted
averages for the sector-level profit margins used in CVaR calculations rather than market capitalization.
Using revenue-based weighted averages is likely to result in more stable data than using market
capitalization, which may change significantly due to stock price movements. In addition, the change
reduces the excessive impact caused by some large companies with extremely large market
capitalizations in industries with fewer companies.
The factors behind changes in policy risks, on the other hand, included the impact of changes inmarket capitalization (▲1.7%), the impact of expanding the scope of analysis to Scope 3 (▲3.2%)

16

Please refer to P.58 for more information on CVaR analytical methods

Copyright © 2021 Government Pension Investment Fund All rights reserved.

33

Chapter 2 Scenario Analysis on Risks and Opportunities ｜ Enhancement of CVaR Analytical Methodology

and the refinement of Scope 2 (▲1.6%), similar to technology opportunities. Some of these costs were
included in Scope 1 in the old model, however, and the resulting transfer to Scope 2 and Scope 3
resulted in positive impact of +4.6%.
Comparing the results of the new model to look at the essential changes in climate-change risks
and opportunities in GPIF portfolios over the last year, we saw positive, albeit slight, changes in allcomponents: policy risks, technology opportunities, and physical risks (Figures 2-1, (b) and (c)).
In addition to the enhancement of analytical methodologies and changes in corporate behavior, there
are other factors that influence CVaR values, such as stock prices. In this model, if enterprise value,calculated as the sum of equity market capitalization and debt, doubles, the absolute value of CVaR
will be reduced by one-half, even if other factors such as the company's climate-change risks andopportunities remain unchanged. Therefore, 2020’s historic rise in global equity markets also pushed
down absolute CVaR values.
Figure 2-1 Changes in GPIF Portfolio CVaR (Total of Equities and Corporate
Bonds) Due to Analysis Model Enhancement
Old Model

New Model

March 2020(a)March 2020(b)

March 2021
(c)

1.7

-6.6

-5.7

8.1

-0.4

0.1

Policy Risks

-6.6

-8.6

-8.2

Technological Opportunities

14.7

8.2

8.3

-6.4

-6.2

-5.8

Aggregated CVaR (%)
Transition Risks and Opportunities

Physical Risks
Note: Based on 2℃ scenario

Source: Reproduced by permission of MSCI ESG Research LLC©2021

Figure 2-2 Breakdown of Changes in GPIF Portfolio CVaR (Total of Equities and Corporate Bonds)
Due to Analysis Model Enhancement by Factor

Copyright © 2021 Government Pension Investment Fund All rights reserved.

34

Chapter 2 Scenario Analysis on Risks and Opportunities ｜ CVaR by Temperature Increase Scenario

CVaR by Temperature Increase Scenario
Analyzing the Impacts of CVaR on Different Temperature Rise Scenarios
In this report, we calculated CVaR for a scenario in which the global average temperature rise fromthe pre-industrial period to the end of this century does not surpass 2°C (the 2°C scenario) andconducted our analysis based on the result of those calculations. As CVaR results vary depending on
the temperature increase scenario being assumed, we first confirm the CVaR of GPIF’s equity andcorporate bond portfolio under scenarios in which policies are implemented to limit temperature
increases to 1.5°C, 2°C, and 3°C (Figure 3).
To understand the overall trend represented by each of the scenarios, we focused first on aggregate
CVaR for the total portfolio and found that the risks to the portfolio are smallest in the 1.5°C scenario,
while the negative impact increases more as we move toward the 2°C and 3.0°C scenarios (i.e. lesspolicy restrictions). Compared with last year’s report, the gaps in CVaR between each scenario aresmaller, owing largely to the analysis model enhancement. However, for both equities and corporate
bonds, the impact of technological opportunities and policy risks are higher in the scenarios withgreater curbs in temperature rises, indicating that climate policy trends are likely to have a significant
impact on corporate value. Investors will have to pay close attention to climate change policy trends
going forward as these will play a pivotal role in investment decisions.
Figure 2-3 CVaR by Temperature Increase Scenario
（%）

25
20
15
10
5
0
-5
-10
-15
-20
-25
-30

-5.6

Scope 1+2

Scope 3

Physical Risks

Aggregated CVaR

-5.7

-5.8

-5.4

Technological Opportunities

-5.8

-6.0

-4.6

-9.0

1.5℃

2℃
Total Portfolio

3℃

1.5℃

2℃
Total Equities

3℃

1.5℃

2℃

-1.1

3℃

Total Bonds

Note1: Physical risks are analyzed under assumptions corresponding to a 4°C–6°C scenario.
Note2: "Scope 1+2" and "Scope 3" indicate policy risks associated with these scopes.
Source: Reproduced by permission of MSCI ESG Research LLC©2021

Copyright © 2021 Government Pension Investment Fund All rights reserved.

35

Chapter 2 Scenario Analysis on Risks and Opportunities ｜ CVaR by Temperature Increase Scenario

Impact Analysis by Different Temperature Rise Scenario (by Asset Class)
Next, we looked at CVaR for GPIF’s portfolio by asset class. Figure 2-4 provides a breakdown bytemperature rise scenario. First, a comparison of equities and bonds revealed a clear difference in theimpact of technological opportunities. For corporate bonds, increased earnings from technologicalopportunities could contribute positively to bond prices through reduced default risk, but the impact islimited as the positive impact is capped at par. On the other hand, the positive impacts of technology
opportunities for equities were significant due to the effect on super-long-term cash flows accumulatingover time. For domestic equities with large patents in low-carbon technologies, the 2°C scenario and
1.5°C scenarios had more positive impacts on enterprise value in terms of overall CVaR than that of
the 3°C scenario.
Figure 2-4（%）
40

CVaR (Equities and Bonds) by Temperature Rise Scenarios
Scope 1+2

Scope 3

Technological Opportunities

Physical Risks

Aggregated CVaR

30
20
10
0

0.6

-4.2

-8.5

-10
-20

-7.5

-11.4

-3.7

-5.4

-5.8

-6.0

3℃
scenario

1.5℃
scenario

2℃
scenario

3℃
scenario

-30
-40
1.5℃
scenario

2℃
scenario

3℃
scenario

1.5℃
scenario

Domestic Equities

（%）
2
0
-2
-4
-6
-8
-10
-12
-14

Scope 1+2

2℃
scenario
Foreign Equities

Scope 3Equities Total

Technological Opportunities

Physical Risks
-0.7

-1.7

-1.1

-4.1

-5.3

Aggregated CVaR

-4.6

-7.2

-9.0

-11.6
1.5℃
scenario

2℃
scenario

3℃
scenario

Domestic Bonds

1.5℃
scenario

2℃
scenario
Foreign Bonds

3℃
scenario

1.5℃
scenario

2℃
scenario

3℃
scenario

Bonds Total

Note1: Physical risks are analyzed under assumptions corresponding to a 4°C–6°C scenario.
Note2: "Scope 1+2" and "Scope 3" indicate policy risks associated with these scopes.
Source: Reproduced by permission of MSCI ESG Research LLC©2021

Copyright © 2021 Government Pension Investment Fund All rights reserved.

36

Chapter 2 Scenario Analysis on Risks and Opportunities ｜ Technological Opportunities

Technological Opportunities
Technology Opportunities and Patent Scores
The Low Carbon Technology Opportunity CVaR analysis examines how enterprise value andsecurity values are likely to change during the transition to a low-carbon economy as the result of
earnings growth stemming from low-carbon technologies. This is calculated based on an assessmentof companies' low-carbon technology patent acquisition status and current low-carbon technologyrelated revenues. The models are based on patent scores developed by the Swiss Federal Institute ofIntellectual Property in collaboration with MSCI Climate Research Centre17.
We saw previously that technological opportunities have changed dramatically from last year due toenhancements made to the analysis model. Here, we investigate the patent scores used to calculatetechnological opportunities for companies included in GPIF’s equity and corporate bond portfolios.
While analysis results are affected by the amounts invested in individual companies, the portfolio asof March 31, 2021 examined in this analysis is mainly managed passively, and is generally in line withthe policy asset mix. As such, in terms of equities, the portfolios do not deviate significantly from policy
benchmarks. The patent score calculation tabulates all low-carbon technology patents held by a given
company and reflects any change in the number of such patents. The results of this analysis do notdiffer greatly from the previous year, with domestic companies in the automotive and energy supply
sectors scoring exceptionally high. The inter-industry transfer of transition risks and opportunities
analysis introduced on page 65 employs a different methodology to assess the patent competitivenessof decarbonization technologies by county and region.

Patent Score: Characteristics by Asset
Looking at patent scores by sector, the consumer discretionary sector, which includes automotive
manufacturers, scored markedly higher compared with other sectors in the domestic equities portfolio.
Within this sector, “automobiles” had the highest patent score, followed by “energy supply,” “electricvehicles,” and “chemicals” (Figure2-5). In the information technology sector, patent scores are high in“energy supply” and “automobiles.” Meanwhile, in the case of foreign equities, the scores for industrials
are the highest, with patents related to aircraft, wind power, and automobiles making major
contributions. In the information technology sector, “information technology” scored highly, while“automobiles” scored highly in the consumer discretionary sector, similar to domestic equities (Figure26).In the domestic bond portfolio as well, “automobiles” tend to have higher scores in the consumer
17

For details of the analysis methodology, please refer to P.63.

Copyright © 2021 Government Pension Investment Fund All rights reserved.

37

Chapter 2 Scenario Analysis on Risks and Opportunities ｜ Technological Opportunities

discretionary sector as in the domestic equity portfolio, as does “energy supply” in the information
technology sector. For foreign corporate bonds, there was an increase in the weighted average patentscores in“automobiles” and “energy supply” for the consumer discretionary sector (Figures 2-7 and 28).
Figure 2-5 Technological Opportunities: Domestic

Figure 2-6

Equity Portfolio

Equity Portfolio
0

1,000

2,000

3,000

Technological Opportunities: Foreign

4,000

0

Consumer Discretionary

Industrials

Information Technology

Information Technology

Industrials

Consumer Discretionary

Materials

Automobiles
Batteries
Construction
ChemicalsElectric Vehicles
Energy Supply
GHG Reduction Technology
Hydrogen Fuel
Information Technology
Solar
PlanesWind Power
OthersUtilities
EnergyReal EstateConsumer Staples
Health Care
Communication Services
Financials（Weighted Average Patent Score）

EnergyHealth Care
Communication Services
Consumer Staples
Financials
Utilities
Real Estate

Corporate Bond Portfolio

Corporate Bond Portfolio
1,500Technological Opportunities: Foreign

0

2,000

Consumer Discretionary

Consumer Discretionary

Information Technology

Industrials

Materials

EnergyUtilities
Industrials
EnergyHealth Care
Real EstateCommunication Services
Consumer Staples
Financials

Automobiles
Batteries
Construction
ChemicalsElectric Vehicles
Energy Supply
GHG Reduction Technology
Hydrogen Fuel
Information Technology
Solar
PlanesWind Power
Others（Weighted Average Patent Score）

Source: Reproduced by permission of MSCI ESG Research LLC©2021

400（Weighted Average Patent Score）

Figure 2-8

1,000

300

Automobiles
Batteries
Construction
ChemicalsElectric Vehicles
Energy Supply
GHG Reduction Technology
Hydrogen Fuel
Information Technology
Solar
PlanesWind Power
OthersMaterials

Figure 2-7 Technological Opportunities: Domestic

500

200

Source: Reproduced by permission of MSCI ESG Research LLC©2021

Source: Reproduced by permission of MSCI ESG Research LLC©2021

0100

Information Technology

200

400

600

800 1,000

Real Estate

Automobiles
Batteries
Construction
ChemicalsElectric Vehicles
Energy Supply
GHG Reduction Technology
Hydrogen Fuel
Information Technology
Solar
PlanesWind Power
OthersFinancials（Weighted Average Patent Score）

Materials
Utilities
Health Care
Communication Services
Consumer Staples

Source: Reproduced by permission of MSCI ESG Research LLC©2021

Copyright © 2021 Government Pension Investment Fund All rights reserved.

38

Chapter 2 Scenario Analysis on Risks and Opportunities ｜ Policy Risks

Policy Risks
Climate-Change Policy-Risk CVaR
We also analyzed policy risks, which, together with technological opportunities, constitute transition
risks and opportunities. The Climate Change Policy Risk CVaR (Policy Risk CVaR) calculates the costs
incurred by companies by future policies related to climate change, assuming super long term to theend of 21st century. This model analyzes the impact of downside risks to enterprise and security values
from policies related to climate change by calculating the estimated future emission reduction costs
required by policies related to climate change18 at the corporate level.

Expanding the Analysis to Scope 3
In the policy risk evaluation conducted in the supplementary guide to last year’s ESG Report 2019,
we analyzed the Scope 1 and Scope 2 emissions of companies in the portfolio. This year, the scopeof the analysis was expanded to include Scope 3 emissions. These emissions consist of “upstream
Scope 3,” which encompasses the raw materials, services, and labor inputs to companies’ production
activities, and “downstream Scope 3,” which covers the sale of produced goods and services. In theanalysis, we focused on changes in Scopes 1 and 2 from the previous year and the magnitude of
Scope 3 risks (Figures 2-9～12).

Policy Risk of Domestic Equity Portfolios
For overall policy risk CVaR including Scope 3, results for domestic equities showed that there weregreater risks in the energy sector (which includes companies such as fossil fuel mining companies),
the utilities sector (which includes electric power and other companies), and the materials sector, whilerisks in the healthcare, telecommunications services, and financial sectors remain low.
This was a similar trend to last year. Scope 1 and 2 risks decreased across all sectors (industries)
from the previous year, including energy (11.5 percentage points), utilities (4.8 percentage points), andmaterials (9.1 percentage points). This may be largely attributable to the fact that a portion of the costsof reducing emissions were passed through to the corporate value chain as a result of the introductionof Scope 3 in the current fiscal year.
Meanwhile, Scope 3 risks tend to be smaller than those of Scopes 1 and 2 in all sectors as a whole.
This is due to the fact that, although absolute Scope 3 greenhouse gas emissions are generally large,
18

Please refer to P.59 for details of the analysis methodology.

Copyright © 2021 Government Pension Investment Fund All rights reserved.

39

Chapter 2 Scenario Analysis on Risks and Opportunities ｜ Policy Risks

this is not necessarily the case when companies’ assumed burden rates are taken into account. By
sector, energy and utilities have the highest Scope 3 policy risks, followed by the consumer
discretionary sector, which includes automobiles. Conversely, for Scopes 1 and 2, risks for thematerials sector exceed those for the consumer discretionary sector. Foreign equities showed thesame trend as last year, with risks in the utilities, energy, and materials sectors remaining high.
Policy risks in the utilities sector also increased from last year. Compared with foreign equities,
domestic equity policy risks are greater in the energy sector, because certain companies in the sector
are weighted more heavily than others.

Policy Risk in Foreign Equity Portfolios
The same trend was observed in foreign equities last year, with substantial risks in "energy,""utilities," and "materials." For Scope 1+2, the change from last year in each sector (industry) showedthat while risk declined in most sectors, as was case with domestic equities, the utilities sector
experienced a slight increase in risk. This was attributable to the increase in CO₂ emissions from 2018
to 2019 leading to a higher emission reduction amount assigned to each sector to achieve the carbon
budget, in addition to higher carbon prices. Focusing on Scope 3, foreign equities also generally
tended to have lower risks than that of Scope 1 and 2, with sector-specific results showing greaterrisks for "energy," "utilities," and "materials," similar to Scope 1+2.
Figure 2-9 Policy Risk: Domestic Equity Portfolio
SectorPolicy Risk
CVaR

Figure 2-10 Policy Risk: Foreign Equity Portfolio

Change fromprevious year

Scope1+2

Scope3

Sector(percentage

Policy Risk
CVaR

points)Change fromprevious year

Scope1+2

Scope3(percentage
points)Communication Serv ices

-1.1%
-1.2%

-0.5%
-0.6%

-0.6%
-0.7%

0.1%
0.3%

Inf ormation Technology
Health Care

-0.8%
-1.3%

-0.5%
-0.8%

-0.4%
-0.5%

0.2%
0.1%

Financials

-2.1%

-0.8%

-1.3%

0.0%

Real Estate

-1.6%

-1.3%

-0.3%

0.1%

Real Estate

-2.7%

-1.3%

-1.4%

0.5%

Financials

-1.7%

-1.1%

-0.6%

0.2%

Inf ormation Technology

-2.8%

-1.5%

-1.3%

0.5%

Communication Serv ices

-1.7%

-1.5%

-0.3%

0.3%

Consumer Staples

-3.6%

-1.3%

-2.3%

0.5%

-6.0%

-4.2%

-1.8%

1.7%

-6.5%
-21.2%

-1.1%
-2.6%

3.5%
12.3%

Health Care

-6.5%

-3.5%

-3.0%

0.6%

Consumer Discretionary

Industrials-10.0%

-6.5%

-3.5%

1.9%

Consumer Staples

Consumer Discretionary-2.6%-25.3%

-8.4%
-4.8%

1.6%
9.1%

Industrials

Materials-11.0%-30.1%

Materials-7.6%-23.9%

Utilities-69.7%-46.8%-23.0%

4.8%

Utilities-36.8%-32.9%

-3.9%

-3.8%

Energy-95.2%-63.2%-32.0%

11.5%

Energy-46.6%-31.3%-15.3%

17.9%

Note: Changes f rom the prev ious y ear ref ers to changes in Scopes 1 + 2

Note: Changes f rom the prev ious y ear ref ers to changes in Scopes 1 + 2

Source: Reproduced by permission of MSCI ESG Research LLC©2021.

Source: Reproduced by permission of MSCI ESG Research LLC©2021.

Copyright © 2021 Government Pension Investment Fund All rights reserved.

40

Chapter 2 Scenario Analysis on Risks and Opportunities ｜ Policy Risks

Policy Risks in the Domestic Corporate Bond Portfolio
Looking at corporate bonds, we confirmed that the overall level of policy risk tends to be lower thanthat of equities. The results for domestic corporate bonds showed significant risks in energy, utilities,
and materials. For Scope 1+2, the range of change from last year in each sector (industry) showedthat while risks declined in most sectors, utilities experienced increased risk. Focusing on Scope 3,
the risk in the energy sector outweighed the risk of Scope 1+2. This was because companies withhigher Scope 3 risk than Scope 1+2 risk had relatively high weights in the energy sector for domestic
corporate bonds. It suggests that the risk associated with the supply chain, i.e. energy extraction andenergy consumption, is greater than that of the policy risk associated with energy production.

Policy Risk of Foreign Corporate Bond Portfolios
The results for foreign corporate bonds revealed significant risks for utilities, energy, and materials.
For Scope 1+2, the range of change from last year in each sector (industry) showed a slight increasein risk for most sectors but a slight decrease in risk for utilities and materials. Focusing on Scope 3,
overall risk tended to be less than that of the risk of Scopes 1 and 2.
Figure 2-11 Policy Risk: Domestic Corporate Bond

Figure 2-12 Policy Risk: Foreign Corporate Bond

Portfolio

Portfolio

SectorPolicy Risk
CVaR

Change fromprevious year

Scope1+2

Scope3

Sector(percentage

Policy Risk
CVaR

points)0.0%
0.0%

Real Estate

Scope3(percentage
points)Financials
Real Estate

-0.1%

0.0%

-0.1%

0.1%

Health Care

-0.2%

-0.2%

-0.1%

0.0%

Inf ormation Technology

-0.2%

-0.2%

0.0%

0.1%

Communication Serv ices

-0.2%

-0.2%

0.0%

0.1%

Health Care

-0.3%

-0.1%

-0.2%

0.0%

Consumer Discretionary

-1.0%

-0.5%

-0.6%

-0.1%

Consumer Staples

-0.4%

-0.2%

-0.2%

0.1%

Financials

-1.3%

-1.1%

-0.1%

-1.0%

Consumer Discretionary

-0.8%

-0.1%

-0.7%

0.1%

Consumer Staples

-1.9%

-1.4%

-0.6%

-0.6%

Materials-2.2%-19.3%-2.0%-18.7%

-0.2%
-0.6%

1.7%
9.3%

Industrials
Materials-6.7%-13.5%-6.6%-13.2%

-0.2%
-0.3%

-2.8%
1.1%

Utilities-24.7%-23.6%-1.1%-15.2%

Energy-17.7%-13.1%

-4.6%

-0.5%

Energy-39.7%-11.7%-28.0%

35.4%

Utilities-20.6%-20.4%

-0.2%

4.2%

Industrials

0.0%
0.0%

Scope1+2

0.0%
-0.1%

Communication Serv ices

0.0%
0.0%

Change fromprevious year

Inf ormation Technology

-0.1%
-0.2%

-0.1%
-0.2%

0.0%
0.0%

0.0%
-0.1%

Note: Changes f rom the prev ious y ear ref ers to changes in Scopes 1 + 2

Note: Changes f rom the prev ious y ear ref ers to changes in Scopes 1 + 2

Source: Reproduced by permission of MSCI ESG Research LLC©2021.

Source: Reproduced by permission of MSCI ESG Research LLC©2021.

Copyright © 2021 Government Pension Investment Fund All rights reserved.

41

Chapter 2 Scenario Analysis on Risks and Opportunities ｜ Physical Risks

Physical Risks
Physical Risks
In the physical risk analysis, we examined potential deterioration in corporate revenues arising fromasset damage and productivity declines caused by climate change-induced abnormal weather, suchas floods and extreme heat19. At the same time, we also analyzed the potential for increased revenues
resulting from such extreme weather. For example, if rising temperatures lead to an improvement in
operating rates and a reduction in heating costs in cold regions, the results of the physical risk analysis
will be positive. This year, we started analyzing fluvial flooding risk to evaluate the impact of river
overflows caused by heavy rain and other factors.

Physical Risk in Equity Portfolios
As was the case last year, physical risks by sector and by portfolio continue to show different trends
from policy risks (Figures 2-13, 2-14). Equities were found to be generally riskier than bonds. We also
found that domestic equity portfolios in particular, tend to be riskier than foreign equity portfolios.
In the domestic equity portfolio, the utilities and energy sectors were shown to have significant
physical risks in addition to policy risks, followed by the financials and consumer staples sectors. On
the other hand, the risk to telecommunications services, which was high last year, has decreased due
to an increase in the ratio of investment in companies with relatively low physical risks. In the foreign
equity portfolio, the financials, real estate, and telecommunications services sectors have significant
physical risks. Most of these are caused by coastal flooding and extreme heat. It is likely that financials
are affected by the location of physical storefronts, and the consumer staples sector is affected by thefact that many production bases and distribution facilities are located at low altitudes, exposing themto the risk of flooding.
The utilities sector was found to have the highest physical risk both domestically and internationally,
which was mainly due to changes in the methodology for assessing physical risk exposures. Whenestimating the physical risks for each facility, we previously aggregated total corporate revenue by
country and allocated this equally across all facilities. The new assessment methodology, however,estimates revenues for each facility location owned by the company based on production activity,
which results in a higher risk assessment for utilities engaged in coastal power generation. The
Physical Risk CVaR assesses not only the direct property damage incurred when an individual facility
suffers flooding or other damage, but also the reduction in revenues associated with the disruption of19

For details of the analysis methodology, please refer to P.64.

Copyright © 2021 Government Pension Investment Fund All rights reserved.

42

Chapter 2 Scenario Analysis on Risks and Opportunities ｜ Physical Risks

productive activities on a facility-by-facility basis. In the worst case scenario for coastal flooding
damage caused by sea level rise, utilities not only suffer direct acute flood damage to power generation
facilities, but profits are also expected to decline due to the interruption of power generation businessactivities. Therefore, the new physical risk assessment method would result in a higher assessmentof physical risk if power generation and other production facilities are located on the coast and face
flood risk.
For both domestic and foreign portfolios, extreme heat has a significant impact on the energy sector,
where temperature increases and other factors are likely to impact fossil fuel mining efficiency and therefining business. Industrials were considered to have high policy risks in both the domestic andforeign portfolios, but the analysis showed that physical risks for this sector are low.

Physical Risk in Fixed Income Portfolios
For domestic bonds, physical risks were found to be highest in the utilities sector, followed by thehealthcare, consumer staples, and materials sectors, while for foreign bonds, the consumer
discretionary, real estate, and financials sectors had the highest risk (Figures 2-15、2-16). It is likelythat the risk of coastal flooding is high in any of these portfolios because of the location of facilities
such as storefronts and factories.
Figure 2-13 Physical Risks: Domestic Equity portfolio
Utilities
EnergyFinancials
Consumer Staples
Materials
Industrials
Real EstateConsumer Discretionary
Health Care
Communication Services
Information Technology

Coastal Flooding
Extreme Cold
Fluvial Flooding
Extreme Heat
Extreme Precipitation
Heavy Snowfall
Tropical Cyclones
Extreme Wind
-80

-70

-60

-50

Source:Reproduced by permissionof MSCI ESG Research(c) LLC.

-40

-30

-20

-10

0

10

(Weighted Average Physical Risks CVaR, %)Copyright © 2021 Government Pension Investment Fund All rights reserved.

43

Chapter 2 Scenario Analysis on Risks and Opportunities ｜ Physical Risks

Figure 2-14 Physical Risks: Foreign Equity Portfolio
Utilities
EnergyFinancials
Real EstateCommunication Services
Consumer Staples
Materials
Industrials
Health Care
Consumer Discretionary
Information Technology-10

Coastal Flooding
Extreme Cold
Fluvial Flooding
Extreme Heat
Extreme Precipitation
Heavy Snowfall
Tropical Cyclones
Extreme Wind
-8

-6

-4

-2

0

2

(Weighted Average Physical Risks CVaR, %)Source:Reproduced by permissionof MSCI ESG Research(c) LLC.

Figure 2-15 Physical Risks: Domestic Bond Portfolio
Utilities
Health Care
Consumer Staples
Materials
EnergyReal Estate
Industrials
Financials
Consumer Discretionary
Communication Services
Information Technology-10

Coastal Flooding
Extreme Cold
Fluvial Flooding
Extreme Heat
Extreme Precipitation
Heavy Snowfall
Tropical Cyclones
Extreme Wind
-8

-6

-4

-2

0

2

(Weighted Average Physical Risks CVaR, %)Source:Reproduced by permissionof MSCI ESG Research(c) LLC.

Figure 2-16 Physical Risks: Foreign Bond Portfolio
Consumer Discretionary
Real Estate
Financials
Industrials
EnergyCommunication Services
Utilities
Consumer Staples
Materials
Health Care
Information Technology

Coastal Flooding
Extreme Cold
Fluvial Flooding
Extreme Heat
Extreme Precipitation
Heavy Snowfall
Tropical Cyclones
Extreme Wind
-3

-2.5

-2

Source:Reproduced by permissionof MSCI ESG Research(c) LLC.

-1.5

-1

-0.5

0

0.5

(Weighted Average Physical Risks CVaR, %)Copyright © 2021 Government Pension Investment Fund All rights reserved.

44

Chapter 2 Scenario Analysis on Risks and Opportunities ｜ CvaR Analysis of Government Bond Portfolio

Climate Value-at-Risk Analysis of Government Bond Portfolio
CVaR Analysis of Government Bonds
Last year, we conducted a CVaR analysis of equities and corporate bonds only, but this year, we
also conducted the same analysis for government bonds. While the analysis for equities and corporate
bonds estimates the impact on securities values, the CVaR methodology for government bonds
assesses how the implementation of policies to achieve the 2°C target would affect GDP trends forindividual countries through 2050.
In particular, this analysis attempts to answer the following questions:①

Does early achievement of emission reduction targets by 2030 lead to greater transition costs?

②

Does the early decarbonization of the economy lead to better economic outcomes than delayed
decarbonization by 2050?

③

Do these patterns vary significantly from country to country?

The REMIND Model
This analysis uses an Integrated Assessment Model. Integrated Assessment Models
comprehensively evaluate the interrelationships between macroeconomics, global science, andenergy systems. These models use GDP trends, emission targets, and many other data points as
inputs, and produce data such as surface temperatures, carbon prices, emission pathways, and GDP
estimates as outputs. While economic forecasts usually focus on the accuracy of short-term GDP
figures, the integrated assessment model focuses on long term GDP impact. Our analysis also focuseson scenario differences rather than absolute levels of GDP impact.
Specifically, this report uses the REMIND model (REMIND1. 7-MagPIE 3. 0 Integrated Assessment
Model), which was developed by the Potsdam Institute for Climate impact Research and was one of
the three integrated assessment models adopted by NGFS (the Network of Central Banks andSupervisors for Greening the Financial System) during Phase 1. Although macroeconomic impact
analysis using integrated assessment models has been conducted in the past, the results have beendifficult to incorporate into investment analysis due to differences in the assumptions made by thevarious analysis agencies involved. To address this issue, NGFS developed several "NGFS scenarios"that standardize the various assumptions across integrated assessment models.
The REMIND (REgional Model of Investment and Development) model first analyzes the “Energy
System Module (Figure 2-17, green and blue)”. In this study, we set a constraint to limit global
cumulative CO₂ emissions during 2011 to 2100 to 1,000Gt, which is aligned with a 2℃ scenario.
Different carbon prices are also set for each region, and gradually consolidate to one universal price.

Copyright © 2021 Government Pension Investment Fund All rights reserved.

45

Chapter 2 Scenario Analysis on Risks and Opportunities ｜ CvaR Analysis of Government Bond Portfolio

Furthermore, each country’s capacity for CO ₂ elimination (Carbon Dioxide Removal: CDRs), isestimated based on survey results in the REMIND model. After completing all these analyses, themacroeconomic module (Figure 2-17, red) analysis is conducted. The macroeconomic analysis
examines three production factors: labor, capital, and energy use. Differences in GDP impact between
scenarios are mainly attributable to energy use differences among these production factors.
Figure 2-17 Specifications of REMIND Model

Early Response Scenario and Delayed Response Scenario
Two scenarios were reviewed in this analysis. There is no one single path to achieving the 2°C target
by the end of this century; for this analysis, we assumed (1) an immediate 2°C scenario, in which
proactive climate action is taken immediately, and (2) a delayed 2°C scenario, in which climate action
is delayed. The main assumptions for these two scenarios are as follows:(1) For the immediate 2°C scenario, we assume that the power generation capacity from renewableenergy will rapidly expand in the 2020s, carbon prices will surge throughout the world in the 2030s,
and decarbonization efforts will accelerate across the entire economy (Figure 2-18).
(2) For the delayed 2°C scenario, we assume that by 2030 each country will achieve the nationaltargets set in 2016 at the conclusion of the Paris Agreement on the one hand, but on the other thatenvironmentally friendly energy technologies will not become widespread until that year. The analysis
also assumes that carbon prices will not rise significantly until 2030 and will rise sharply thereafter(Figure 2-18).

Copyright © 2021 Government Pension Investment Fund All rights reserved.

46

Chapter 2 Scenario Analysis on Risks and Opportunities ｜ CvaR Analysis of Government Bond Portfolio

Figure 2-18 Carbon Price Assumptions by Country (US$2010 per t CO₂)
Carbon Price, Delayed 2C, limited
CDR (US$2010/t CO₂ )

2020

2030

2040

Japan

3.3

13.7

359.0

USA

3.3

48.7

376.6

Europe

5.5

57.3

381.0

2020

2030

Japan

3.3

96.3

USA

3.3

96.3

Europe5.5

97.4

Carbon Price, Immediate 2C,
limited CDR (US$2010/t CO₂ )

2050

2060

2070

2080

2090

2100

704.4

1,147.4

1,644.1

2,140.9

2,637.6

3,134.3

2040

2050

2060

2070

2080

2090

2100

189.3

308.3

502.2

719.6

937.1

1,154.5

1,372.0

Source: Reproduced by permission of MSCI ESG Research LLC©2021

Analysis Results
Using the REMIND model, we analyzed GDP impact in the early and delayed scenarios for Japan,
the United States, and Europe. Results showed that the early response scenarios reached the same
GDP level of the delayed response scenarios by at least 2040. Therefore, the cost of taking early
action to achieve the 2°C scenario could be lower than delayed action.
In Japan, the United States, and Europe, each region showed a decline in GDP when climate
measures were taken, although the magnitude of the impact varies by scenario and region.
Figure 2-19 shows the difference in the impact on GDP between the immediate 2°C scenario andthe delayed 2°C scenario (difference in GDP between the two scenarios). If the value on the graph is
positive (negative), it can be interpreted as a positive (negative) impact on GDP if the immediate 2°C
scenario is implemented.
In the case of Japan, the immediate 2°C scenario has a negative impact on GDP as of 2030, but apositive impact on GDP as of 2040 and 2050. In the United States and Europe, the immediate 2°C
scenario has a positive impact on GDP at all time points—2030, 2040, and 2050. The result of thisanalysis shows that the immediate 2°C scenario can be expected to have a positive impact on GDP
in the long term compared with the delayed 2°C scenario.

Copyright © 2021 Government Pension Investment Fund All rights reserved.

47

Chapter 2 Scenario Analysis on Risks and Opportunities ｜ CvaR Analysis of Government Bond Portfolio

Figure 2-19 Analysis of GPIF Government Bond Portfolio: Difference in GDP between Immediate 2°C
Scenario and Delayed 2°C Scenario

Note: Based on GPIF portfolio as of the end of April 2020
Source: MSCI ESG Research LLC, REMIND-MAGPIE 1.7-3.0, NGFS Phase I Scenarios of June 2020,IIASA 2020

Copyright © 2021 Government Pension Investment Fund All rights reserved.

48

Chapter 2 Scenario Analysis on Risks and Opportunities ｜ Analysis of Portfolio Global Warming Potential

Analysis of Portfolio Global Warming Potential
What is the Global Warming Potential Analysis?
Global warming potential is a measure of the extent to which greenhouse gases emitted by thecompanies reviewed can potentially contribute to global warming, expressed as an increase intemperature. Specifically, we estimate individual companies’ greenhouse gas emission trends through2100, and gauge how much global average temperatures would increase if all greenhouse gas
emissions followed the same path.
In estimating warming potential, we (1) derive a function linking carbon intensity to warming potential
for each sector based on literature such as the Emissions Gap Report published by United Nations
Environment Programme (UNEP), (2) estimate the future carbon intensity of each company (Figure220), (3) calculate the warming potential for each company in the portfolio using the function derived in(1) and the carbon intensity of each company estimated in (2) (Figure2-21), and (4) calculate theweighted average warming potential of the portfolio using the portfolio weight of each company.
Revenue from clean technologies expected to have the effect of preventing global warming isdesignated as “Cooling Potential,” which pushes down overall warming potential. MSCI estimates the
Cooling Potential per dollar of revenue for each company based on publications such as the Emissions
Gap Report published by UNEP.
Last year’s analysis only included scope 1 (direct) GHG emissions. This year’s analysis includes
scope 2 (indirect emissions) and scope 3 (indirect emissions), as well as the company's emissions
reduction targets. Corporate emissions reduction targets may be based on carbon intensity or absoluteemissions, and the boundary (scope) may vary from company to company, so data are standardized
based on models when conducting analyses.

Overall Global Warming Potential of GPIF Portfolios
The results of the analysis showed that the warming potential of GPIF’s portfolio as a whole was
3.40°C for domestic equities, 3.26°C for domestic bonds, 3.49°C for foreign equities, and 4.34°C for
foreign bonds (Figures 2-22～25). In all asset classes, warming potential is well above 2°C. Looking
at domestic and overseas trends, the warming potential for foreign companies was generally higher
than that for domestic companies.
A breakdown of trends by sector reveals that warming potential tended to be high in the energy andmaterials sectors across all asset classes (Figures 2-22～25), while a comparison of the domestic andoverseas portfolios shows that the warming potential of foreign companies is higher than that of

Copyright © 2021 Government Pension Investment Fund All rights reserved.

49

Chapter 2 Scenario Analysis on Risks and Opportunities ｜ Analysis of Portfolio Global Warming Potential

Japanese companies, particularly in the energy and materials sectors.
In all cases, warming potential is naturally lower when emission reduction targets are factored inthan when they are not. To bring the global warming potential closer to 2°C, it is critical for companies
to set reduction targets and take action to achieve them.
Figure 2-20

Conceptual Diagram of Global Warming Potential Calculation

Source: Reproduced by permission of MSCI ESG Research LLC©2021

Figure 2-21

Data Used in Global Warming Potential Calculation

Source: Reproduced by permission of MSCI ESG Research LLC©2021

Copyright © 2021 Government Pension Investment Fund All rights reserved.

50

Chapter 2 Scenario Analysis on Risks and Opportunities ｜ Analysis of Portfolio Global Warming Potential

Figure 2-22
℃
8

3.40
(3.28)

Global Warming Potential of GPIF's Domestic Equity Portfolio
6.13(5.69)

4.26(4.16)

4.11(3.89)

4.04(3.86)

3.63(3.63)

3.66(3.32)

3.30(3.28)

3.05(2.94)

2.71(2.62)

3.01(2.88)

2.56(2.53)

6
4
2
0
-2
-4

Scope 1+2 Warming Potential

Scope 3 Warming Potential

Cooling Potential

Aggregated WP

Note: Global warming potential does not include reduction targets. Figures for global warming potential in consideration of
reduction targets are shown in parentheses in the label.
Source: Reproduced by permission of MSCI ESG Research LLC©2021

Figure 2-23
℃
8
6
4

3.26
(3.19)

Global Warming Potential of GPIF’s Domestic Bond Portfolios
5.24(4.74)

3.61(3.47)

3.97(3.60)

4.17(3.96)

3.34(3.34)

3.59(3.51)

4.03(4.02)

2.64(2.58)

3.18(2.91)

2.41(2.35)

2.76(2.71)

20-2-4

Scope 1+2 Warming Potential

Scope 3 Warming Potential

Cooling Potential

Aggregated WP

Note: Global warming potential does not include reduction targets. Figures for global warming potential in consideration of
reduction targets are shown in parentheses in the label.
Source: Reproduced by permission of MSCI ESG Research LLC©2021

Copyright © 2021 Government Pension Investment Fund All rights reserved.

51

Chapter 2 Scenario Analysis on Risks and Opportunities ｜ Analysis of Portfolio Global Warming Potential

Figure 2-24℃

3.49
(3.38)

Global Warming Potential of GPIF's Foreign Equity Portfolios
7.34(7.28)

4.06(3.99)

4.07(3.83)

8
6
4
2
0
-2
-4

Scope 1+2 Warming Potential

4.88(4.77)

3.23(3.17)

2.80(2.50)

Scope 3 Warming Potential

5.27(5.18)

3.10(3.07)

Cooling Potential

2.80(2.66)

3.02(2.93)

3.54(3.41)

Aggregated WP

Note: Global warming potential does not include reduction targets. Figures for global warming potential in consideration of
reduction targets are shown in parentheses in the label.
Source: Reproduced by permission of MSCI ESG Research LLC©2021

Figure 2-25

Global Warming Potential of GPIF's Foreign Bond Portfolio℃

8.49(8.46)

4.34(4.25)

4.17(4.10)

4.51(4.21)

4.76(4.67)

4.20(4.16)

4.31(3.77)

8
6
4
2
0
-2
-4

Scope 1+2 Warming Potential

Scope 3 Warming Potential

6.14(6.07)

2.97(2.95)

Cooling Potential

2.73(2.69)

3.29(3.16)

3.42(3.15)

Aggregated WP

Note: Global warming potential does not include reduction targets. Figures for global warming potential in consideration of
reduction targets are shown in parentheses in the label.
Source: Reproduced by permission of MSCI ESG Research LLC©2021

Copyright © 2021 Government Pension Investment Fund All rights reserved.

52

Chapter 2 Scenario Analysis on Risks and Opportunities ｜ Analysis of Real Estate Portfolio Using CVaR

Analysis of Real Estate Portfolio Using Climate Value-at-Risk
Climate Change Risk Analysis of Real Estate Portfolio
GPIF’s portfolio includes traditional assets such as equities and bonds, as well as alternative assets
such as infrastructure, private equity, and real estate. In this year’s climate-related financial disclosures,
we conducted a quantitative analysis of climate change risk for domestic real estate in which we invest
through private equity funds. With regards to the weight based on total net assets (NAV) of thedomestic real estate portfolio, industrial properties such as logistics facilities was largest at 60.8%,
followed by residential housing (15.1%), retail (12.3%), and offices (10%). For this property portfolio,
we analyzed (1) physical risks, (2) policy risks, and (3) warming potential as climate change risks(Figure 2-26)20。

Figure 2-26

20

Overview of Climate Change Risk Analysis of Real Estate Portfolio

Please refer to P.58-65 for details of the analysis methodology

Copyright © 2021 Government Pension Investment Fund All rights reserved.

53

Chapter 2 Scenario Analysis on Risks and Opportunities ｜ Analysis of Real Estate Portfolio Using CVaR

Physical Risks
The physical risk analysis predicts the building damage and the risk of heating/cooling cost
increases caused by climate change. We assessed the risks of (1) coastal flooding, (2) fluvial flooding,(3) tropical cyclones, (4) extreme heat, and (5) extreme cold, as well as comprehensive physical risks
covering all of those risks by sector. If available, information on countermeasures against physicalrisks for each property is partially included in the analysis, but in general, we use methods thatemphasize data on the location and topography of the property.
Physical risk is analyzed at each facility level based on three factors: "exposure (assessment basedon the location, size, type, and value of assets held by the company)", "hazard (probability and severityof occurrence of extreme weather events)", and "vulnerability (the propensity or predisposition of anasset to be affected)", and is assessed in six levels : "very high", "high", "medium", "low", "very low",and "no risk". The results of the analysis (Figure 2-27) indicate a high risk from (3) tropical cyclones
across all sectors. Risks from (4) extreme heat were relatively high as well, except for rental housing.
On the other hand, risks posed to the overall portfolio by (1) coastal flooding and (2) fluvial flooding,which are of particular concern in Japan, are low despite the inclusion of a very small number ofproperties with a particularly high risk of coastal and other flooding (Figure 2-28). As a result,comprehensive physical risks covering (1) to (5) are generally “low” or “very low” in each sector.

Figure 2-27 Physical Risks by Sector
Coastal Flooding

Fluvial Flooding

Tropical Cyclones

Extreme Heat

Intense Cold

Aggregate Physical
Risks

Industrial

Very Low

Low

High

High

No Risk

Low

Offices

Very Low

No Risk

High

High

No Risk

Very Low

RentalHousing

Very Low

No RiskHigh

No Risk

No Risk

Low

RetailNo Risk

No Risk

High

High

No Risk

Very Low

Others

No Risk

No Risk

High

High

No Risk

Very Low

Source: Reproduced by permission of MSCI ESG Research LLC©2021.

Copyright © 2021 Government Pension Investment Fund All rights reserved.

54

Chapter 2 Scenario Analysis on Risks and Opportunities ｜ Analysis of Real Estate Portfolio Using CVaR

Figure 2-28 Distribution of Properties by Physical Risk
Aggregate
Physical Risks
Extreme Cold
Extreme Heat
Tropical Cyclones
Fluvial Flooding
Coastal Flooding
0%10%
No Risk

20%
30%
Very Low

40%
Low

50%
60%
Medium

70%
High

80%
90%
Very High100%

Source: Reproduced by permission of MSCI ESG Research LLC©2021.

Policy Risk
In the analysis of transition pathways, we measured the carbon intensity (greenhouse gas emissions
per area) of each property and estimated the required reduction in carbon intensity by 2034 (14 years
from the end of 2020, which is the base year) needed to reach the 1.5°C, 2°C, and 3°C targets. Dataon environmental performance and the energy usage for each property is included in the analysis if
available, but in general, we use methods that uses the average data of the sector of the property ifsuch information has not been disclosed. The analysis results showed that portfolio emissions needto decline by a total of 32.8 CO2-equivalent kg per square meter over the next ten years or so in orderto achieve the 1.5°C target (Figure 2-29).

Copyright © 2021 Government Pension Investment Fund All rights reserved.

55

Chapter 2 Scenario Analysis on Risks and Opportunities ｜ Analysis of Real Estate Portfolio Using CVaR

Figure 2-29 Reduction in GHG Emissions Required to Achieve 1.5°C Scenario(kg CO2e/square meters)
50
40
30

32.8
45.8

20
10

13.0

0
Present
Carbon Intensity of Portfolio

1.5°C Scenario
Reduction Required to Achieve Targets

Source: Reproduced by permission of MSCI ESG Research LLC©2021.

Global Warming Potential and Transition Risks
Finally, this analysis also confirmed that the warming potential of the entire portfolio. By sector, theglobal warming potential was 3.8°C for retail, 2.68°C for office, 2.33°C for industrial, and 3.8°C for
residential. The overall portfolio’s warming potential was 2.78°C (Figure 2-30) which is higher than the
2°C and 1.5°C targets set by the Paris Agreement (Figure 2-30).
As described above, by analyzing climate-related financial information on the real estate portfolio
using CVaR, we were able to evaluate physical risks from natural disasters, global warming potential,
and the distance to the achievement of the 1.5°C target. However, unlike climate-related risk andopportunity analysis for traditional asset classes, there is still a great deal of room for further
development in the analysis for alternative assets. There are several reasons for this, such as data
limitations that restrict the scope of analysis for alternative assets, and the fact that results differ at theportfolio level depending on whether the weighted average is calculated using gross floor area or asset
price.

Copyright © 2021 Government Pension Investment Fund All rights reserved.

56

Chapter 2 Scenario Analysis on Risks and Opportunities ｜ Analysis of Real Estate Portfolio Using CVaR

Figure 2-30

Global Warming Potential of the Domestic Real Estate Portfolio

Source: Reproduced by permission of MSCI ESG Research LLC©2021

Copyright © 2021 Government Pension Investment Fund All rights reserved.

57

Chapter 2 Scenario Analysis on Risks and Opportunities ｜ (Appendix) CVaR: Methodology Descriptions(Appendix) CVaR: Methodology Descriptions
Characteristics of CvaR
MSCI's Climate Value-at-Risk (CVaR) is a valuation model that measures the potential impact ofclimate change on corporate and security values. CVaR measures the impact of future climate-related
costs and revenue opportunities from low-carbon technologies on the value of a company and the
securities it issues. Although there is still room for improvement in measurement methods, CVaR is anextremely innovative analytical method in that it can comprehensively assess the costs andopportunities of climate change in terms of its impact on corporate and security values based on
financial theory. The following four steps are taken to measure the impact of climate change-related
costs and revenue opportunities from low-carbon technologies on corporate equities and bonds:
Step 1: Estimate future climate change-related costs and profits
Step 2: Discount future climate change-related costs and profits to present value
Step 3: Estimate the impact on present corporate value (EV: Enterprise Value)
Step 4: Apportion the impact into impacts on equity and debt securities
CVaR has three main components: (1) Policy risk, (2) Technology opportunities, and (3) Physicalrisk21、which are combined into aggregated CVaR (Figure 2-31). (1) and (2) together are categorizedas "transition risks and opportunities," and can be evaluated as a whole with (3) physical risks. The
following sections provide details on calculating CVaR for (1), (2) and (3) above.
Figure 2-31 Composition of Aggregated CVaR and Scenario Analysis Assumptions

Source: Reproduced by permission of MSCI ESG Research LLC©2021

21"Physical Risks and Opportunities" in the last fiscal year's ESG REPORT and in the supplementary guide to the ESG REPORT
are referred to as "Physical Risks" in this fiscal year. However, as described in the main text, this is the same as last fiscal year inthat the positive and negative impacts on corporate earnings are netted.

Copyright © 2021 Government Pension Investment Fund All rights reserved.

58

Chapter 2 Scenario Analysis on Risks and Opportunities ｜ (Appendix) CVaR: Methodology Descriptions

Climate Change Policy CvaR
Policy CVaR estimates a company’s costs associated with reaching emissions reduction targets
under future climate change policies through the end of the 21st century. The Policy CVaR model
analyzes the downside risk of climate policy to a company and its securities by estimating the future
cost to that company of reducing emissions required to comply with these policies.
First, Policy CVaR analyzes the impact of national emissions reduction targets (Nationally
Determined Contributions, commonly called NDCs) submitted under the Paris Agreement and recent
national climate change-related regulations. These targets and regulations include Scope 1 GHG
emissions, which are directly emitted from business activities, and Scopes 2 and 3 GHG emissions,which are indirectly emitted. The Scope 1 emissions analysis involves setting GHG emissions
reduction targets at the national and sector level based on the country’s NDC, and assigning emissions
reduction requirements to companies operating in those sectors. The allocation is based on the "fairshare" principle – i.e. each company is allocated a portion of the total required country and sector
Scope 1 emission reduction according to the company’s level of emissions. In other words, companies
with a greater percentage of total emissions levels in their sector are required to reduce GHG
emissions by a proportionally higher percentage.
In addition, company asset data is used to assign sector emission reduction targets to eachcompany's facility level. This allows us to calculate emissions reduction requirements for facilities
owned and operated by companies worldwide. By multiplying each company's demand for emission
reductions by the future carbon price, we calculate the climate change policy cost that each company
would have to pay to achieve its emission reduction target (reduction requirement) (Figure 2-32).
A portion of this climate change policy cost is modeled to pass through to customers and suppliers
within a company's value chain as discussed below. Incidentally, the carbon price is determined using
the integrated assessment model and depends on the selected policy scenario (1.5℃, 2℃, 3℃).
Figure 2-32

Image of Scope-1 Emissions Analytical Models for Policy CVaR

Source: Reproduced by permission of MSCI ESG Research LLC©2021

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Chapter 2 Scenario Analysis on Risks and Opportunities ｜ (Appendix) CVaR: Methodology Descriptions

The scope 2 emissions analysis calculates the costs incurred by power producers that are passed
on to consumers. The transition to a low-carbon economy requires switching electricity sources fromcoal and natural gas to lower carbon or GHG emissions-free sources. However, this transition canbe costly. For electric power companies, phasing out fossil-fuel-based thermal power plants andshifting to low-carbon power sources leads to increased capital expenditures. These include
decommissioning aging power plants, introducing new technologies, and upgrading power grids toensure supply from new power sources. Electric power companies do not bear all these costs – someare passed on to electricity consumers. The potential cost associated with electricity consumption foreach transition scenario is calculated from data on electricity production and consumption generated
by the Integrated Assessment Model and estimates of cost passthrough rates to consumers. For
example, in regions where the electricity market is fully liberalized, power producers are expected topass on 85% of their costs to end consumers. We assume a pass-through rate of 50% for partiallyliberalized regions and 25% for fully regulated regions.
Figure 2-33

Pass through rates of Scope 2 Emissions from the Policy CVaR

Fully liberalized
market, pass-throughrate of 85%

Partially liberalized
market, pass-throughrate of 50%

Fully regulated market,
pass-through rate of25%

Source: Reproduced by permission of MSCI ESG Research LLC©2021

The Scope 3 emissions analysis examines each company’s potential carbon-related costs within
the value chain, as determined by the size of the company's Scope 3 emissions. By combining Scope
3 carbon-related costs with assumed burden rates, we estimate the impact on the costs thatcompanies will incur from GHG emissions occurring in the value chain. The assumed burden rate
represents the level of costs that a company may bear depending on the amount of GHGs emitted
from the value chain, which stem from 15 upstream and downstream categories as defined by the
GHG protocol.22 The CVaR analyses also distinguish between upstream and downstream categories.
For example, by analyzing upstream GHG emissions, we assess the risk that companies' procurement
22

International standards for the calculation and reporting of greenhouse gas emissions. The World Resources Institute and
WBCSD operate in cooperation with governments, companies, and NGOs, and publicize the definitions of Scopes 1, 2, and 3. GHG
Protocol https://ghgprotocol.org/

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Chapter 2 Scenario Analysis on Risks and Opportunities ｜ (Appendix) CVaR: Methodology Descriptions

costs for materials and other items will increase. The downstream GHG emissions analysis, on theother hand, examines the risk that a company's market share will be lost due to changes in demand.
By evaluating upstream and downstream GHG emissions independently, we calculate a company's"value chain (scope 3) CVaR" and included this in the company's policy risk evaluation. The assumed
burden rates applied to distinguish the upstream and downstream impacts of the value chain are as
follows (Figure 2-34).
Scope 3 Upstream Burden Rate: Upstream Burden Rate represents the percentage of costs thatare passed through from companies upstream in the value chain to companies being evaluated. If
countries implement climate change policies aimed at reducing GHG emissions, companies may needto shift to less-emitting production technologies and product development, and if this is not possible,
they may face the risk of paying fines and taxes. This could lead to increased capital and operating
expenditures to comply with climate change policies, which in turn could increase a company's
marginal cost of production. Competitiveness in a company's product markets and how efficiently acompany can internalize its costs affect analysis of how much the company can pass on its climate
costs to its customers.
Scope 3 Downstream Burden Rate: Downstream Burden Rate is the percentage of costs that acompany must absorb as market demand for its products has been affected. In a low carbon economy
transition scenario, it is anticipated that the implementation of regulations aimed at reducing GHG
emissions will result in weak market demand for high GHG emission products and a shift in market
demand from low carbon products to zero emission products. This means that demand for its products
may decline sharply in a particular sector. The assumed burden ratio varies depending on the priceelasticity of demand and the substitutability of the product.
Figure 2-34

Examples of Scope 3 Emissions burden rates in the Policy CVaR

Source: Reproduced by permission of MSCI ESG Research LLC©2021

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Chapter 2 Scenario Analysis on Risks and Opportunities ｜ (Appendix) CVaR: Methodology Descriptions

Measures Against Double Counting
Given that GHG emissions from Scope 3 are an important factor in institutional investors' climate
risk management, we need to consider the issue of double counting of GHG emissions. Double
counting for GHG emissions refers to counting the same emissions more than once. For example,
the Scope 1 GHG emissions for one company can be counted as another company’s Scope 3
emissions. This occurs primarily when a company's comprehensive carbon footprint (scopes 1, 2,
and 3) is aggregated within its investment portfolio. Even if companies in the same value chain
calculate and report the same emissions, the reasons for double counting differ. For example, oil
mining companies should report GHG emissions generated when fuel products sold are burned,
while car companies should include emissions from the combustion of the same fuel in reporting
GHG emissions generated when vehicles sold are used. Some fossil fuel refining companies also
perform similar calculations and reports. In most cases, model estimates are available without
problems, but the inclusion of double counting may be a barrier. We recognize that it is not possible
to completely eliminate duplication from scope 3 emissions even in CVaR analyses. The mostdifficult issue is that individual companies may have significantly different levels of double counting.
Despite these barriers of double counting, pressure is increasing to fully understand the upstream
and downstream climate risks of the investment portfolio. In CVaR analyses, we use deduplication
factors to reduce the impact of double counting. With regard to the calculation of the deduplication
factors, at first, in order to determine the double counting at the macro level, we calculated the total
GHG emissions of the largest group of enterprises (10,000 or more enterprises) with both Scope 1
GHG emissions and Scope 3 GHG emissions data points for each scope and determined theirrelationship. Assuming that the GHG emissions for these two data sets are within a limited closed
environment, the relationship between the data points can be regarded as an approximation of the
double counting that occurred. All Scope 3 emissions at any point in time are considered to havebeen Scope 1 emissions by other companies. CVaR models calculate deduplication factors fromthese relationships and apply them to the analyses.
Figure 2-35

Estimated Burden Rate of Scope 3 Emissions from the Climate-Change Policy-Risk CVaR
Number of companies

10,881

Sum of Scope 1 total emissions

15,028 MtCO2 / year

Sum of Scope 3 total emissions

68,080 MtCO2 / year

Deduplication Factor～0.22

Note: This deduplication factor is illustrative and may not be the actual factor used to compute CVaR.
Source: Reproduced by permission of MSCI ESG Research LLC©2021

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Chapter 2 Scenario Analysis on Risks and Opportunities ｜ (Appendix) CVaR: Methodology Descriptions

Low-carbon Technology Opportunity CvaR
The Low Carbon Technology Opportunity CVaR calculates the profits a company generates in the
future from low carbon technologies based on an assessment of the status of companies' acquisitionsof low carbon technology patents and current low carbon technology-related revenues. This patent
analysis covers approximately 100 million corporate patent data from more than 70 patent authorities
worldwide. Assessing the quality of low-carbon patents classified in more than 400 groups and usingthat assessment as an alternative indicator of an enterprise's innovative capacity, this model aims toanalyze which companies are likely to generate profits and gain growth opportunities from low-carbon
technologies when policies related to climate change are implemented globally at the 3°C, 2°C, or
1.5°C levels. This low-carbon technological opportunity CVaR works to boost corporate value andsecurity value as a factor in contrast to the impact of the costs of climate change policies (the cost of
reducing carbon emissions) that arise as a result of the transition to a low-carbon society.
Because not all patents have equal value, the number of patents alone cannot predict a company's
innovative capabilities or future market growth potential. The Low-Carbon Technology Opportunities
CVaR calculates patent scores based on four statistical measures established in academic literatureand by practitioners (Figure 2-36).
Profits from each company's environmental technologies are calculated by allocating futureenvironmental revenues for each sector by the share of patent scores within the sector, and multiplying
the allocated revenues by the sector average profit margin. At this time, we assume that the size ofthe sector's future revenues from environmental technologies is equal to the sector-level climatechange policy costs (the cost of reducing carbon emissions) calculated under the Climate Change
Policy Risk CVaR. This is because we assume that if the cost of reducing carbon emissions is incurred,
the potential revenues from selling low-carbon technologies are equal.
Figure 2-36

Four statistical measures in the calculation of patent scores

Forward

The number of references to the patent in other patent applications. This is a measure of the widespreadcitations

acceptance of the value or significance of a patent. If a patent is frequently cited by other patent applications,the patents frequently cited are likely to be fundamental technologies or important technology patents.

Backward

The number of patents of others cited at the time of filing of the patent application. A larger number of backward

citationscitations reduces the patent value because it is likely to be older and based on more established technology.

Market

The total GDP of the country in which the patent to be evaluated was filed. The higher the market coverage,

Coverage

the higher the patent score.

CPC

Number of tagged CPC patent groups. Cooperative Patent Classification (CPC) evaluates the relevance ofcoveragepatents to patent groups based on the International Patent Classification. The more groups tagged in thisrelevance assessment, the higher the patent score.

Source: Reproduced by permission of MSCI ESG Research LLC©2021

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Chapter 2 Scenario Analysis on Risks and Opportunities ｜ (Appendix) CVaR: Methodology Descriptions

Physical Risks CvaR
The Physical Risks CVaR analyzes the financial impacts of acute and chronic extreme weather thatis expected to occur over the next 15 years, based on abnormal weather patterns observed over thelast 40 years. The impact of physical risk is calculated at the region, sector, and enterprise levels.
The Physical Risk CVaR estimates the physical risk at the company’s facility level under selectedscenario conditions (average or aggressive scenario) for three factors: "exposure (assessment basedon the location, size, type, and value of the enterprise's assets)", "hazards (probabilities and severityof abnormal weather events)", and "vulnerability (the propensity or predisposition of an asset to beaffected)".
The physical risk CVaR is currently classified into two types of risk (chronic risk and acute risk). The
following eight types of extreme weather events are the scope of the Physical Risk CVaR Analysis,
with the addition of the Fluvial Flooding in this fiscal year (Fig. 2-37).
New natural disaster: Fluvial Flooding
The regions affected by flooding are usually relatively limited on coastlines, but those regions are
exposed to potential significant risks because of the concentration of economic activity and assets inthese regions. The Physical Risks CVaR assesses the impact of river flooding and coastal flooding on
investment portfolios based on an extensive hazard data set, data on regional flood control, andcharacteristics of sector vulnerabilities. Specifically, we estimate the full range of impacts that could
have a financial impact on the business activities, including the costs of repairing or replacing affectedassets and restoring operations, as well as the impact of disruptions in operations.
Figure 2-37

Natural Disasters Subject to Analysis of Physical Risks CVaR

Source: Reproduced by permission of MSCI ESG Research LLC©2021

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Chapter 2 Scenario Analysis on Risks and Opportunities ｜ (Appendix) CVaR: Methodology Descriptions

Financial Models that Reflect Climate Change Risks and Opportunities in Security Values
As noted earlier, CVaR estimates follow four steps. In Step 1, we estimate future climate-related
costs and profits, and the analyses will take a different approach over the next 15 years and beyond.
For the first 15 years, we estimate in detail climate change policy risks, profits from low carbon
technologies, business losses and facility damage due to extreme weather. From the 16th year onward,
we estimate costs through 2080 using the model.
The model estimates that climate change policy costs and profits from low-carbon technologies will
peak in the next 25 years and then decrease linearly to 0 by 2080 (Figure 2-38). On the other hand,
actual climate change, such as global warming, is expected to have a longer-term impact. For physicalrisks, the annual growth rate is set at 3%, and it is assumed that this will continue until 2080.
Step 2 is to discount costs and profits calculated under Step 1 using the weighted-average cost ofcapital (WACC). The model assumes that the discount rate used for the first year is equal to acompany's WACC and over time the rate converges to the sector average WACC by 2080.
Step 3 calculates CVaR of the company, which is the present value of the costs and profits calculated
in previous step divided by the enterprise value (EV:). The value implies the impact of climate changerelated costs and profits on enterprise value23.
Finally, Step 4 divides the company-level CVaR into its equity and debt securities. In this step, CVaR
for debt securities is determined by the Merton model to estimate the change in the probability of thecompany’s default resulting from climate-change-related costs and profits (Figure 2-39). Equity CVaR
is then calculated using the company’s aggregated CVaR and CVaR for debt securities.
Figure 2-38 Estimation Methods and Image of Climate Change

Figure 2-39 Image of the Merton Model

Policy Costs and Low-Carbon Technologies Profits

Source: Reproduced by permission of MSCI ESG Research
LLC©2021

Source: Reproduced by permission of MSCI ESG Research
LLC©2021

23

It is assumed that the current enterprise value does not incorporate the climate change-related costs and benefits that are being
analyzed.

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Chapter3 Analysis of Inter-Industry Transfer of Transition Risks and Opportunities

Chapter 3:

Analysis of Inter-Industry Transfer ofTransition Risks and Opportunities
Analysis Purpose and Process
The analyses presented in previous sections of this report adopt a bottom-up approach to explore
the impact of climate risks on GPIF’s portfolio. This approach begins by measuring and analyzing thecarbon footprint, CVaR, and other factors of individual companies and securities, then aggregating theresults across all of GPIF’s equity and bond holdings.
This section departs from the perspective of the direct impact on GPIF’s portfolio to examine how
climate change-related risks and opportunities will shift between industries over the long term to 2030
and 2050, according to an analysis performed by Astamuse. Specifically, this analysis uses data on
industry-level required greenhouse gas (GHG) reductions, expected GHG reduction contributions ofindividual decarbonization technologies, and projections for the rate at which they will be implemented
in society. As opposed to the CVaR analysis, which assumes that the transfer of risks and opportunities
occur within the same industry, the purpose of this analysis is to focus more on the opportunities
inherent in decarbonization and appraise different GHG reduction technologies by understanding thetransfer of risks and opportunities that occur between industries. We reveal the potential for certain
industries to boost growth by turning risks for other industries into opportunities for themselves.
Figure 3-1

Inter-Industry Risk and Opportunity Transfer Visualization Process

Step1: Risk Analysis
Estimate Required GHG reductions by industry for 2030/2050.
＊The Sustainable Development Scenario (SDS) developed by the International Energy Agency (IEA) is used toestimate required GHG reduction rates for 2030/2050 for each industry.

Step:2 Opportunity Analysis
Identify technologies with the potential to contribute to GHG reductions by industry andestimate GHG reduction contributions (= current GHG emissions × GHG reduction rate ×
implementation rate) in 2030/2050 for individual decarbonization technologies.
Step:3 Risk and Opportunity Transfer Visualization
Net GHG reduction opportunities = GHG reduction contributions – required GHG reductions＊GHG reduction contributions = GHG reduction potential x adjustment factor
The adjustment factor is a value that balances total required GHG reductions for all industries with total GHG reduction contributions

Source: Prepared by GPIF based on Astamuse analysis

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Chapter3 Analysis of Inter-Industry Transfer of Transition Risks and Opportunities

Risk Analysis
The first step in this analysis is to identify the emissions reductions required in each industry by2030 and 2050 to achieve the target of limiting global warming to “well below 2, preferably to 1.5
degrees Celsius, compared to pre-industrial levels” (Step 1 of Figure 1) as agreed in the Paris
Agreement. Here, we use the Sustainable Development Scenario (SDS) compiled by the International
Energy Agency (IEA) to calculate the emissions reductions required to achieve the goals of the Paris
Agreement. The SDS outlines CO2 emission reduction paths for a number of different industries from2019 to 2070 that would meet these goals (Figure 3-2). Based on these paths, we derive the GHG
reduction targets for each industry for 2030 and 2050 as a percentage of 2019 emissions. The
industries included in the IEA analysis are “Power,” “Industry,” “Transportation,” “Buildings,”“Agriculture,” and “Other Energy Transformation,” which Astamuse reorganizes into 13 different
industries based on decarbonizing/carbon reducing technologies for the purposes of this analysis(Figure 3-3).
For each of these 13 industries, we aggregate GHG emissions data based on public information for
the top 40 companies in the world by revenue. Emissions for companies with no or partial GHG
disclosures are estimated based on financial data and emissions information disclosed by similar
companies. The total emissions for the top 40 companies in the industry are then divided by the total
revenue share of these companies as a percentage of total industry revenue to derive the estimatedGHG emissions of the entire industry. The total GHG emissions for each industry in 2020 ((a)), GHG
reduction target rates for 2030 and 2050 ((b), (c)) and required reduction amounts ((a) x (b), (a) x (c))
are shown in Figure 3-4. Additionally, we calculate emissions generated for each segment in the supply
chain for each industry. Using the GHG Protocol24 definition of Scope 1 to Scope 3 emissions andCategories 1 to 15, which separate the supply chain into upstream portions (purchased goods/services,etc.) and downstream portions (processing, usage and disposal of sold goods, etc.), we break down
the supply chain into four broad segments: “raw materials” (Scope 3 categories 1-3 and 5-8),“production” (Scope 1, Scope 2), “use/disposal” (Scope 3 categories 10-15) and “transportation”(Scope 3 categories 4 and 9) (Figure 3-5).
The results of the above analysis indicate that “Construction, Civil Engineering and ConstructionRelated Products”, “Energy,” and “Metals, Mining and Paper Products” are predicted to have thehighest level of required GHG emission reductions (i.e. high risk). Looking at the supply chain of theConstruction, Civil Engineering and Construction-Related Products industry, we can see that most ofemissions are generated in the “raw materials” (i.e. cement and steel-related GHG emissions) and“use/disposal” (i.e. GHG emitted when buildings are used) segments.

24

GHG emission calculation and reporting standards developed by the GHG Protocol initiative

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Chapter3 Analysis of Inter-Industry Transfer of Transition Risks and Opportunities

Figure 3-2

CO2 Emission Trends by Industry from 2019 to 2070 Under the SDS

Source: Prepared by GPIF based on IEA analysis

Figure 3-3

IEA-Calculated 2030/50 GHG Reduction Target Rates (2019 base) Under the SDS and ProjectIndustry Classification

Source: Prepared by GPIF based on Astamuse analysis

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Chapter3 Analysis of Inter-Industry Transfer of Transition Risks and Opportunities

Figure 3-4

2020 Total GHG Emissions and GHG Reduction Target Rates/Required Reduction

Volumes for 2030/50
2030

Total em issions (as of 2020)

Total GHG
Industry

2050

Reduction Required Reduction Required

emissionstargetreductions

targetreductions

(a)

(b)

(a x b)(c)(a x c)bn. tons%

bn. tons%

bn. tons

Energy

8.30

46%

3.8

96%

7.97

Social Infrastructure

0.56

46%

0.3

96%

0.54

Chemicals, etc.

4.83

11%

0.5

61%

2.95

Metals, Mining / Paper Products

5.86

11%

0.6

61%

3.57

Construction, Civil Engineering andConstruction-Related Products

13.55

11%

1.5

61%

8.27

Electrical Equipment

0.13

11%

0.0

61%

0.08

Machinery

1.03

11%

0.1

61%

0.63

Automobiles

1.50

11%

0.2

61%

0.92

Durable Consumer Goods

0.80

11%

0.1

61%

0.49

Transportation

1.51

13%

0.2

63%

0.95

Agriculture, Forestry and Fisheries

3.47

40%

1.4

80%

2.77

Food

1.75

11%

0.2

61%

1.07

Telecommunications

2.01

17%

0.3

67%

Total

45.29

9.2

1.34
31.54

Source: Prepared by GPIF based on Astamuse analysis

Figure 3-5

Supply Chain Segment Emissions by Industry
Total

Industry

Supply Chainemissions

Raw Materials

Production

Use/Disposal

Transportation

Subtotal

bn. tons

bn. tons

bn. tons

bn. tons

bn. tons

Energy

0.36

1.67

6.05

0.22

8.30

Social Infrastructure

0.02

0.47

0.07

0.00

0.56

Chemicals, etc.

1.67

1.84

1.18

0.14

4.83

Metals, Mining / Paper Products

0.24

4.28

1.22

0.11

5.86

Construction, Civil Engineering andConstruction-Related Products

3.66

2.58

6.78

0.54

13.55

Electrical Equipment

0.02

0.02

0.08

0.00

0.13

Machinery

0.01

0.01

1.01

0.00

1.03

Automobiles

0.33

0.05

1.09

0.03

1.50

Durable Consumer Goods

0.20

0.18

0.40

0.01

0.80

Transportation

0.38

0.85

0.00

0.27

1.51

Agriculture, Forestry and Fisheries

1.53

1.41

0.27

0.26

3.47

Food

0.97

0.36

0.12

0.30

1.75

Telecommunications

0.36

0.49

1.11

0.04

Total

2.01

45.29

Source: Prepared by GPIF based on Astamuse analysis

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Chapter3 Analysis of Inter-Industry Transfer of Transition Risks and Opportunities

Opportunities Analysis
Next, we identified the technologies that contribute to the reduction of GHG, estimated emissions
reduction rates for each technology compared with existing technologies, and forecast theimplementation of each in 2030 and 2050. We then use these figures to calculate the GHG reduction
contributions (opportunities) of individual technology fields (Step 2 of Figure 3-1). In this step,
Astamuse utilized their proprietary database, which includes data on various technologies, research
themes, research papers and new business enterprises, along with technology analyst insight tocomprehensively identify 40 technology fields likely to contribute to greenhouse gas reduction (Figure3-6). This is done by using machine learning to perform a cluster analysis of 10s of millions ofinnovation-producing ideas (new products, businesses and technologies) and experts withsophisticated technical knowledge to identify where innovators and innovation capital is flowing.
Figure 3-6

40 Technology Fields Contributing to GHG Reduction
Industry
EnergyTechnology Fields
Bioenergy (generation, fuel)Hydropower energy, small and medium hydroelectric power generation
Smart grid / smart city
Hydrogen/ammonia power generation
Hydrogen systems and infrastructure
Green hydrogen
Hydrogen storage/transport
Photovoltaic power generation, solar batteries, solar thermal power generation
Wind Power
Marine energy
High-efficiency thermal power generation (coal, natural gas, methane capture from oil fields)
High-efficiency thermal power generation
High-efficiency LNG power generation
Geothermal power
Nuclear power, nuclear fusion

SocialInfrastructure

Underground and submarine carbon storage (phytoplankton solidification,
upwelling/sinking current promotion (synthetic submarine mountain ranges), etc.)
Underground carbon storage
Submarine carbon storage
Underground injection, submarine storage
Waste and sewage sludge treatment (energy capture from hydrogen/methane/BFC)
Power generation from anaerobic digestion of biomass waste
Usage of waste materials in production of biomass

Metal, Mining,and Paper
Products

Low-carbon steelmaking
Ferro coke
Reduced ironHydrogen direct reduction steelmaking

Construction, Civil
Engineering andConstruction-Related
Products

Energy-efficient housing (insulation, HEMS/BEMS/ZEH/ZEB)

Continued on following page

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Chapter3 Analysis of Inter-Industry Transfer of Transition Risks and Opportunities

Figure 3-6

40 Technology Fields Contributing to GHG Reduction
Industry
Chemicals

Technology Fields
Bio materials (concrete/biomass-based plastics)
Materials capable of CO2 absorption/adherence/separation/condensation/long-term storage(membranes, filters, polymers, chemicals) (including DAC, carbon-absorbing concrete)
CCS from high emission sources
DAC
Carbon absorbing concrete
Fuel cells
Batteries
Fully solid batteries
Next-generation capacitors
Air cells
Reduction of CFC emissions, green refrigerants
Carbon reuse (usage of captured CO2 in production, fuel, concrete, etc.)
Methanol production
Polymer production
Concrete/cement production

Electricalequipment

Electrification of industrial equipment (heating/drying, etc.), energy management (FEMS, etc.)
Industrial heat pumps
Sensing networks
Energy harvesting
Reducing losses in power transmission

Machinery

Electric drive, power supply equipment (ships/aircraft (incl. drone-based transport),
farm equipment, construction equipment) excl. automobiles
Hybrid aircraft
Electric ships
Electric farm equipment/construction equipment
Ammonia drive (automobiles/ships)
Heat storage, heat transport technology, heat pumps

Automobiles

Hydrogen/fuel cell vehicles
Clean energy vehicles (engine efficiency, usage reduction through smaller vehicles, lightweight chassis)
Electric Vehicles
Hybrid automobiles
Electric vehicles (BEV)

DurableConsumer
Goods

Transportation

Energy-efficient home appliances and lighting
Power semiconductors
Auto-control of appliances/lighting using AI
Smart transport, MaaS (ship operation/docking efficiency, sophistication of air traffic control systems
using satellites, etc.)
Modal shift (public transport, community busses, on-demand transport, shift from trucking to rail/ship)

Agriculture,
Forestry and
Fisheries

Advanced uses of wood (construction material, charcoal, modified lignin, cellulose nanofibers, etc.),
substitution of plastic/metal materials with wood/paper
Smart agriculture (fertilizer/water absorption/feeding efficiency, improvements in feed stock efficiency,
reduction in methane emissions, use of CO2 in horticulture/greenhouses
Cultured meat/meat substitutes/dairy substitutes (reducing livestock methane)
Afforestation, desert greening (incl. breed improvement/elite trees, etc.)

Food

Reducing byproducts and food waste in manufacture of food products
Innovative extension of storage periods
Food waste utilization

Telecommunications

Power semiconductors

Source: Prepared by GPIF based on Astamuse analysis

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Chapter3 Analysis of Inter-Industry Transfer of Transition Risks and Opportunities

Next, we project the GHG reduction rate and market implementation rate in 2030 and 2050 for these40 technology fields. For the GHG reduction rate, Astamuse analysts review a broad array of reports
and publications by governments, international institutions and think tanks to identify the current
technologies that can be substituted by GHG reducing technologies, and estimate the degree to which
they can be substituted by 2030 and 2050. Taking the bioenergy field as an example, the CO2
reduction rate for liquid biofuels used in transportation is around 55% as compared to gasoline
according to the Japanese government’s Energy Supply Structure Enhancement Act, so gasoline is
specified as the replaced technology for bioenergy, and the GHG reduction rate is set at 55% for 2030
and 2050.
For the implementation rate estimate, Astamuse analysts first perform a qualitative assessment of
key technologies based on academic papers and other leading research to identify hurdles to thewidespread adoption of each technology field and the milestone technologies vital to overcoming theseissues. Based on who is the main party involved in developing the technology (business and/or
academia), the current state of research and development and other factors, analysts then select themost appropriate data source (patents, research papers or grants) to use in determining the current
implementation phase (R&D, Verification, Introduction, Spread, or Expansion) for each milestone
technology. Then, using this data source, analysts study technological development trends over the
past 20 years to estimate the life cycle and current implementation phase for each technology. In the
bioenergy example, production of biofuels based on inedible and organic waste and algae-based fuelsis expected to grow in the future, and as such, 1) cellulose-based fuels, 2) waste product biomass
fuels and 3) algae-based fuels are designated as milestone technologies. For each of these, research
papers are used to determine the future implementation phase and therefore the implementation rates
for each milestone technology in 2030 and 2050 (Figure 3-7).

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Chapter3 Analysis of Inter-Industry Transfer of Transition Risks and Opportunities

Figure 3-7

GHG Reduction Rates and Implementation Rates for Bioenergy Milestone Technologies

Source: Prepared by GPIF based on Astamuse analysis

Next, Astamuse analysts evaluate each technology field based on replaced technologies and otherfactors. For each industry’s estimated supply chain segment emissions shown in Figure 3-5, they
identify which technology can contribute to GHG reductions in which supply chain segment of which
industry, and by how much. These values are then aggregated for each technology across industries
to obtain the total emissions for all target segments to which the technology can contribute to GHG
reductions. In the case of bioenergy, gasoline is identified as the replaced technology. As a result,bioenergy is anticipated to contribute to the manufacturing and transportation segments across a
broad swath of industries, resulting in an estimated target segment emission total of 11.48 billion tons
(Figure 3-8).
Multiplying total target segment GHG emissions by the GHG reduction rate and implementation rate
for each technology field as derived above yields the potential GHG reduction contribution thereof.
Figure 3-10 gives the 10 technological fields with the highest potential GHG reduction contributions.
The energy field in particular has many technologies that have significant potential to contribute tolower greenhouse gases, owing to the high emissions that occur along the supply chains in theindustries for which these technologies can contribute, among other factors. One somewhat
unexpected finding is that “hydropower energy and small and medium hydroelectric power generation”
is shown to have the largest opportunity out of all technologies. On a global level, however, theCopyright © 2021 Government Pension Investment Fund All rights reserved.

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Chapter3 Analysis of Inter-Industry Transfer of Transition Risks and Opportunities

technological potential of hydroelectric power as a whole is estimated to be approximately 15,000 TWh,or about 65% of global power consumption (approx. 23,000 TWh)25. Additionally, looking at global
demand trends, countries that have rivers with large watersheds such as China are expected to
substantially expand hydroelectric power generation. Furthermore, as fossil fuel-based power
decreases, enhanced hydropower generation management made possible by improvements inweather, precipitation and flow forecasting will help maximize dam performance for existing and future
stock, thereby dramatically contributing to reduced emissions.

Figure 3-8

GHG Emission Reduction Target Sectors (Bioenergy)
Industry

Supply Chain
Raw materials

Production Use/Disposal Transportation

Subtotal

Construction, Civil Engineering and ConstructionRelated Products

0

3.87

0

0.21

4.08

Energy

0

1.59

0

0.18

1.76

Metals, Mining / Paper Products

0

2.14

0

0.09

2.23

Chemicals, etc.

0

0.92

0

0.11

1.03

Agriculture, Forestry and Fisheries

0

0.70

0

0.21

0.91

Telecommunications

0

0

0

0

0

Food

0

0.18

0

0.24

0.42

Transportation

0

0.43

0

0.22

0.64

Automobiles

0

0.03

0

0.02

0.05

Machinery

0

0.01

0

0.00

0.01

Durable Consumer Goods

0

0.09

0

0.01

0.10

Social Infrastructure

0

0.24

0

0

0.24

Electrical Equipment

0

0.01

0

0

0.01

Total

11.48

Note: Values are in billions of tons.
Source: Prepared by GPIF based on Astamuse analysis

25

Technology Roadmap: Hydropower (IEA) https://iea.blob.core.windows.net/assets/8b1f76a8-f48a-46bf-ab5ef91695011a85/2012_Hydropower_Roadmap.pdf

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Chapter3 Analysis of Inter-Industry Transfer of Transition Risks and Opportunities

Figure 3-9

Top 10 Technology Fields With Largest GHG Reduction Potential
Present

Industries

Technology Fields

2030

GHG
Emissionsof Target
Segment(a)

GHG
Reduction
Rate (b)bn. tons

%

2050

GHG
GHG
GHG
Implementation
Reduction
Implementation Reduction
Reduction
Rate (c)Contributions
Rate (e)Contributions
Rate (d)(a × b × c)(a × d × e)%bn. tons%%

bn. tons

EnergyHydropower energy, small and medium hydroelectric power
generation

10.02

100%

65%

6.51

100%

65%

6.51

Chemicals

CCS from large emitters

8.00

90%

5%

0.36

90%

85%

6.12

EnergyMarine energy

6.64

100%

15%

1.00

100%

85%

5.65

EnergySolar power generation, solar cells, solar thermal power
generation

6.64

99%

50%

3.29

99%

85%

5.59

EnergyBioenergy (power generation, fuel)

11.48

55%

15%

0.95

55%

85%

5.37

Telecommunications

Power semiconductors

7.27

71%

50%

2.58

71%

100%

5.16

Chemicals

Methanol production

8.83

65%

15%

0.86

65%

85%

4.88
4.80

Social Infrastructure

Power generation by anaerobic digestion of waste biomass

6.64

15%

15%

0.15

85%

85%

EnergyGreen hydrogen

8.43

100%

0%

0.00

100%

50%

4.21

EnergyHydrogen/ammonia power generation

10.02

79%

5%

0.40

79%

50%

3.96

Source: Prepared by GPIF based on Astamuse analysis

Inter-Industry Risk and Opportunity Shift Potential
The last step in the process is to reveal how risks and opportunities may potentially shift between
industries. To do this, we aggregate the GHG reduction potential of all technology fields by industry,then multiply each by an adjustment factor to obtain each industry’s GHG reduction potential. From
this, we subtract the required GHG emission reductions for that industry. The adjustment factor is
included in the calculation to reflect the fact that in reality, amongst the many competing GHG reduction
technologies, those that are most effective and efficient at cutting emissions will be used most widely.
As a result, total GHG reduction contributions far surpassing total required GHG reductions is not avery realistic outcome. An adjustment factor is therefore applied to balance total required GHG
reductions and total potential GHG reduction contributions. In other words, GHG reduction
contributions is defined as potential GHG reduction contributions multiplied by the adjustment factor.26
If GHG reduction contributions are larger than required reductions, the industry has a “netopportunity.” Conversely, if required reductions outweigh potential contributions, the industry isdeemed to have a “net risk.” (Figure 3-1 Step 3, Figure 3-10). The risk and opportunity profile for eachindustry in 2030 and 2050 as determined by the above process is shown in Figure 3-11. In 2050,
opportunities will outweigh risks in seven industries, including energy, chemicals, and social
infrastructure, while risks will outweigh opportunities in six industries, including construction, civil
26

This is a revision made to the model after the publication of the ESG Report 2020. While the term “GHG reduction contribution” isused in the ESG Report, the definition is different than in this report as it does not include the adjustment factor.

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Chapter3 Analysis of Inter-Industry Transfer of Transition Risks and Opportunities

engineering, and construction-related products. The energy industry, which is considered to have thegreatest net opportunities in 2030 and 2050, is also the industry required to reduce GHG emissions
the most in both target years. On the other hand, this industry is expected to contribute greatly todecarbonization in other industries through a wide range of technologies, including hydrogen systems
and infrastructure, hydropower energy and small and medium hydroelectric power generation(proliferation of small and medium hydroelectric power generation, optimization of weather forecastingand power generation, and improvement of flow control), and solar power generation and solar cells(weight reduction and cost reduction through the use of new materials). These GHG reduction
contributions are expected to far exceed the level of reductions required for the industry.
For chemicals, although decarbonization opportunities in 2030 are not as great, from 2030 to 2050,
technological developments in Carbon Capture and Storage (CCS) from large-scale sources of CO2
emissions and Direct Air Capture (DAC) are forecast to accelerate, and, as costs come down andefficiency improves, these technologies are expected to be more widely adopted. In the social
infrastructure industry, progress in the utilization of useful biogases through the treatment of waste
and sewage sludge and the implementation of underground and submarine carbon storage will leadthe reduction of GHG emissions in a variety of different sectors, including agriculture, forestry andfisheries.
On the other hand, the construction, civil engineering, and construction-related products industry is
expected to have negative net opportunities in both 2030 and 2050. While the required GHG reductionin this sector is just as high as that of the energy sector, unlike that and other industries, thetechnologies in construction and civil engineering, such as low-energy housing, are seen as making
limited GHG reduction contributions to other industries.

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Chapter3 Analysis of Inter-Industry Transfer of Transition Risks and Opportunities

Figure 3-10

Analysis of GHG Reduction Contributions and Required Reductions by Industry

Source: Prepared by GPIF based on Astamuse analysis

Figure 3-11

Transfer of Risks and Opportunities by Industry in 2030 and 2050
2030

Industries

Reduction
Contributions(a)Required
Reduction(b)bn. tons

bn. tons

2050

Volume (a - b)

(Reference)
Monetary Amount

Reduction
Contributions(a)Required
Reduction(b)

Volume (a - b)

(Reference)
Monetary Amountbn. tons

US $bn.

bn. tons

bn. tons

bn. tons

US $bn.

GHG Reduction Net Opportunity

GHG Reduction Net Opportunity

Energy

4.8

3.8

1.0

108.1

13.5

8.0

5.5

998.4

Social Infrastructure

0.5

0.3

0.2

23.4

3.9

0.5

3.4

606.1

Chemicals, etc.

0.7

0.5

0.1

13.4

4.7

2.9

1.8

318.6

Electrical Equipment

0.7

0.0

0.7

75.5

1.7

0.1

1.6

284.4

Machinery

0.2

0.1

0.1

11.7

1.6

0.6

1.0

184.1

Automobiles

0.7

0.2

0.5

51.2

1.8

0.9

0.9

162.1

Telecommunications

0.8

0.3

0.4

45.2

1.6

1.3

0.3

51.9

Durable Consumer Goods

0.2

0.1

0.1

9.8

0.3

0.5

-0.2

-38.2

Transportation

0.1

0.2

-0.1

-13.1

0.6

1.0

-0.3

-58.9

Food

0.0

0.2

-0.2

-19.0

0.1

1.1

-1.0

-171.8Agriculture, Forestry and Fisheri

0.1

1.4

-1.3

-135.7

0.6

2.8

-2.2

-394.1

Metals, Mining / Paper Products

0.5

0.6

-0.2

-20.1

0.8

3.6

-2.8

-502.1

Construction, Civil Engineering andConstruction-Related Products

0.1

1.5

-1.4

-150.4

0.3

8.3

-8.0

-1440.7

Note: Monetary amounts above were converted using a carbon price of USD$105/ton in 2030 and USD$180/ton in 2050 as a reference.
The carbon price above is based on the scenario of keeping the rise in global mean temperature to within 2°C in 2100 with a probability of 66%, which
was proposed by the International Energy Agency and International Renewable Energy Agency

Source: Prepared by GPIF based on Astamuse analysis

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Chapter3 Analysis of Inter-Industry Transfer of Transition Risks and Opportunities

Analysis of Patent Competitiveness of Decarbonization Technologies by Country/Region
This analysis also examined the patent competitiveness of decarbonizing and low-carbon
technologies by country and region. In MSCI’s CVaR analysis of low-carbon technologies, “forward
citations,” “backward citations,” “market coverage,” and “cooperative patent classification coverage”
were factored into the estimation of patent value.27 The analysis performed by Astamuse, on the other
hand, assigns each patent a “Patent Impact Score,” which evaluates the patent’s impact in terms of
its exclusivity rights, meaning the competitive threat posed to other companies (as determined by the
number of patent rejections issued to other companies, invalidation trial requests, etc.) and the levelof attention paid to the patent by other companies (e.g. number of views by other companies, numberof times information is provided, etc.), among other factors. Each Patent Impact Score is then weighted
by the geographical scope (countries of application, etc.) and remaining term of these rights, andaggregated by company to obtain the company’s “Total Patent Assets.” The competitiveness of eachcountry’s patents is measured using the Total Patent Asset indicator.
Figure 3-12 shows the relative competitiveness for five major countries and regions for all 40
technology fields. The results of this analysis indicate that Japan’s technological competitiveness isparticularly high in the energy technology field with respect to hydropower energy, small and mediumhydroelectric power generation, hydrogen/ammonia power generation, photovoltaic power generation,
solar batteries, and solar thermal power generation, among others. In the chemical technology field
as well, Japan is 2nd in the world behind the U.S. in materials for carbon absorption, adherence,
separation and storage, as well as carbon reuse. On the other hand, the analysis found that the U.S.
is superior in bioenergy and marine energy within the energy technology field, in addition tounderground/submarine carbon storage and waste/sewage sludge treatment within the social
infrastructure technology field (Figure 4), with the E.U.(Germany, France, Switzerland), the U.K. andSouth Korea also being highly competitive.
This analysis shows that socioeconomic trends and the evolution of technologies toward net-zerowill bring about a shift in supply and demand among industries and among countries, and that many
companies in Japan have the potential to benefit from this shift.

27

Please refer to page 63

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Chapter3 Analysis of Inter-Industry Transfer of Transition Risks and Opportunities

Figure 3-12

Comparison of Total Patent Assets of Decarbonization Technologies by Country/Region(Continued on following page)

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Chapter3 Analysis of Inter-Industry Transfer of Transition Risks and Opportunities

Figure 3-12

Comparison of Total Patent Assets of Decarbonization Technologies by Country/Region(Continued on following page)

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Chapter3 Analysis of Inter-Industry Transfer of Transition Risks and Opportunities

Figure 3-12

Comparison of Total Patent Assets of Decarbonization Technologies by Country/Region

Notes:
1. Indexed with the country with the highest total patent asset score in each technology domain, assigned a score of 100.
2. “EU” refers to EU member countries.
3. Chinese patents are not included in the analysis because it is difficult to compare them with patents from other countries
from a quality perspective.
Source: Prepared by GPIF based on Astamuse analysis

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81

Chapter 4: Other Analysis ｜ Energy Mix

Chapter 4:

Other Analysis

Energy Mix
This section reviews company disclosed data to analyze the physical units of power generated byenergy companies to calculate the corresponding energy mix. The energy mix is then compared to the2-degree aligned energy mix requirements for 2030- and 2050-time horizons, as estimated by theInternational Energy Agency (IEA) (Figure 4-1). The energy mix of the portfolio is the weighted
average 28 of the power supply composition of the portfolio's energy companies, based on theirdisclosures. As a result, compared to the power supply composition in 2030 and 2050, which isassumed in the IEA's 2-degree Scenario,29 the share of fossil fuel (coal, oil, and natural gas) power
generation is higher across all portfolios. Also, the share of renewable energy (hydro, biomass, andother renewable energy) is lower in all portfolios. Compared with fiscal 2019, fiscal 2020 saw anincrease in the share of natural gas generation across all portfolios. In foreign equities and bonds, theshare of renewable energy grew significantly from fiscal 2019 to fiscal 2020, accounting for about 20%
of generation. On the other hand, domestic equities and bonds have reflected a slower growth inrenewable energy, so there are expectations for this to grow in the future.
Figure 4-1 2-degree Alignment: Energy Mix
100%

(%)

90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
2019

Coal

2020

(FY)

2019

2020

(FY)

Domestic Equities

Foreign Equities

Petroleum

Fossil energy with CCS

Natural Gas

2019

2020

Domestic Bonds
Nuclear

2019

(FY)

Other sources

2020

Foreign Bonds
Hydroelectric

2030

(FY)

Biomass

2050

IEA(World)(Y)

Other Renewables

Source: S&P Trucost Limited© Trucost 2021

28

The percentage (%) is obtained by multiplying the amount of electricity generated by energy by its portfolio weight and dividingthat figure by the total electricity generated, weighted by the portfolio weight.
29
Based on data presented by the 2°C Scenario (2DS) developed by the IEA ©OECD IEA 2017.

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82

Chapter 4: Other Analysis ｜ EU Taxonomy Analysis

EU Taxonomy Analysis
Background and Overview
In March 2018, as part of its Action Plan for Sustainable Finance, the European Commission
adopted a strategy to incorporate Environmental, Social and Governance (ESG) considerations into
Europe's finance-related policy framework to promote sustainable economic growth from finance. In
May 2018, the Commission published the first batch of legislation based on this plan. In June 2019,
the draft taxonomy was published. The final report, with recommendations including the design of the
EU Taxonomy and implementation guidance, was published in March 2020.
The EU Taxonomy addresses six key environmental objectives: climate change mitigation, climatechange adaptation, sustainable use and protection of water and marine resources, transition to acircular economy, pollution prevention and control, and the protection and restoration of biodiversity
and ecosystems. The taxonomy considers economic activities that meet the following three conditions
to be environmentally sustainable: (1) make a substantive contribution to one of six environmental
objectives (meet the thresholds set by the taxonomy); (2) do no significant harm (DNSH) to the other
five, where relevant; and (3) meet minimum safeguards such as the Organisation for Economic Cooperation and Development (OECD) Guidelines for Multinational Enterprises and the United Nations
Guiding Principles on Business and Human Rights. Institutional investors, major listed companies andothers must make their first disclosures that take climate change mitigation and adaptation into
account by the end of 2022.
Economic activities covered by the taxonomy will be designated as either (1) low-carbon activities;(2) transitional activities; or (3) enabling activities. Low-carbon activities are those that do not alreadyemit GHGs (e.g., wind power generation, electric transportation, etc.); transitional activities are thosethat currently have a high carbon intensity but have room for significant reduction (e.g., natural gas
power generation, gasoline-powered transportation, etc.); and enabling activities are those that enable
the transition to a low-carbon society (e.g., the production of wind power and electric vehicles).
This analysis is based on Trucost's methodology to determine what percentage of the portfolio, in
terms of revenue, is potentially aligned with the EU taxonomy. Due to data and methodology limitations,the analysis will not consider the performance threshold for substantial contribution described above;
it will only examine whether a business falls under the transitional activity or enabling activity
categories described above.

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Chapter 4: Other Analysis ｜ EU Taxonomy Analysis

Analysis Methodology and Results
In the EU Taxonomy, 67 climate change mitigation activities are mapped to the seven macro-sectorsof the European industry-standard economic activity classification system (NACE30). This analysis
begins by mapping the 464 business activities in Trucost's classification system to the NACE macro
sectors to identify those businesses that fall within the 67 activities identified in the EU Taxonomy. Of
the 464 business activities, 117 are mapped to the EU taxonomy. The percentage of revenue fromeach company from each of these 117 business activities is then calculated and weighted using theportfolio weights of those businesses to measure the EU taxonomy revenue share of the entire
portfolio and the proportions of transitional and enabling businesses.
The results of the analysis of the GPIF portfolio by asset class are shown in Figure 4-2. We foundthat the EU taxonomy revenue share in the domestic equity portfolio exceeds that of the foreign equity
portfolio, with both the transitional revenue (13%) and enabling revenue (20%) exceeding the
proportion of foreign equity (10% and 14%). On the other hand, while the EU taxonomy revenue sharefor domestic bonds is higher than that for foreign bonds, the enabling revenue for foreign bonds (19%)
is higher than that for domestic bonds (12%).
Note that this analysis does not consider the criteria (thresholds) for judging substantial contributions
to climate change mitigation and climate change adaptation, but rather shows the percentage ofpotential revenue that could be considered environmentally sustainable economic activity. Therefore,
the figures that consider the above criteria are expected to be lower than those shown in Figure 4-2.
Figure 4-2 Weighted Average EU Taxonomy Revenue Share
Domestic
Equities

13%

Foreign
Equities

20%

10%Domestic
Bonds

14%

22%

Foreign
Bonds

12%

13%
0%

5%

19%
10%

15%

20%

Transitonal linked Revenue

25%

30%

Enabling linked Revenue

35%

40%
(%)

Note: Data is as of the end of March, 2021.
Source: GPIF, S&P Trucost Limited©Trucost 2021

30

Nomenclature des Activités Économiques dans la Communauté Européenne

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Chapter 4: Other Analysis ｜ EU Taxonomy Analysis

Analysis by Sector
We will now look at the results of the analysis above by sector. As a trend across all portfolios,
sectors such as Utilities, Materials, Industrials, and Energy have a high level of transitional revenue
because their current emissions are high and can be significantly reduced through future technologicalinnovation. On the other hand, electric vehicles and their components, energy-efficient communication
networks such as 5G, and software used to improve resource efficiency in other industries aretechnologies expected to contribute to reducing GHG emissions in the future. For this reason, theConsumer Discretionary, Communication Services, and Information Technology sectors, which containthese technologies, have a high ratio of enabling revenue. In addition, since almost all businesses
related to real estate are designated as transitional businesses in the EU taxonomy, the transitional
revenue share of the Real Estate sector in each portfolio is exceptionally high.
Figures 4-3 and 4-4 show the results of our analysis of equity portfolios. The reason why thedomestic equity portfolio has a relatively higher ratio of transitional revenue than the foreign equity
portfolio is that domestic equity has a higher weight in Industrials. In addition, the Utilities and Materials
sectors in the domestic equity portfolio have a larger revenue share from businesses that have moreroom for GHG reduction in the future than the same sectors in the foreign equity portfolio. Domestic
equities had a higher enabling revenue share than foreign equities due to the relatively large share ofrevenue generated from businesses that will contribute to future GHG reductions in Consumer
Discretionary and Communication Services.
The results for the bond portfolio are shown in Charts 4-5 and 4-6. The domestic bond portfolio hasa higher share of transitional revenue than the foreign bond portfolio due to the high portfolio weightingof Utilities and the relatively large amount of revenue generated by businesses with considerable
potential for future GHG reductions in this sector, as well as the Materials and Industrials sectors.
Although the weight of the Utilities sector in the foreign bond portfolio is lower than that of domestic
bonds, the share of the revenue from business lines that will contribute to future GHG reductions ishigh. In addition, unlike both the equity portfolios, the revenue share of enabling was higher than thatof domestic bonds due to the significant revenue share of projects that contribute to emission
reductions from Communication Services.
As noted above, the above results focus only on whether each business is eligible for the taxonomy
framework and does not assess whether the three conditions described above (in particular, theachievement of the substantial contribution threshold) are met. Therefore, it should be noted that therevenue shares shown here may not technically be considered as revenue from sustainable economic
activities under the EU taxonomy.

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Chapter 4: Other Analysis ｜ EU Taxonomy Analysis

Figure 4-3 EU Taxonomy Revenue Share by GICS

Figure 4-4 EU Taxonomy Revenue Share by GICS

Sectors in Domestic Equities Portfolio

Sectors in Foreign Equities Portfolio

100%

100%

(%)

(%)

Enabling linked revenue

Enabling linked revenue
80%

80%

Transitional linked revenue

Transitional linked revenue

Financials

Health Care

Consumer Staples

Financials

Health Care

Consumer Staples

EnergyIndustrials

Information Technology

Communication Services

Consumer Discretionary

Materials

Utilities

Real Estate

Source: GPIF, S&P Trucost Limited©Trucost 2021

Energy0%Industrials

0%

Information Technology

20%

Communication Services

20%

Consumer Discretionary

40%

Materials

40%

Utilities

60%

Real Estate60%

Source: GPIF, S&P Trucost Limited©Trucost 2021

Figure 4-5 EU Taxonomy Revenue Share by GICS

Figure 4-6 EU Taxonomy Revenue Share by GICS

Sectors in Domestic Bonds Portfolio

Sectors in Foreign Bonds Portfolio

100%

100%

(%)

(%)

Enabling linked revenue
80%

Transitional linked revenue

80%

Financials

Health Care

Consumer Staples

Financials

Health Care

Consumer Staples

EnergyIndustrials

Information Technology

Communication Services

Consumer Discretionary

Materials

Utilities

Real Estate

Energy0%Industrials

0%

Information Technology

20%

Communication Services

20%

Consumer Discretionary

40%

Materials

40%

Utilities

60%

Transitional linked revenue

Real Estate60%

Source: GPIF, S&P Trucost Limited©Trucost 2021

Enabling linked revenue

Source: GPIF, S&P Trucost Limited©Trucost 2021

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86

Chapter 4: Other Analysis ｜Analysis of

SDGs-Related Revenue Opportunities and Risks

Analysis of SDGs-Related Revenue Opportunities
and Risks
SDGs Positive Impact Analysis
In previous sections, we analyzed the risks and opportunities in the context of climate change, but
this section expands the discussion beyond climate change by presenting an analysis of the indirectcontributions of GPIF’s equities portfolio to the resolution of social issues identified in the Sustainable
Development Goals (SDGs) defined by the United Nations.
In this analysis, we determined the percentage of total revenue generated by products and services
that contribute to the SDGs for the companies in GPIF’s equities portfolio, based on definitions by
Trucost. We then measured the exposure of companies contributing to the SDGs by using portfolio
holding weights to calculate the weighted average revenue exposure, or SDGs Positive Impact, of theportfolio.
In a comparison of the SDGs Positive Impact of GPIF’s domestic and foreign equities portfolios foreach SDGs, the foreign equities portfolio generally tends to have a greater positive impact. This result
suggests that, from the perspective of contributing to the SDGs and securing profit opportunities
thereby, Japanese companies have much room for growth (Figure 4-7).

SDGs Additionality Analysis
Each year, the Sustainable Development Solutions Network (SDSN), launched in 2012 by the UN
Secretary-General, releases the Sustainable Development Report. The report includes the “SDGs
Performance Gap,” which estimates the distance to the achievement of each target of the SDGs. The
gap for each country is expressed as the contribution rate of the country to the global gap (Figure 48).
To determine the SDGs performance gap, it is necessary to analyze the extent to which countries
are currently achieving the SDGs targets. The SDSN has set numerical targets for each of the 169
targets of the SDGs. Specifically, if a target already has a numerical target, that number is applied(e.g., Target 3.1 is to reduce the global maternal mortality ratio to less than 70 per 100,000 by 2030).
For those where no targets are given, targets will be set based on scientific knowledge or the
performance of the top five countries that have already achieved their targets. Next, each country's
progress is assessed against the indicators using official data from the OECD, the World HealthOrganization (WHO), United Nations Children’s Fund (UNICEF), and other sources. The distance from

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87

Chapter 4: Other Analysis ｜Analysis of

SDGs-Related Revenue Opportunities and Risks

the current progress to the target value is called the SDGs performance gap.
For SDG 1: No Poverty and SDG 4: Quality Education, for example, the G20 nations’ total
contribution to the gap is only around 30%, indicating that, if the SDGs are to be achieved,
improvement will be needed in non-G20 countries, especially African nations. On the other hand, for
SDG 13: Climate Action, the G20 nations’ total contribution to the gap is over 80%, indicating that thisis a challenge particularly for the developed nations and China.
In the SDGs Positive Impact Analysis mentioned above, we linked the SDGs targets with companies’
products and services. Even if two companies provide the same products and services, their degreeof contribution to the SDGs will increase if the products and services are provided in countries that area long way from achieving the SDGs. For example, marketing a certain drug in emerging countries
that have poor sanitation and high morbidity rates is likely to make a greater contribution to the SDGs
than if the same drug were marketed in developed countries with low morbidity rates. From thisperspective, the SDGs Additionality. Analysis uses the SDGs Performance Gap to examine which
products and services marketed in which countries and regions are able to contribute to what extent
to the achievement of the SDGs. These contributions are aggregated for each company according to
the composition of their net sales to determine their SDGs Additionality.
Comparing the weighted average SDGs additionality and the benchmark for GPIF’s portfolio reveals
that both domestic and foreign equities slightly exceeded the benchmark, showing that the portfolio
makes a relatively large contribution to the SDGs (Figure 4-9). Among equities in major economies(top ten countries and regions by MSCI ACWI composition weight), we calculated the weighted
average SDGs additionality by constituent country and ranked them by country and region. Taiwan
came out on top, far ahead of the others, while Japan ranked seventh (Figure 4-10). In Taiwan,
semiconductor-related companies, which have an extremely high weight in the index, are making
significant contributions to SDG 9: Industry, Innovation and Infrastructure and SDG 17: Partnerships
for the Goals, which seems to be largely attributable to individual company attributes.

SDGs Risk-Exposure Analysis
While the previous section examined the SDGs from a positive perspective, the SDGs RiskExposure Analysis is conducted from a risk perspective. In the SDGs Risk Exposure Analysis, theexposure to SDGs-related risks that directly or indirectly affect or are affected by the company in thevalue chain is represented by a score from 0 to 100, where 0 is the lowest risk, and 100 is the highest
risk. These include the risks that a company directly or indirectly generates negative impacts, such as
GHG emissions and the risks that a company relies on practices or activities that conflict with theSDGs, such as child labor and underpayment of wages. Exposure to these risks is assessed basedon the geographic distribution of the sectors and supply chains in which the company operates. For

Copyright © 2021 Government Pension Investment Fund All rights reserved.

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Chapter 4: Other Analysis ｜Analysis of

SDGs-Related Revenue Opportunities and Risks

example, air, land, and water pollution issues are more likely to involve companies in the heavy
industry and energy sectors than companies in retail and services. Similarly, the risk of corruption andchild labor may vary depending on the country in which a company has production activities. Since
few companies disclose details such as the geographic distribution of their entire supply chain, we use
Trucost's model for this analysis.
An analysis of the GPIF's domestic and foreign equity portfolios by sector reveals that while thehigh-risk SDGs items are similar for both domestic and foreign equities, foreign equities tend to havehigher risk scores than domestic equities for many of the goals. In other words, foreign equities are
more likely to have SDGs-related risks. This may be due to the geographical distribution of the supply
chain affecting the evaluation, as foreign companies may be procuring products and services fromcountries with relatively higher risks. Reports released by the OECD31 and other organizations haveconfirmed that Japanese companies have a low presence in global value chains. Where companies
supply and procure goods and services across multiple countries to optimize their production
processes, the supply chains of foreign companies tend to span more countries than those ofJapanese companies. In all asset classes and sectors, the risks associated with SDG 17, "Achieve
the Goals through Partnership," are high. One of the targets set in this goal is to "strengthen themobilization of domestic resources, including international assistance to developing countries, toenhance taxation and tax collection capacity.” This risk tends to be higher when companies based in
tax havens are included in the supply chain. It should be noted that the SDGs Risk Exposure Analysis
measures the exposure to risks defined by sector and supply chain and does not consider the actual
activities that companies are undertaking to address SDGs-related risks.
Figure 4-7 SDGs Positive Impact by Individual Goal
SDGs 1 No Poverty
SDGs 2 Zero Hunger
SDGs 3 Good Health and Well-Being
SDGs 4 Quality Education
SDGs 5 Gender Equality
SDGs 6 Clean Water and Sanitation
SDGs 7 Affordable and Clean Energy
SDGs 8 Decent Work and Economic Growth
SDGs 9 Industry, Innovation and Infrastructure
SDGs 10 Reduced Inequalities
SDGs 11 Sustainable Cities and Communities

Foreign Equities

SDGs 12 Responsible Consumption and Production
SDGs 13 Climate Action

Domestic Equities

SDGs 14 Life below Water
SDGs 15 Life on Land
SDGs 16 Peace, Justice and Strong Institutions
SDGs 17 Partnerships for the Goals
Note: Data is as of the end of March, 2021.
Source: GPIF, S&P Trucost Limited©Trucost2021

31

0%

5%

10%

15%(%)

Global value chains: Efficiency and risks in the context of COVID-19©OECD 2021

Copyright © 2021 Government Pension Investment Fund All rights reserved.

89

Chapter 4: Other Analysis ｜Analysis of

SDGs-Related Revenue Opportunities and Risks

Figure 4-8 SDGs Performance Gap
Japan
0.1
1.0
0.3
0.0
1.6
0.7
0.4
0.9
0.3
0.8
1.2
3.3
4.7
2.0
1.4
0.4
1.2

SDGs 1 No Poverty
SDGs 2 Zero Hunger
SDGs 3 Good Health and Well-Being
SDGs 4 Quality Education
SDGs 5 Gender Equality
SDGs 6 Clean Water and Sanitation
SDGs 7 Affordable and Clean Energy
SDGs 8 Decent Work and Economic Growth
SDGs 9 Industry, Innovation and Infrastructure
SDGs 10 Reduced Inequalities
SDGs 11 Sustainable Cities and Communities
SDGs 12 Responsible Consumption and Production
SDGs 13 Climate Action
SDGs 14 Life below Water
SDGs 15 Life on Land
SDGs 16 Peace, Justice and Strong Institutions
SDGs 17 Partnerships for the Goals

USA
0.2
3.5
1.5
0.1
2.6
2.1
1.0
2.8
0.5
5.0
1.4
12.5
16.3
3.9
4.3
2.9
3.0

EU
0.3
4.6
1.5
1.1
3.1
2.6
1.4
4.7
2.1
3.1
2.7
14.7
14.6
6.1
2.9
3.1
4.7

China
1.8
10.5
11.7
5.4
10.7
17.2
20.1
10.3
10.5
16.0
13.5
13.7
17.2
23.2
18.7
18.2
22.8

India
21.8
23.8
24.5
17.3
29.2
23.1
19.7
14.0
21.5
17.6
27.2
8.8
5.2
16.6
22.0
18.7
20.8

G20 Total
33.3
57.8
50.8
30.2
58.7
56.3
49.7
49.2
47.6
62.4
56.8
74.7
81.9
66.3
66.3
57.9
65.1

Note: Numbers in red are 10-20%, highlighted in yellow are +20%.
Source: Created by GPIF based on the Sustainable Development Report 2020.

Figure 4-9 GPIF Portfolio Weighted Average SDGs Additionality
90
80
70

(%)
59.9

57.5

Domestic Equities

TOPIX

60

77.4

77.1

Foreign Equities

MSCI ACWI(exJapan)

50
40
30
20
10
0
Note: Data is as of the end of March, 2021.
Source: S&P Trucost Limited©Trucost2021

Figure 4-10 Comparison of Weighted Average SDGs Additionality by Major Countries and Regions
TaiwanSwitzerland
China
USA
CanadaAustralia
Japan
Germany
UK
France
0

20

40

60

80

100

120

Note: Aggregated data is of MSCI ACWI constituents, Upper graph indicates the top 10 countries/regions with the most SDG Additionality among the 10
highest exposures in the index.
Source: MSCI, S&P Trucost Limited©Trucost2021

Copyright © 2021 Government Pension Investment Fund All rights reserved.

140
(%)

90

Introduction of Each Company

Introduction of Each Company＜About MSCI Climate Risk Center＞

MSCI Climate Risk Center plays a central part in analyzing climate-change risks in MSCI. The Centre
aims to use climate change science for financial risk analysis through partnerships with major
academic institutions and research institutions built by Carbon Delta, which MSCI acquired in October
2019.

＜About Trucost＞

Established in 2000, Trucost is a pioneer in the field of carbon data and reporting and has compiled acomprehensive and growing dataset that includes over 15,000 companies. Acquired by S&P Global in
October of 2016, Trucost is continuing to provide not only environmental data, but also essential ESGrelated data on a global scale.

＜About Astamuse＞

Astamuse has built one of the world's largest intangible asset visualization databases with more than
700 million data points from193 countries and in 39 languages. We classify and analyze this data into
uniquely defined "growth areas" and "social issues" that humanity needs to solve to achieve the SDGs.

The purpose of this report is to provide pension beneficiaries and investee companies with the results of several
analyses consigned to MSCI, Trucost and Astamuse for use in GPIF’s TCFD-aligned disclosures. GPIF does
not intend to directly reflect the results into our immediate investment activity. The contents of the report are
based upon information available at the time of creation, and are subject to future correction or revision without
notice. GPIF does not guarantee the accuracy or completeness of the report, and retains full rights to the content.
Reproduction, etc. without prior approval is prohibited.

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91

Disclaimer

MSCI
Although GPIF’s information providers, including without limitation, MSCI ESG Research LLC and its
affiliates (the “ESG Parties”), obtain information from sources they consider reliable, none of the ESG
Parties warrants or guarantees the originality, accuracy and/or completeness, of any data herein andexpressly disclaim all express or implied warranties, including those of merchantability and fitness fora particular purpose. None of the Information is intended to constitute investment advice or arecommendation to make (or refrain from making) any kind of investment decision and may not be
relied on as such, nor should it be taken as an indication or guarantee of any future performance,
analysis, forecast or prediction. None of the ESG Parties shall have any liability for any errors oromissions in connection with any data or Information herein, or any liability for any direct, indirect,
special, punitive, consequential or any other damages (including lost profits) even if notified of thepossibility of such damages.
S&P Trucost
Certain data and information contained herein has been supplied by S&P Trucost Limited. All rights inand to the Trucost data, information and reports (including any and all intellectual property contained
therein) vest in Trucost and/or its licensors or affiliates. Neither Trucost, nor its affiliates, nor its
licensors accept any liability for any errors, omissions or interruptions in the Trucost data, information
and/or reports. No further distribution of the data, information and/or reports is permitted without
Trucost’s express written consent. S&P Trucost Limited and/or its licensors or affiliates do not in any
manner warrant or represent that its’ respective data, information and reports contained herein areappropriate or available for use in any particular location. Your access and use of the relevant data
and reports shall be done so in compliance with all applicable laws.
Astamuse
This document has been compiled by astamuse Co., Ltd. ("astamuse") using data provided by patentoffices and corporate information providers around the world. This material is not a solicitation or
inducement to engage in investment activities, should not be used as an offer to "buy" or "sell" anysecurities, and does not constitute tax, investment or any other advice. astamuse does not intend toprovide advice that is tailored to the individual circumstances of each individual investor. The use ofthis material is not a substitute for the investment advisory of a qualified investment professional.
Although the information in this material has been obtained from sources believed to be of generalreliability, neither astamuse nor its information providers, nor any party providing this material to thereader, guarantee the accuracy or completeness of this material, and astamuse assumes noresponsibility for any errors or omissions in the provision of information, or for any interruptions ordelays in transmission, or for any damages arising from the use of this material.

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92