RESEARCH INSIGHTSMSCI ESG RESEARCH LLC

2023 Analysis of
Climate ChangeRelated Risks in the
GPIF’s Portfolios
MSCI ESG Research
July 2023

This Paper is prepared by MSCI in connection with information provided by GPIF, and the Copyright of this Paper belongs to GPIF.
© 2023 MSCI Inc. All rights reserved. Please refer to the disclaimer at the end of this document.

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Contents
Executive summary ................................................................................................... 3
Analysis of companies’ climate target-level data ..................................................... 5
Status of companies’ climate targets based on MSCI target-level data......................... 5
Status of companies’ Scope 1 and 2 and Scope 3 emissions disclosure rates ............ 7
Analysis of corporate GHG emissions and climate targets by scope ............................. 8
Modelling target-based emissions projections using a Target Summary Model... 12
Understanding the MSCI Target Summary Model ......................................................... 12
Target-based emissions projections using target credibility assessments .................. 15
Impact analysis using Implied Temperature Rise (ITR) .......................................... 19
Climate-related risks for the sovereign bond portfolio ........................................... 27
MSCI Sovereign Bond Climate Value-at-Risk ................................................................ 27
NGFS scenarios............................................................................................................. 27
Results for GPIF’s sovereign bonds portfolio ................................................................. 28
Climate-related risks on the real estate portfolio .................................................... 33
MSCI Real Estate Climate Value-at-Risk ........................................................................ 33
The Transition Policy Risk Model ................................................................................. 33
The Physical Risk Model ............................................................................................... 34
Results for GPIF’s real estate portfolio............................................................................ 35
Appendixes .............................................................................................................. 37
Appendix I: Understanding the MSCI Target Summary Model ..................................... 37
Appendix II: Comparison of yield curve shocks between NGFS phase II and phase III............................................................................................................................................. 41© 2023 MSCI Inc. All rights reserved.

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Executive summary
This paper provides an analysis of climate-related investment risks and impacts from the portfolios of
the Government Pension Investment Fund (GPIF), using MSCI’s analytical tools. We cover issues
including the state of corporate carbon emissions disclosures, target-setting, and portfolio alignment
as well as investment risks for sovereign and Real Estate assets. Wherever possible, we conducted
historical comparisons with past GPIF analyses and comparisons to relevant benchmarks. Our main
conclusions are as follows.
Increasing transparency regarding carbon emissions: Using the MSCI ACWI Investable Market
Index (IMI) as a benchmark, we found Scope 1 and Scope 2 emissions disclosures at 52% andScope 3 emissions disclosure at 32% (as of June 2023). By contrast, companies in the MSCI Japan
IMI showed higher Scope 1 and 2 emissions disclosures of 61% and 41% for Scope 3 emissions.
While Japanese companies tended to have better emission disclosures, we note a global trend
towards improved emissions reporting. This extends to Scope 3 emissions, despite challenges
related to determining supply chain emissions. We attribute this upward trend in part to a series ofincoming corporate climate disclosure standards across different markets.
Corporate climate target-setting on the rise: the UNFCCC1-mandated “Nationally Determined
Contributions” have been in place since the Paris Agreement in 2015, with a requirement formember states to regularly ratchet up those commitments. Similarly, there is a growing number ofcompanies setting climate targets on a voluntary basis.2 The proportion of issuers with climate
targets for target years of 2023 and beyond in the MSCI ACWI IMI rose from 6% in 2015 to 48% in
2023. Of the 9,181 constituents of the MSCI ACWI IMI, 18% had set or committed to set in the futureclimate targets approved by the Science Based Targets Initiative (SBTi), as recommended by a new
UN agency.3 When looking at the GPIF’s home market, we found 65% of companies in the MSCIJapan IMI have set climate targets and the proportion of SBTi-approved targets in Japan is in linewith the global average of 18%. Japanese companies tended to lag peers in other developed
markets, represented by the MSCI Kokusai IMI, in which 24% of constituents had set, or committed
to set, SBTi-approved targets.
Targets gaining “credibility” in places: not all corporate climate targets are created equal. They
vary significantly in terms of scope and ambition. MSCI’s Target Summary Model standardizes theassessment of such targets and projects the resulting emissions, referring to the latest guidancefrom the Glasgow Financial Alliance for Net Zero (GFANZ). The model incorporates target credibility
assessments, which focus on the following four factors: i) short-term and long-term target-setting, ii)
third party target validation, iii) track record of achieving past targets, and iv) alignment of emissions
reduction progress with current targets, across each emissions scope. Few issuers achieved fullcredibility on all four factors. Using the target credibility factors, we have also compared companies
with SBTi-approved targets (i.e., SBTi Group) and those with targets which are not approved (i.e.,
Non-SBTi Group). Overall, we assessed companies in the SBTi Group as having targets with higher
credibility than those in the Non-SBTi Group. This suggests that companies which underwent a third-

1 United Nations Framework Convention on Climate Change
2 MSCI collects climate target level data from publicly available disclosures including corporate disclosures. Climate target level

data incudes various targets such as corporate greenhouse gas (GHG) emissions reduction targets, emissions intensity reduction
targets, renewable energy procurement targets, methane leak reduction targets, and portfolio emissions reduction targets.
3 United Nations’ High-Level Expert Group on the Net-Zero Emissions Commitments of Non-State Entities. See “Integrity Matters: Net

Zero Commitments by Businesses, Financial Institutions, Cities and Regions.” United Nations’ High-Level Expert Group on the NetZero Emissions Commitments of Non-State Entities, November 2022.

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party target-validation process tended to set more comprehensive targets and provided greatertransparency into their decarbonization strategy.
Aligning with the goals of the Paris Agreement remains challenging: MSCI’s Implied
Temperature Rise (ITR) provides investors with an understanding of the extent to which companies,
portfolios and funds are aligned with global climate goals, expressed in terms of degrees of warming.
In 2023, MSCI updated the ITR methodology using the latest guidance from the GFANZ. Applying
the updated ITR model, the proportion of so-called “Paris-aligned” companies, i.e., aligned with 2°C
of warming or lower, has slightly increased in the GPIF’s portfolios during FY2021 and FY2022.4
This also reflects the fact that an increased proportion of companies in the GPIF total portfolio haveset emissions reduction targets, going up from 63.1% in FY2021 to 65.7% in FY2022. However,collectively, these companies might not have set as clear or as ambitious emissions reduction
targets to keep the global average temperature rise below 1.5°C or 2.0 °C. That is, the GPIF’s total
portfolio-level ITR remained stable at 2.5°C during FY2021 and FY2022, performing slightly better
than the MSCI ACWI IMI at 2.6°C, but remaining misaligned with the goals of the Paris Agreement.
Transition risks rise for sovereign bonds under the “Divergent Net Zero” scenario, but the full
extent of acute physical risks under a higher temperature rise scenario remain to be seen: in
addition to ITR analysis, we conducted an analysis on the potential impact of a low carbon transition
on sovereign bonds using MSCI’s Sovereign Bond Climate Value-at-Risk (VaR) model. This tool
estimates the change in sovereign yields when markets factor in climate risks based on certain
scenarios – in this case the Network for Greening the Financial System (NGFS) scenarios, which
predominantly focus on transition risks and incorporate some chronic physical risks.5 When using thelatest NGFS scenarios (“Phase III”), we find that the losses from transition risks are more severe
than previous analyses using Phase II, for the “Divergent Net Zero” scenario, as the NGFS assumes
that policy uncertainty may lead to a higher investment premium. When focusing on Japan and U.S.
sovereign bonds, the highest portions of the GPIF holdings, both in Japan and U.S. bear the largest
transition risks under the Divergent Net Zero scenario.
The trade-off between physical and transition risks on real estate portfolios: buildings are asignificant source of carbon emissions mainly through their energy consumption, which may give riseto transition risks. They are also exposed to physical climate impacts, for example through extreme
weather events. We thus analyzed the GPIF commercial (office, industrial, retail) and residential realestate portfolios using the MSCI Real Estate Climate Value-at-Risk (VaR). The “Transition Policy
Risk” model assessed the potential cost impact from the transition to a low-carbon economy under
different scenarios. The “Physical Risk” model assessed the cost of physical climate risks onbuildings, using geo-localized climate data incorporating extreme heat, extreme cold, fluvial andcoastal flooding, tropical cyclones and wildfire, using NGFS scenarios to compute forward-looking
risks and impacts. Using the Physical Risk VaR model, the GPIF Real Estate portfolios are expected
to face the lowest risk under a 1.5°C scenario and highest risk under a 3°C scenario, with coastal
flooding accounting for most of risks. On the other hand, the Transition Policy VaR showed thelargest impact under the 1.5°C REMIND Orderly Scenario, with the 3°C REMIND “Hot House World”
being the least impactful.6 This shows how stringent (1.5°C) climate policies designed to mitigate
carbon emissions in the Real Estate sector could increase costs, while less stringent climate policies
could result in temperature rise scenarios as high as a 3°C, posing highest physical risks throughmore acute and frequent extreme weather events.
4 Unless otherwise noted, updated ITR results in this report were based on simulated results as of April 2023.
5 We note that the NGFS scenario has not yet fully incorporated acute physical risks such as coastal flooding and tropical cyclones

nor it has not prescribed low carbon technology opportunity metrics, indicating that the impacts of acute physical risks andtechnology opportunities on the sovereign bonds were outside of scope for this analysis.
6 We note that the model cannot fully predict cost allocations. For example, some transition costs may be shared with the buildings’

tenants.

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Analysis of companies’ climate target-level data
Status of companies’ climate targets based on MSCI target-level data
The Paris Agreement has required each state to communicate a nationally determined contribution(NDC) every five years.7 This binding obligation on each state was characterized as the ambitionraising cycle of the Paris Agreement. The ambition-raising cycle was intended to promote
progressively stronger NDCs over time and it was viewed as crucial by many states since the NDCs
submitted to date were considered insufficient to meet the temperature goal of the Paris Agreement.8
G7 nations also highlighted their commitments to reach net-zero emissions by 2050 in Hiroshima.9
Globally, 88 states, covering approximately 80% of global greenhouse gas (GHG) emissions, haveadopted net-zero pledges, as of September 2022. This is up from 74 states in 2021.10 The NDCs
including these net-zero pledges, however, will not be achieved by the state actors alone; it requires
a combined effort in conjunction with the private sector. Therefore, in the transition to a net-zero
economy, companies may face regulatory risks centered around emissions from their businessactivities. Corporate climate targets can provide an indication of a company’s intent to reduce its
impact on climate change and minimize potential risks associated with its emissions.
This section examines the status of corporate climate target setting. Of the 9,181 companies in the
MSCI ACWI Investable Market Index (IMI), an equity index that comprises the large, mid and smallcap constituents, the number of companies setting climate targets with a target year of 2023
and later has increased to 48% from 6% over eight years during 2015 and 2023 (Exhibit 1).
Exhibit 1: Number of companies with greenhouse gas emissions reduction targets

Source: MSCI ESG Research LLC, data as of June 30, 2023. Refers to constituents of the MSCI ACWI IMI.
7 United Nations Framework Convention on Climate Change. 2015. “The Paris Agreement, Art 14.2.”
8 United Nations Environmental Program. 2022. “Emissions Gap Report 2022.”, D. Bodansky. 2017. “International Climate Change

Law.”
9 Ministry of Foreign Affair. May 2023. “G7 Hiroshima Leaders’ Communique.”
10 Ibid.

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Of the 9,181 constituents in the MSCI ACWI IMI, 32% aimed to reach a state of “self-declared” netzero, in the same time period. The rise in target setting may reflect a variety of factors, including thestrengthening of NDCs and a series of both voluntary and mandatory corporate climate disclosure
standards, both in effect and anticipated.11
A caveat is that self-declared net-zero targets vary in terms of their comprehensiveness andambition.12 Some aim to balance carbon emissions with carbon removal, while others do not covercompanies’ complete carbon footprint or rely on carbon offsets that lack third-party validation.
Of the total 9,181 MSCI ACWI IMI constituents, 18% of listed companies had set or committed to set
decarbonization targets aligned with the standard defined by the Science-Based Targets initiative(SBTi), which requires companies to set long-term targets that would reduce their residual emissions
to net-zero by 2050 while aligning their reductions with a 1.5°C pathway over the near term.13 A
United Nations high-level expert group on net-zero commitments by the private sector recommended
at COP27 that investors have their targets verified by a third party, such as SBTi.14
In Exhibit 2, we have also analyzed the status of corporate climate targets by market types, using
constituents of three different indexes, namely Japan (the MSCI Japan IMI), developed markets, ex.
Japan (the MSCI Kokusai IMI15), and emerging markets (the MSCI EM IMI).
Exhibit 2: Climate target status of constituents across four MSCI Indexes

Source: MSCI ESG Research, data as of June 30, 2023

11 They include the standard from the International Sustainability Standards Board, European Sustainability Reporting Standards inthe European Union, and climate disclosure rules proposed by the U.S. Securities and Exchange Commission. See “ESG and Climate
Trends to Watch for 2023.” MSCI ESG Research, Dec. 6, 2022.
12 “The Road to Science-Based Corporate Net-Zero Target Setting.” MSCI ESG Research, September 2022.
13 “SBTi Corporate Net-Zero Standard, Version 10.” Science Based Targets initiative, October 2021. Data as of March 31, 2023.
14 “Integrity Matters: Net Zero Commitments by Businesses, Financial Institutions, Cities and Regions.” Report from the United

Nations’ High-Level Expert Group on the Net Zero Emissions Commitments of Non-State Entities, Nov. 8, 2022.
15 The MSCI World IMI excluding the MSCI Japan IMI.

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We found that 65% of index constituents from Japan (MSCI Japan IMI) and 52% of constituents fromdeveloped markets outside of Japan (MSCI Kokusai IMI) had set some type of climate target. This
dropped to 48% and 35% when looking at self-declared net-zero targets (Exhibit 2). This trend wasreversed when looking at SBTi-approved targets, or a commitment to set future SBTi targets, withfewer Japanese constituents doing so (18% of MSCI Japan IMI) compared with other developed
market constituents (24% of MSCI Kokusai IMI).16
Of the 3,336 MSCI EM IMI constituents, 37% set some types of climate targets, 23% had set selfdeclared net-zero targets and 9% had committed to the SBTi standards. These results highlight thedifferences between emerging and developed markets in terms of corporate decarbonization targets.

Status of companies’ Scope 1 and 2 and Scope 3 emissions disclosure
rates
For the first step of our target assessment, we analyzed how many companies have reported
emissions in line with the GHG Protocol across the four different indexes – a fundamental first step
to planning decarbonization strategies and measuring progress.
Of the 9,181 constituents in the MSCI ACWI IMI, 52% disclosed Scope 1 and 2 emissions and 32%
disclosed some Scope 3 emissions, as of June 2023 (Exhibit 3).17 Across the four indexes,
companies in the MSCI Japan IMI showed the highest Scope 1 and 2 disclosure rates of 61%.
Exhibit 3: Status of Scope 1, 2 and 3 emissions disclosure rates across four MSCI Indexes

Source: MSCI ESG Research, data as of June 30, 2023

Further, Japanese companies have increased the disclosure rates of some Scope 3 emissions
to 41% from 35% between 2019 and 2020, the highest increase rate across the four indexes.
Companies in the MSCI Kokusai IMI have also increased Scope 1 and 2 disclosure rates to 54%
from 49% in the same period.
16 SBTi. “Company Taking Action.”, last accessed on June 30, 2023.
17 Greenhouse gas protocol divided Scope 3 emissions into 15 categories in accordance with Corporate Value Chain (Scope 3)

Accounting and Reporting Standard. We counted Scope 3 emissions disclosures if a company reported at least one category.

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These increases could be attributed to a series of corporate climate disclosure standards slated totake effect in the coming years, including the mandatory disclosure of sustainability metrics forsecurities reports in Japan, the SEC’s proposed rule in climate-related disclosure and the corporate
sustainability reporting standard (CSRD) in Europe.18
Of the 3,336 companies in the MSCI EM IMI, 47% of constituents have disclosed Scope 1 and 2
emissions, catching up with the rest of the world rapidly, as of June 2023. Nonetheless, companies
in emerging markets continue to lag their developed market peers on Scope 3 emissions reporting.

Analysis of corporate GHG emissions and climate targets by scope
Using MSCI’s target-level data, we analyzed companies’ emissions by scope and the rate of thecompanies’ emissions covered by their targets, i.e., “comprehensiveness”.
In a transition to net-zero economies, a company may face regulatory risks centered around its
operational emissions (i.e., Scope 1 and 2). Its upstream suppliers (i.e., Scope 3) may also passthrough increased costs for sourcing carbon-intensive materials, or its downstream customers may
show reduced demand for particular products based on their emissions, such as fossil fuels andconventional internal combustion engine vehicles. Hence, companies may find it helpful to align theirtarget scopes with these potential regulatory and market risks.
Measuring the rates of emissions by scope and comparing those to the emissions coverage rate by
a company’s stated target allows investors to assess the potential impact such targets could provide,
if met, in mitigating transition risks in a low-carbon scenario.
Exhibits 4, 5, 6 and 7 below illustrate the aggregate of sector-level emissions by scope compared tothe scope of company targets and demonstrates the misalignment between the most carbonintensive parts of companies’ business activities and the scopes that their targets cover.
Across the four different indexes, most targets set by the utilities and materials sectors focused on
their own operations, the highest-emitting business activities in their value chain, i.e., Scope 1 and 2,
indicating among the highest coverage ratios by their targets. However, we found greater degrees of
misalignment in other sectors. When large misalignments occur, it could imply that certain climate
risks are not being disclosed or appropriately considered, elevating uncertainty around whether
transition risks are being managed adequately.
Scope 3 emissions represent the largest gap. As these emissions can stem from clients andsuppliers and out of direct control or risk management practices of the company, Scope 3 targets
have historically been relatively rare. Developed market constituents outside of Japan (MSCI
Kokusai IMI) showed the highest proportions of Scope 3 targets at 38%, compared to 31%, 24% and
20% of the MSCI ACWI IMI, MSCI Japan IMI and MSCI EM IMI, respectively.

18 Financial Service Agency. November 2022. “Cabinet’s order on corporate disclosure.”, U.S. Securities and Exchange

Commissions. March 2022. “SEC Proposes Rules to Enhance and Standardize Climate-Related Disclosures for Investors.”, European
Commission. “Corporate Sustainability Reporting.” Last accessed, as of June 30, 2023.

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Exhibit 4: GHG emissions and reduction targets of companies in different sectors across the
MSCI ACWI IMI

Source: MSCI ESG Research, data as of June 30, 2023. Refers to constituents of the MSCI ACWI IMI.
Notes: Chart on the left-hand side indicates average percentages of emissions from Scope 1+2 boundaries, Scope 3
upstream boundaries and Scope 3 downstream boundaries. The center chart indicates percentages of companies
that aim to reduce Scope 1 and 2 emission, Scope 1, 2 and 3 upstream emissions, Scope 1, 2 and 3 upstream anddownstream emission and Scope 1 and 2 and undefined categories of Scope 3 emissions in the final target year.
Chart on the right-hand side indicates average percentages of total emissions covered by targets in each sector of
the Global Industry Classification Standard (GICS®).19

Exhibit 5: GHG emissions and reduction targets of companies in different sectors across the
MSCI Japan IMI

Source: MSCI ESG Research, data as of June 2023. Refers to constituents of the MSCI Japan IMI.
Notes: Chart on the left-hand side indicates average percentages of emissions from Scope 1+2 boundaries, Scope 3
upstream boundaries and Scope 3 downstream boundaries. The center chart indicates percentages of companies
that aim to reduce Scope 1 and 2 emission, Scope 1, 2 and 3 upstream emissions, Scope 1, 2 and 3 upstream and
19 GICS is the global industry classification standard jointly developed by MSCI and S&P Global Market Intelligence.

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downstream emission and Scope 1 and 2 and undefined categories of Scope 3 emissions in the final target year.
Chart on the right-hand side indicates average percentages of total emissions covered by targets in each GICS
sector.

Exhibit 6: GHG emissions and reduction targets of companies in different sectors across the
MSCI Kokusai IMI

Source: MSCI ESG Research, data as of June 30, 2023. Refers to constituents of the MSCI Kokusai IMI.
Notes: Chart on the left-hand side indicates average percentages of emissions from Scope 1+2 boundaries, Scope 3
upstream boundaries and Scope 3 downstream boundaries. The center chart indicates percentages of companies
that aim to reduce Scope 1 and 2 emission, Scope 1, 2 and 3 upstream emissions, Scope 1, 2 and 3 upstream anddownstream emission and Scope 1 and 2 and undefined categories of Scope 3 emissions in the final target year.
Chart on the right-hand side indicates average percentages of total emissions covered by targets in each GICS
sector.

Exhibit 7: GHG emissions and reduction targets of companies in different sectors across the
MSCI EM IMI

Source: MSCI ESG Research, data as of June 30, 2023. Refers to constituents of the MSCI EM IMI.

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Notes: Chart on the left-hand side indicates average percentages of emissions from Scope 1+2 boundaries, Scope 3
upstream boundaries and Scope 3 downstream boundaries. The center chart indicates percentages of companies
that aim to reduce Scope 1 and 2 emission, Scope 1, 2 and 3 upstream emissions, Scope 1, 2 and 3 upstream anddownstream emission and Scope 1 and 2 and undefined categories of Scope 3 emissions in the final target year.
Chart on the right-hand side indicates average percentages of total emissions covered by targets in each GICS
sector.

Meanwhile, upstream and downstream supply chain emissions constitute by far the largest portion of
the carbon footprint across all four indexes. As operational and market risks associated with Scope 3
emissions start impacting businesses, for example, through reduced demands for carbon-intensive
products and services, we may see more Scope 3 emissions targets emerging.
Companies that set Scope 3 targets may demonstrate a broader climate risk awareness andstrategy than peers that do not, potentially indicating greater preparedness to manage transitionalrisks tied to their products and supply chains.
Our analysis of the MSCI target-level data showed that the comprehensiveness or emissions
coverage rate of companies’ climate targets depends greatly on the status of their Scope 3 target
setting. As more progress is made in Scope 3 emissions disclosures and target-setting, we may see
greater alignment between the emissions scopes covered by targets and the boundaries ofcompanies’ GHG emissions.

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Modelling target-based emissions projections using a Target
Summary Model
Understanding the MSCI Target Summary Model
Climate targets are a key component of the TCFD recommendations, used by companies andinvestors to assess and manage relevant climate-related risks.20 They may continue to be a corebuilding block within corporate climate change strategies, with an increasing number of companies
setting some type of targets aiming for a target year of 2023 and later (e.g., 48% of the MSCI ACWI
Index constituents had some type of target, as of June 2023, vs. 6% in 2015).
Using the MSCI Target Summary Model, MSCI ESG Research has aimed to standardize theassessment of corporate climate targets and provided an estimate of each company’s target-based
projected emissions. However, company climate targets can be varied, divergent and complex.
Modelling the future emissions of companies based on their climate targets requires corporate
disclosures that specify several factors, including targeted emissions by scope, target type (e.g.,absolute or intensity-based) and the timeline of emissions reduction.
The Target Summary Model projects companies’ future emissions only when companies havedisclosed targets to this level of detail. In the absence of a climate target with sufficient detail, MSCIESG Research assumes a default emissions increase of 1% per year.
Sufficiently granular target-level data can thus be a key input when modelling the emissions
trajectories of companies. In this section, we summarized seven types of data points that are
required for emissions projections and progress of emissions reduction under the Target Summary
Model. These target-level data points are relevant not only in modelling emissions projections, butthey can also be key discussion points in issuer engagement efforts. The data points are as follows:
1.

Target type (e.g., absolute or intensity target. If intensity, intensity type)2.

Targeted scopes and categories

3.

Emissions reduction percentages

4.

Base year and base year emissions

5.

Targeted year and targeted year emissions

6.

Reported year and reported year emissions

7.

Coverage ratios of targeted scopes and categories

Appendix I gives examples of data from a hypothetical company to illustrate how the Target
Summary Model standardized a company’s target-level data and projected its future emissions.
Companies’ target disclosures often lack specific information regarding a target’s baseline year,
baseline value for calculating GHG emissions reductions, target coverage, targeted reduction, as
well as targeted year and expected emissions at the target year. These are regarded criticalinformation, without which MSCI ESG Research cannot project a company’s emissions into the
future.

20”Breaking down corporate net-zero targets.” MSCI ESG Research, May 2020.

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For certain cases, however, where the target description includes some critical information but ismissing one partial element, MSCI ESG Research can use previously reported emissions data or
minimal calculations to complete the target description and process the target into a company’s
future emissions projection.
By applying the imputations shown in Appendix I, MSCI ESG Research can process morecompanies’ targets into projected emissions and may provide a more accurate view of a company’s
decarbonization efforts. Of the 9,181 MSCI ACWI IMI constituents, 4,384 companies set ongoingclimate targets for target years of 2023 and beyond, as of June 2023.
Of the 4,384 companies with climate targets, 2,014 companies disclosed sufficient data for the MSCI
Target Summary Model to estimate their emissions projections and 2,370 companies set climate
targets, but they did not report sufficient data for the projection. Of the 2,014 companies that
disclosed sufficient target-level data, 727 companies set SBTi-approved targets and 1,287
companies set targets that are not approved by the SBTi standard.
To see if aiming for this type of global standard might strengthen the likelihood for companies toachieve their targets, we compared the differences between the targets of companies that had
committed to the SBTi standards (SBTi Group), and those that had not done so (Non-SBTi Group) in
the following analysis.
Exhibit 8: Target variability of MSCI ACWI IMI constituents under the Target Summary Model

Source: MSCI ESG Research, June 30, 2023. Refers to constituents of the MSCI ACWI IMI.

The Target Summary Model estimates about 1% p.a. emissions growth for companies that did not
set climate targets or did not report sufficient granularity in target-level data. The Target Summary
Model also estimates 1% p.a. emissions growth from scope or category of GHG emissions notcovered by a company’s climate targets. The chart below illustrates the classification of emission
projections into six different trends.

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Exhibit 9: Examples of target-based emission projections under the Target Summary Model

Source: MSCI ESG Research

The Target Summary Model imputes high emissions reduction percentages when companies set
net-zero emissions reduction targets. This imputation model resulted in high percentages ofcompanies in both SBTi and Non-SBTi groups (i.e., 41% and 32%) that showed high emissions
reduction trends. All in all, higher proportions of companies in the SBTi Group showed decreasing
emissions trends than companies in the non-SBTi Group under the MSCI Target Summary Model(i.e., 61% and 42%).
Exhibit 10: Examples of target-based emission projections for SBTi and Non-SBTi groups in
the MSCI ACWI IMI

Source: MSCI ESG Research, June 30, 2023. Refers to constituents of the MSCI ACWI IMI.

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Target-based emissions projections using target credibility assessments
At the COP 27 climate conference in Egypt, the United Nations’ High-Level Expert Group on the NetZero Emissions Commitments of Non-State Entities (Expert Group) underscored the need for action
on corporate climate pledges, calling for companies and financial institutions to back up their climate
commitments with action and investment.
Using MSCI’s Climate Change Metrics, we have outlined a climate change target assessment
framework to determine what steps companies have taken to achieve their corporate climate targets.
This assessment covers several key indicators recommended by GFANZ. We determine a credibility
weight based on the target assessment and allocate the weight to each scope’s projected emissions.
The greater the credibility of a company's target, the closer we project their emissions to that target.
For instance, the weight allocated in the example below is 25% (out of a maximum of 100%).
Exhibit 11: Examples of projected company emissions based on target credibility
assessments

Source: MSCI ESG Research

Referring to the GFANZ recommendations, we apply the following credibility assessment formula.
We apply it for each GHG scope projected emissions, using a total credibility weight.
We use a mix of forward- and backward-looking indicators that result in a score between 0% and100% (e.g., 25% credibility on Scope 1 projections). For each scope, the maximum credibility weightis 100%. SBTi defined near-term targets, for instance, as emissions reduction targets for the next 5
to 10 years.
The SBTi at the time of this research no longer validates targets for oil & gas companies, so weredistribute a specific weighting to the oil & gas companies.
Within eligible companies in the MSCI ACWI IMI (approximately 2,000 companies), only a minority
manage to get a full credibility weight of 100% for a given scope.

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Exhibit 12: Examples of target credibility assessment metrics
Question

FactorScope
specific?

Weight w (adds up to 100%)

Does the company
have any short-termtargets?

Target year

Scope-specificweighting

40% for having at least one target set
between 2020 and 2030

Does the company
have third party
verified targets?

SBTi approved target(s)20% for having only target(s) beyond 2030

Companywide weighting

Yes = 20%
No = 0%*Not applicable for oil & gas companies
Does the company
have a good trackrecord of achieving
targets in the past?

Record on achieving
targets

Is the company
currently achieving
targets?

Being (linearly) on trackto achieve targets% of past targets achieved * 20%*For oil & gas companies, % of pasttargets achieved * 30%

On track for at least some targets = 20%
Not on track to meet any targets = 0%

*For oil & gas companies, On track for atleast some targets = 30%

Source: MSCI ESG Research

Exhibit 13: Results of target credibility assessments per target scope

Source: MSCI ESG Research. Data as of April 2023

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How successfully a company has been in reducing its emissions relative to its ongoing targets may
also add useful context. Specifically, taking historical emissions performance and benchmarking it
against a company’s targeted trajectory can offer a helpful sense check. In this track record analysis,
we drew a linear target trajectory, linking base year emissions to target year emissions.
By comparing a company’s reporting year emissions with its target trajectory, we assume thatcompanies are on track to meet their climate targets if their reporting year emissions are below its
target trajectory in the reporting year. By contrast, the steeper a company’s target trajectory relative
to its base year emissions trend, the more drastic its future mitigation efforts will need to be to meet
its targets (Exhibit 14).
Exhibit 14: Examples of track record analysis for ongoing targets

Source: MSCI ESG Research. Based on a hypothetical company. Notes: SBTi was developing a guide on whatcompanies are required to report for target progress at the time of this research. The SBTi aims to complete thedevelopment of the SBTi progress framework by COP28. Please see SBTi. “Measurement, Reporting and Verification(MRV).” Last accessed as of March 1, 2023.

Using these target credibility assessment metrics, we have compared the target credibility weights
for constituents of the MSCI ACWI IMI that had set SBTi-approved targets (SBTi group) and thosethat had set targets that are not approved by the SBTi standard. (non-SBTi group).
We found that about 95% of companies in the SBTi Group had a 40% credibility assessment
for their Scope 1+2 targets, compared to about 80% for companies in the Non-SBTi Group.21
The difference between the SBTi and Non-SBTi Groups was more apparent in their Scope 3 target
credibility assessments. About 71% of companies in the SBTi Group had a 40% credibility
assessment for their Scope 3 targets, compared to only 24% of companies in the Non-SBTi
Group.
Further we found that about 70% of companies in the SBTi Group made emissions reduction
progress at least for one of targets, compared to 55% of companies in the Non-SBTi Group.
Overall, companies in the SBTi Group have had higher credibility weights in achieving their targets
than ones in Non-SBTi Group. This may suggest that companies that went through a rigorous third21 40% is full credibility weight for target year (please see Exhibit 12).

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party target-validation process under the SBTi standards were more likely to have disclosed targetlevel data, increased the transparency of their emissions-reduction strategies, and made further
progress on emissions reduction activities.
Exhibit 15: Examples of target credibility assessments for SBTi and Non-SBTi groups of MSCIACWI IMI constituents

Source: MSCI ESG Research, June 30, 2023

Achieving climate targets remains a more demanding prospect than in setting them. However, theresults of these assessments highlighted how rigorous third-party validation processes, like thoseunder SBTi, could offer scope to enhance the transparency of corporate decarbonization strategies
and to improve the likelihood that the companies can achieve such climate targets.22

22 “Assessing Science-Based Corporate Climate Target-Setting.” MSCI ESG Research. June 2023.

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Impact analysis using Implied Temperature Rise (ITR)
MSCI’s Implied Temperature Rise (ITR) computes the forward-looking temperature alignment ofcompanies, portfolios and funds with global temperature goals. ITR is designed to help investors
evaluate how companies and portfolios manage their “fair share” of decarbonization efforts to limit
global warming.
To do so, ITR allocates a carbon budget to companies, which can be aggregated at portfolio level.
The model then extrapolates this value to estimate planetary warming to a 2100 horizon if the global
economy had the same carbon budget overshoot or undershoot as a given company or portfolio. For
instance, an ITR in excess of 2°C signals that company climate targets are not ambitious enough to
be compatible with a 2°C world. New company targets are dynamically integrated in ITR model,
which helps investors set portfolio temperature objectives and engage with companies.
ITR is also designed to provide information on the alignment of financial activities with a well-below
2°C scenario, as recommended by the Task Force on Climate-related Financial Disclosures.23 Thisis the key focus of this report.
See full methodology guide on www.msci.com/our-solutions/climate-investing/implied-temperaturerise.
Exhibit 16: Model steps overview for Implied Temperature Rise1) 1.55°C is the baseline temperature of the REMIND Net Zero 2050 NGFS scenario. Any overshoots/undershoots of the benchmark are relative to this 1.55°C baseline.
2) IPCC AR6 Report (Summary for Policymakers): “Each 1000 GtCO2 of cumulative CO2 emissions is assessed to likely cause a 0.27°C to 0.63°C increase in global surface
temperature with a best estimate of 0.45°C”

Source: MSCI ESG Research

23 “Guidance on Metrics, Targets, and Transition Plans.” Task Force on Climate-related Disclosures (TCFD), October 2021.

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In 2023 MSCI ESG Research implemented a series of updates to the ITR methodology based on thelatest best practice guidance for measuring portfolio alignment published by the Glasgow Financial
Alliance for Net Zero (GFANZ).24 The updated methodology:
•

•

•

•

Features sector-specific pathways for limiting warming to 1.5°C. The metric now aligns with
open source 1.5°C decarbonization pathways provided by the Network of Central Banks andSupervisors for Greening the Financial System (NGFS) and developed by climate scientists.25 (Itpreviously aligned with 2°C pathways based on high-level assumptions from the U.N.
Intergovernmental Panel on Climate Change.) The change also aligns the metric fully with
GFANZ’s recommendation that portfolio alignment metrics should reflect differences indecarbonization pathways for specific sectors and regions. A company’s pathway in the Indiancement sector, for example, now reflects the sector’s ability to transition to net-zero based on
scientific assumptions.
Brings forward to 2050 the time horizon for reaching net-zero. MSCI ESG Researchassumes that the world can reach net-zero by midcentury, based on the NGFS REMIND Net
Zero 2050 scenario. The metric previously assessed companies’ decarbonization based on a
scenario where the world reached net-zero emissions by 2070, in line with a 2°C pathway.
Weighs the credibility of corporate decarbonization targets. We now adjust projectedcompany emissions for credibility instead of taking any climate target at face value. To define a
credibility weight, we assess whether a company has at least one short-term target for each
emissions scope, at least one target validated by the Science-Based Targets initiative (SBTi), a
record of achieving past targets, and a current trajectory to meet at least some of its futuretargets. Because SBTi does not currently validate decarbonization targets for oil and gas
companies, we consider whether such companies are on track to meet at least some of theirtargets.26
Fine tunes the calculation of companies’ remaining carbon budgets. Our latest
methodology allocates a carbon budget to each company starting Jan. 1, 2020 and ending in
2050, based on the company’s 2019 revenue and NGFS revenue-intensity pathways.27 Rather
than recalculate the budget based on new annual revenue data as our methodology directed
previously, we now update what remains of the company’s initial emissions budget based onwhether the company gained or lost market share during the previous year. A company’s
economic performance can only influence the budget if it increases or decreases the company’smarket share. This ensures company carbon budgets are redistributed within a sector, consistent
with the reality of a limited global budget.28 In addition, we subtract from each company’s
remaining carbon budget the reported and estimated quantity of greenhouse gases emitted by
the company in the prior year. Realized company emissions now count towards decreasing
carbon budgets.

24 “Measuring Portfolio Alignment: Driving Enhancement, Convergence, and Adoption.” GFANZ, November 2022.
25 “NGFS Climate Scenarios for central banks and supervisors.” NGFS, Sept. 6, 2022.
26 “Oil and Gas: Next Steps for the SBTi’s Guidance Development.” SBTi, Jan. 12, 2023.
27 Revenue intensity refers to the amount of carbon a company emits to generate every USD 1 million of revenue. See“Understanding MSCI’s Climate Metrics,” MSCI ESG Research, January 2023.
28 Market share reflects a company’s revenue as a proportion of global revenue for its main MSCI emissions sector.

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Because of this switch from the current ITR model to the updated model for this 2023 portfolio
analysis, we note that comparison with ITR data previously reported by GPIF has some limits. In
addition, the updated ITR model outputs used in this report are simulated results.29
This report section analyzes the following elements:•

Changes in ITR output at the GPIF total portfolio as of March 31, 2022 (FY2021), using thecurrent model vs the updated model.30•

Change in the GPIF total portfolio ITRs from FY2021 to FY2022 (as of March 31, 2023), using
the updated model.

•

Asset class level ITRs within the total GPIF portfolio as of FY2022.

•

GICS sector level ITRs for each four-asset class (Yen Equity, Non-Yen Equity, Yen Fixed
Income, and Non-Yen Fixed Income) in the FY 2022 GPIF portfolio, using the updated model.

Exhibit 17: Difference between current ITR model (green bars on the left) and updated ITR
model (blue bars on the right) per asset class for FY2021 GPIF portfolio

Source: MSCI ESG Research, April 1, 2023
Notes: Unless otherwise noted, updated ITR results in this report were based on simulated results as of April 2023

The chart above shows that, aside from the Yen Equity portfolio, the model changes do notsignificantly impact broad asset class or regional aggregated outputs, even though individual sectors
or issuers may be more significantly impacted.
Similarly, when applying the updated ITR model to the total GPIF portfolios (Yen, non-Yen, both
equities and Fixed Income) retroactively over the last two years between FY2021 and FY2022, theoutput remains stable at 2.5°C. A broad portfolio is influenced by the state of the economy – which iscurrently not on track to meet the objectives of the Paris agreement. While the GPIF portfolio
appears “misaligned” with global climate goals, a portfolio ITR is best understood in relative terms.
29 Please note that updated ITR results were based on simulated results as of April 2023. The results using the published data may

differ from the simulated results.
30 Unless otherwise noted, updated ITR results in this report were based on simulated results as of April 2023.

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The GPIF portfolio is in fact more aligned than the MSCI ACWI IMI which displays an ITR of 2.6°C.31
This shows that while the GPIF portfolio is “misaligned”, it performs slightly better than the broad
investment universe in which GPIF operates. However, when focusing on Yen Equities, we find that
the GPIF Yen Equities portfolio (2.5°C) is slightly less aligned than its local benchmark (Japan
Equities: 2.4°C in updated ITR model).32
Exhibit 18: GPIF portfolio-level ITR in FY2021 and FY2022

Source: MSCI ESG Research, April 1, 2023
Notes: Unless otherwise noted, updated ITR results in this report were based on simulated results as of April 2023

However, the proportion of 2°C-aligned companies in the portfolio increased slightly from 27.2% in
FY2021 to 27.6% in FY2022.

Exhibit 19: Distribution of company ITR Bands in the GPIF total portfolios in FY2021 andFY202231 Based on simulated results as of July 6, 2023.
32 Based on simulated results for the MSCI Japan Index as of July 6, 2023.

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Source: MSCI ESG Research, April 1, 2023
Notes: Unless otherwise noted, updated ITR results in this report were based on simulated results as of April 2023

Exhibit 20: Distribution of issuers per updated ITR status in the GPIF total portfolios in FY
2022

Source: MSCI ESG Research, April 1, 2023
Notes: Unless otherwise noted, updated ITR results in this report were based on simulated results as of April 2023

Climate targets are a key input for the ITR model, which can also be analyzed on a standalone
basis. The companies that have set no target has decreased from 36.9% in FY2021 to 34.3% in
FY2022. The proportion of the companies with sufficient target-level data disclosure (covering data
points that we assess under the MSCI Target Summary Model) has also increased to 34.5% (i.e.,
12.5% of companies with SBTi-approved targets and 22.0% with some targets) in FY2022 from
34.1% (i.e., 12.4% of companies with SBTi-approved targets and 21.7% with some targets) in
FY2021. The share of issuers with targets approved by the Science-Based Targets Initiative (SBTi)
remained almost the same at 12.4% in FY2021 and 12.5% in FY2022.

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Exhibit 21: Changes in the proportions of issuers with SBTi-approved targets, clear climate
targets and no clear target in the GPIF total portfolios in FY2021 and FY2022

Source: MSCI ESG Research, April 1, 2023
Notes: Unless otherwise noted, updated ITR results in this report were based on simulated results as of April 2023.

By contrast with the current ITR model, the updated ITR model does not take corporate climate
targets at face value (i.e., assuming they will be fully followed through and achieved). Instead, using
guidance from the GFANZ Portfolio Alignment recommendations, MSCI ESG Research hasdeveloped a target credibility assessment whereby the influence of climate targets on projected
emissions is moderated to some extent by a credibility weighting.
The assessment applies to all three GHG emissions scopes. It takes into account the existence ofshort-term targets, third party verification (typically undertaken by SBTi), the issuer’s track record forachieving past targets, and progress towards current targets. The details of these weighting
indicators are described in a methodology note (accessible here). As illustrated in the following
diagram, since some targets are discounted, the updated ITR model produces “hotter” values across
GPIF’s invested asset classes when compared to the same model without the target credibility
assessment feature.

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Exhibit 22: Comparative analysis of ITR values in the GPIF FY2022 portfolio when taking
targets at face value, versus including a target credibility component

Source: MSCI ESG Research, April 1, 2023
Notes: Unless otherwise noted, updated ITR results in this report were based on simulated results as of April 2023

We performed this comparative analysis of ITR based on targets at face value vs. ITR based on
credible targets across GICS sectors, both for GPIF’s Yen and non-Yen equity portfolios in FY2022.
Both the Yen and non-Yen portfolios showed systematically lower ITR values when targets are taken
at face value, in every sector. Sectors such as materials, energy, industrials and utilities showed
higher discrepancy and/or higher ITR values. This may reflect greater gaps between target ambition
and measurable emissions reduction progress towards those targets. We saw similar results when
doing the same analysis on Yen and non-Yen fixed income portfolios.
Exhibit 23: Comparative analysis of ITR values for Yen and Non-yen Equities in the GPIFFY2022 portfolio when taking targets at face value, versus including a target credibility
component

Source: MSCI ESG Research, April 1, 2023
Notes: Unless otherwise noted, updated ITR results in this report were based on simulated results as of April 2023

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Exhibit 24: Comparative analysis of ITR values for Yen and Non-yen fixed income
investments in the GPIF FY2022 portfolio when taking targets at face value, versus including
a target credibility component

Source: MSCI ESG Research, April 1, 2023
Notes: Unless otherwise noted, updated ITR results in this report were based on simulated results as of April 2023

In conclusion:•

Applying the updated ITR model, the proportion of Paris-aligned companies, especiallyaligned with 2.0°C, has slightly increased in the GPIF portfolios between FY2021 andFY2022. This also reflects the fact that more MSCI ACWI IMI companies have strengthened
their net-zero ambitions in recent times.

•

GPIF’s total portfolio-level ITR remains stable between FY2021 and FY2022, using the
updated ITR model. At 2.5°C, it remains misaligned with the goals of the Paris Agreement. It
is however performing slightly better than a benchmark (MSCI ACWI IMI: 2.6°C), which
illustrates the scale of the challenge to meet the Paris Agreement targets. This nonsignificant difference can be explained by the fact that a large part of GPIF’s total portfolio is
passively managed.

•

The proportion of companies with climate targets, including SBTi-approved targets, has also
increased during the same period. This is a positive change towards a “cooler” portfolio ITR.

•

When taking corporate targets at face value, the GPIF ITR values would decline by 0.2°C.
However, the target credibility assessment feature makes ITR values hotter by increasing
company projected emissions, particularly in certain sectors.

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Climate-related risks for the sovereign bond portfolio
MSCI Sovereign Bond Climate Value-at-Risk
We conducted an analysis on the potential impact of climate change and economic decarbonization
on sovereign bonds using the MSCI Sovereign Bond Climate Value-at-Risk (VaR).33 The MSCI
Sovereign Bond Climate VaR estimates the change in the sovereign yield curve when market
expectations move from a climate-agnostic baseline expectation to any other climate scenario. We
use the framework put forward by the Network for Greening the Financial System (NGFS) and theirscenarios for interest rates under various climate change scenarios.
Based on the NGFS scenarios, we derived potential shocks to sovereign bond yield curves, and,using our stress testing capabilities, we used these shocks to reprice sovereign bonds in our
Sovereign Bond Climate VaR model. These scenarios predominantly focus on transition risks andincorporate to some extent the impact of chronic physical risks, 34 but acute physical risks are not yet
part of the macroeconomic modeling in the NGFS scenarios.
The below illustrates the workflow:•

The scenarios are based on interest rate projections for the one- and ten-year sovereign interest
rate in the NGFS scenarios. Those scenarios include a range of climate scenarios as well as aclimate-agnostic baseline scenario.

•

We then estimate how today’s yield curve would look if markets priced a given scenario and its
interest rate projections.

•

The difference between the implied yield curve from a climate scenario and the baseline
scenario gives us the ‘shock’ we would observe if markets changed expectations from theclimate-agnostic baseline to a particular climate scenario.

•

This yield curve shock is then the input into a stress test which reprices a universe of sovereign
bonds. The inflation shocks are also included in a similar way.

NGFS scenarios
In line with the TCFD recommendations, the Network for Greening the Financial System (NGFS), agroup of central banks and supervisors, implemented a set of hypothetical scenarios for climatechange. They developed six scenarios with varying severity of physical risks (hot house world
scenarios versus scenarios with lower physical impacts) and varying degrees of transition risks(going from an orderly transition to delayed and disorderly transitions). To conduct analysis on the
GPIF portfolio, we used five scenarios except for Current Policies. In the Current Policies scenario,
the impacts on inflation rate are negligible reflecting not only limited transition risk but also the factthat only one potential physical risk transmission channel (productivity) has been modelled.35

33 Scenarios analysis under the MSCI Sovereign Bond Climate Value-at-Risk predominantly focus on transition risks and incorporate

to some extent the impact of chronic physical risks, but acute physical risks or low carbon technology opportunities were not yet
part of the macroeconomic modeling in the NGFS scenarios.
34 Chronic physical risks are related to longer-term shifts in climate patterns, such as sustained higher temperatures, that may cause

sea level rise or chronic heat waves.
35 “NGFS Scenarios for central banks and supervisors.” NGFS, September 2022.

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Exhibit 25: NGFS scenario framework

Note: NDCs stand for Nationally Determined Contributions. Source: Network for Greening the Financial System

In September 2022, NGFS published the third climate scenario (phase III scenarios), an updated setof climate scenarios reflecting the latest trends including the new country-level commitments toreach net-zero emissions, the latest GDP and population pathways.36

Results for GPIF’s sovereign bonds portfolio
We ran an analysis for GPIF’s latest portfolio as of the end of March 2023 (FY2022) using phase III
scenarios.37 In addition, to compare the results using the previous version of scenarios (phase II
scenarios) that were included in GPIF’s report last year “GPIF 2021 ESG Report”, we also ran
FY2022 portfolio using phase II scenarios and compare the results of FY2021 portfolio using phase
II scenarios for countries that accounted for the highest portion of market caps (Exhibit 26). While we
did not find a change in the order of results by scenario between FY2021 and FY2022 using phaseII, the UK bonds incurred smaller losses especially for Divergent Net Zero scenario. This was partly
because the UK bonds that were newly added in FY2022 portfolio had relatively low impacts.

36 “NGFS publishes the third vintage of climate scenarios for forward looking climate risks assessment | Banque de France.” NGFS,

September 6, 2022.
37 Please note that the results were based on pro-forma data that we computed for GPIF as of June 2023. The results using the

published data may differ from the results based on pro-forma data.

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Exhibit 26: Sovereign bond Climate VaR results by country for the GPIF portfolio using NGFS
phase II scenarios (FY2021 vs. FY2022)

Source: MSCI ESG Research

We also compared the results for the FY2022 portfolio between NGFS phase II and phase III
scenarios (Exhibit 27). We found that the losses were generally more severe under the Phase III
scenarios, especially for the Divergent Net Zero scenario. Also, notably for U.S. bonds, Divergent
Net Zero scenario showed the largest negative return in phase III, whereas in phase II, Net
Zero 2050 scenario showed the largest negative return for U.S. bonds. This was partly because
yield curve shocks were higher in phase III than those in phase II especially for Divergent Net Zeroscenario for most year/tenor (Appendix II). NGFS assumed that in the disorderly scenarios policy
uncertainty may lead to a higher investment premium, lasting for two years, with the premium
gradually returning to baseline thereafter, which occurs in the period 2021-2022 in the Divergent Net
Zero policies scenario and 2030-2031 in the Delayed Transition scenario.38

38 “NGFS Scenarios for central banks and supervisors.” NGFS, September 2022.

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Exhibit 27: Sovereign bond Climate VaR results by country for the GPIF portfolio for FY2022(NGFS phase II scenarios vs. phase III)

Source: MSCI ESG Research

We took a closer look at the results using phase III scenarios for Japan and U.S. sovereign bonds of
FY2022 portfolio as those two countries accounted for the highest portion of holdings: Japan forabout half and U.S. for about a quarter in FY2022 sovereign bonds portfolio of GPIF.
Both Japan and the U.S. experienced the largest impacts under the Divergent Net Zeroscenario (Exhibit 28 and 30). Also, both countries’ relatively longer maturity bonds (in buckets
10-20 years and 20+ years) experienced the largest impact (Exhibit 29 and 31). Focusing on the
Divergent Net Zero Scenario, while the impacts under those relatively longer maturity bonds werehigher for the U.S. than those for Japan, the portfolio weights of those bonds were higher for Japan
than those for U.S., which led to similar impacts (Japan of -6.6% and U.S. of -6.4%).

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Exhibit 28: Sovereign bond Climate VaR results for Japanese bonds in the FY2022 GPIF
portfolio using NGFS phase III scenarios

Source: MSCI ESG Research

Exhibit 29: Sovereign bond Climate VaR results for Japanese bonds in the FY2022 GPIF
portfolio using NGFS phase III scenarios and across different time to maturity buckets (return%)

Time tomaturity

WeightNet Zero
2050

Below 2Degrees

Divergent
Net Zero

DelayedTransition

Nationally
Determined
Contributions

1- years

2.3%

-0.2

-0.1

-0.3

0.0

-0.1

1-5 years

36.8%

-1.3

-0.4

-1.9

-0.2

-0.4

5-10 years

21.0%

-3.9

-1.3

-6.6

-0.6

-1.4

10-20 years

25.5%

-7.2

-3.0

-12.6

-1.9

-2.8

20+ years

14.5%

-5.1

-2.2

-8.8

-2.6

-1.9

Total

100.0%

-3.9

-1.5

-6.6

-1.0

-1.4

Note: Weight assumes that the portfolio consists of only Japanese sovereign bonds.
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Exhibit 30: Sovereign bond Climate VaR results for U.S. bonds in the FY2022 GPIF portfolio
using NGFS phase III scenarios

Source: MSCI ESG Research

Exhibit 31: Sovereign bond Climate VaR results for U.S. bonds in the FY2022 GPIF portfolio
using NGFS phase III scenarios and across different time to maturity buckets (return %)Time tomaturity

WeightNet Zero
2050

Below 2Degrees

Divergent
Net Zero

DelayedTransition

Nationally
Determined
Contributions

1- years

1.5%

-0.1

-0.1

-0.5

0.0

-0.1

1-5 years

52.6%

-2.0

-0.9

-3.2

-0.1

-0.5

5-10 years

25.0%

-5.1

-2.2

-7.7

-0.3

-1.4

10-20 years

7.7%

-9.2

-4.3

-14.1

-2.6

-2.8

20+ years

13.3%

-8.3

-4.1

-12.7

-3.6

-2.6

Total

100.0%

-4.1

-1.9

-6.4

-0.8

-1.2

Note: Weight assumes that the portfolio consists of only U.S. sovereign bonds.
Source: MSCI ESG Research© 2023 MSCI Inc. All rights reserved.

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Climate-related risks on the real estate portfolio
MSCI Real Estate Climate Value-at-Risk
Buildings are a significant source of global greenhouse gas (GHG) emissions as well as a key driverof energy consumption.39 Thus buildings may play an important role in a country’s decarbonization
efforts. At the same time, physical risks exacerbated by climate change are increasingly affecting
assets, e.g., through damages caused by rising sea levels or strong winds. Using the MSCI Real
Estate Climate Value-at-Risk (VaR), we conducted an analysis of the GPIF’s investments incommercial and residential real estate as of the end of March 2023 (FY2022) to evaluate the risks ofboth climate transition policy and physical climate-related impacts in their portfolio.40
The Transition Policy Risk Model
The Transition Policy Risk model assesses the potential cost impact from a transition to a lowcarbon economy under different scenarios.
In the Transition Policy Risk computation, reduction requirement pathways are derived from theemissions pathways of each region and sector, which are the outputs of Integrated Assessment
Models (IAM). These reduction requirements are combined with property-specific data such asenergy intensity and building carbon intensities.
Real estate emissions at the building level can be separated in different categories according to theGreenhouse Gas Protocol.
•

Scope 1 emissions are direct emissions related to fossil fuel burnt on-site and fugitive emissions
related to fluorinated gases.

•

Scope 2 emissions are indirect emissions related to the consumption of electricity and district
heating / cooling.

•

Scope 3 emissions are indirect emissions from any other downstream or upstream activities
such as tenants’ emissions. In the real estate sector, tenants’ emissions are one of the main
sources of Scope 3 emissions. In the MSCI Real Estate Climate VaR model, we include theseemissions included in Scope 1 and 2.

In the MSCI Real Estate Climate VaR model, all these emissions are ultimately summed todetermine the collective emissions related to building use. Decarbonization pathways also use this“whole building” emissions approach.
Emissions pathways are computed using NGFS data. In the MSCI Transition Climate VaR model,
costs are computed until 2050 and are considered null afterwards.41
39 “Energy Efficiency: Buildings.” IEA. 2019.
40 Please note that the results were based on pro-forma data that we computed for GPIF as of July 2023. The results using the

published data may differ from the results based on pro-forma data.
41 The reason for this is manyfold. Many countries, companies and investors have set net zero emission targets and many countries

already have their net zero targets codified in law or in policy documents. Taking these targets at face value would have most of theclimate transition over by the objective date of 2050. This would mean that costs related to reducing emissions or complying withregulations would be over around 2050. There is uncertainty around how climate transition policies could evolve after 2050 and thecosts associated with them given that the most economically viable reductions would have been made between today and 2050.
The only reductions left would be from very hard to abate sources that would have massive marginal abatement costs that are nolonger economically viable.

© 2023 MSCI Inc. All rights reserved.

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First, we calculate country/property type-specific intensity pathways per scenario, country andsector. We obtain the regional absolute emissions pathways and regional floor area pathways of thebuilding stock from the REMIND IAM and NGFS. We then calculate the regional carbon intensity
pathways by dividing the regional absolute emissions pathways by the regional floor area pathways.
The pathways for each country and property type until 2050 are obtained by scaling down theregional carbon intensity pathways.
Secondly, we calculate asset-level emission intensity based on reported total emissions or reported
energy consumptions. If total emissions or energy consumptions are not provided by the client, thencountry and property type-specific market averages are used as a proxy. In the case of assets
located in Japan, the CRREM (Carbon Risk Real Estate Monitor) emission intensity values are used
as a basis to compute the market average emission intensities.
By using the decarbonization pathway for a specific asset, based on the data calculated in the firststep and the asset’s current intensity from the second step, we calculate intensity reduction
requirements.
By multiplying the intensity reduction requirements with the floor area of the building, we calculate
emission reduction requirements. We then multiply the emission reduction requirement with thecarbon price obtained from the REMIND IAM to calculate yearly costs. Please note that the modelcannot fully predict cost allocations. For example, some transition costs may be shared with thebuildings’ tenants. The total net present value is calculated by discounting the entire cost timeseries
until 2050 using a Real Estate Model specific discount rate of 7.4%.42 Finally, Transition Policy VaR
is calculated as the present value of cost in relation to property value.
The Physical Risk Model
The Physical Risk model assesses the potential cost of climate hazards on buildings, using climate
data for the given locations of assets incorporating the hazards of extreme heat, extreme cold, fluvial
and coastal flooding, tropical cyclones and wildfire.
For real estate, the Physical Risk model analyzes building damages caused by extreme weather
events and additional costs related to temperature changes (e.g., additional cooling costs). It covers
the chronic physical risks of extreme heat, extreme cold, as well as the acute physical risks of fluvial
flooding, coastal flooding, tropical cyclones, and wildfire.
The core cost functions due to either damage or increased heating and cooling are shown below:•

Damage cost computations follow the equation: Costs from acute risk impacts = hazard intensity* percentage of building damage for given intensity * property value•

Additional chronic heating and cooling costs follow the equation: Costs = number of days withextreme temperature * additional cooling/heating requirements per day * costs per kWhFirst, we analyze climate scenarios to identify changes in extreme event frequency and intensity until
the end of the century. Second, we extract physical hazard information such as the number of days
with extreme temperature or the wind gust modeled for a tropical cyclone. Then we derive realestate sector vulnerabilities for simulated physical hazard intensities. Vulnerability is expressed aspercentage of building value damaged per event. Additional cooling/heating requirements per day
are expressed in kWh per square meter. Costs are calculated using the equations defined above inthis section. Additional future costs are discounted at an annual rate of 7.4 % as we do for the
42 Global average annualized total return of the MSCI Global Property Index.

© 2023 MSCI Inc. All rights reserved.

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Transition Policy Risk model to present the net present value. Finally, Physical Risk VaR iscalculated as the present value of the aggregated additional future costs in relation to property value.
MSCI ESG Research uses a probabilistic modeling framework to determine the distribution of theannual cost from weather extremes for assets at a given location. This approach allows us todetermine the average cost from climate change while also exploring the possibility of much more
severe outcomes. We calculate the average scenario by considering the expected value of the cost
distribution. We used this average scenario for the analysis of GPIF portfolio.

Results for GPIF’s real estate portfolio
The real estate portfolio of GPIF contained reported energy consumption data for nearly half of theassets. Where available, the reported energy consumptions were used to compute emissions,otherwise emission intensity proxy numbers based on CRREM data were used.
Physical Risk VaR was the lowest for the 1.5°C scenario and highest for 3°C scenario (Exhibit 32).
For hazard types, Coastal Flooding accounted for most of the Physical Risk VaR for GPIF’s FY2022
portfolio (Exhibit 32).

Exhibit 32: Physical Risk VaR of GPIF’s FY2022 domestic real estate portfolio across four
REMIND scenarios (Average)

Source: MSCI ESG Research“Average” refers to the use of average expected values from the model’s cost distribution

Based on absolute thresholds, we set the Financial Risk Category, which indicates an asset’s broadrisk level associated with a Climate VaR for a given scenario. Categories include: Severe Risk
(VaR<-25%), Significant Risk (VaR<-5%), Moderate Risk (VaR<-0.5%), Negligible Risk (VaR<0%),
No Identifiable Risk (VaR=0%), Negligible Risk Reduction (VaR>0%), and Risk Reduction(VaR>0.5%). In the REMIND 1.5°C Orderly scenario, while there was about 5% of assets under© 2023 MSCI Inc. All rights reserved.

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Severe Risk or Significant Risk due to coastal flooding, the majority of assets fell under Negligible
Risk (Exhibit 33).
Exhibit 33: Physical Risk VaR of GPIF’s FY2022 domestic real estate portfolio under the
REMIND 1.5°C Orderly scenario (Average) – percentage of capital value per risk category

Source: MSCI ESG Research“Average” refers to the use of average expected values from the model’s cost distribution

On the other hand, Transition Policy VaR showed the largest impact under 1.5°C REMIND Orderly
Scenario, SSP2 (Net Zero 2050), followed by 2°C REMIND Disorderly Scenario, SSP2 (Delayed
Transition), 2°C REMIND Orderly Scenario, SSP2 (Below 2 Degrees), and 3°C REMIND Hot House
World, SSP2 (NDCs) (Exhibit 34). This shows how stringent (1.5°C) policies designed to mitigate
carbon emissions in the real estate sector will increase costs, while 3°C scenarios will present thehighest physical risks.43 Ultimately, climate change risks may manifest through both transition andphysical risks. This real estate analysis may underscore the importance of considering climaterelated risks for alternative assets as well as traditional assets for a universal owner.
Exhibit 34: Transition Policy VaR of GPIF’s FY2022 domestic real estate portfolio across four
REMIND scenarios

Source: MSCI ESG Research

43 Note that the model cannot fully predict cost allocations. For example, some transition costs may be shared with the buildings’

tenants.

© 2023 MSCI Inc. All rights reserved.

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Appendixes
Appendix I: Understanding the MSCI Target Summary Model
The Target Summary Model projects companies’ future emissions only when companies havedisclosed targets beyond a threshold level of detail. In the absence of a climate target with sufficientdetail, MSCI ESG Research assumes a default emissions increase of 1% per year.
Exhibit 35: Process Flow for Incorporating Climate Target Data

Source: MSCI ESG Research, Climate Targets and Commitments Methodology, as of January 2022.
Notes: Intensity targets-based emissions projections depend on the growth rate chosen for the calculation’s
denominator. Absolute emissions can rise even if the headline intensity metric falls. The MSCI Target Summary
Model thus normalizes intensity-based targets by applying a 1% growth factor to the denominator (i.e., productionunit) over the period of the target.

Sufficiently granular target-level data is a key input when modelling the planned emissions
trajectories of companies. In this section, we summarize seven types of data points that are required
for emissions projections and progress of emissions reduction under the Target Summary Model.
These target-level data points are relevant not only in modelling emissions projections, but they canalso be key discussion points in issuer engagement efforts. The data points are as follow:
1.

Target type (e.g., absolute or intensity target. If intensity, intensity type)2.

Targeted scopes and categories

3.

Emissions reduction percentages

4.

Base year and base year emissions

5.

Targeted year and targeted year emissions

6.

Reported year and reported year emissions

7.

Coverage ratios of targeted scopes and categories

The table below shows examples of data from a hypothetical company to illustrate how the Target
Summary Model standardizes a company’s target-level data and projects its future emissions.

© 2023 MSCI Inc. All rights reserved.

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Exhibit 36: Hypothetical company example of projecting future emissions using climate
targets
Reported

Base

Target

Year

Year

Years

(6) 2020
Emissions(4) 2018
Emissions(7) Target(3) Reduction %Coverage

2030/2040/2050(5) 2030
Emissions2040
Emissions2050
Emissions(2) Scope 1 (MtCO2e)

5.1

6.81

100%

72%/ 100%/ 100%

1.91

0

0

Scope 2 (MtCO2e)

0.54

0.72

100%

72%/ 100%/ 100%

0.20

0

0

C1+2

1.85

2.03

100%

45% / 82% / 100%

1.16

0.37

0

C3

0.93

1.01

100%

45% / 82% / 100%

0.56

0.18

0

C4+9

0.11

0.84

100%

45% / 82% / 100%

0.46

0.15

0

C5

0

0

-

-

0.00

0.00

0

C6

0

0

-

-

0.00

0.00

0

C7

0

0

-

-

0.00

0.00

0

C8

0

0

-

-

0.00

0.00

0

C10

0

0

-

-

0.00

0.00

0

C11

2.35

2.79

100%

45% / 82% / 100%

1.53

0.50

0

C12

0

0

-

-

0.00

0.00

0

C13

0

0

-

-

0.00

0.00

0

C14

0

0

-

-

0.00

0.00

0

C15

0

0

-

-

0

0.00

0

10.88

14.2

-

-

5.82

1.20

0

Hypothetical Company(1) Absolute Targets

Scope 3
(MtCO2e)Total MtCO2e

Source: MSCI ESG Research. Based on a hypothetical company. The MSCI Implied Temperature Rise (ITR) model
uses estimated Scope 3 emissions per category across all companies to maintain consistency, as company
disclosures of this emission type vary considerably.

In the example above, a hypothetical company announced a net-zero target across Scope 1+2
emissions boundaries by 2040, and a net-zero target across all categories of its Scope 3 emissions
by 2050. Its decarbonization strategies also included interim 2030 and 2040 targets to reduce its
absolute Scope 1+2 emissions by 72% by 2030 and reduce Scope 3 emission by 45% and 82% by
2030 and 2040, respectively, both using 2018 as the baseline year.
We also note that the MSCI’s Implied Temperature Rise (ITR) Model (see following section)assesses a company’s temperature alignment, using its target-based emissions projection estimatedunder the Target Summary Model. The bold black line in the chart below is an illustration of acompany’s target-based emissions projection used in the ITR model.

© 2023 MSCI Inc. All rights reserved.

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Exhibit 37: Hypothetical company example of emissions trajectory and ITR

Source: MSCI ESG Research. Based on a hypothetical company.
Note: Illustration of projected emissions reduction assumed the hypothetical company would achieve the targets inthe stated target years. *The MSCI Implied Temperature Rise (ITR) model uses estimated Scope 3 emissions per
category across all companies to maintain consistency, as company disclosures of this emission type varies
considerably. MSCI Trajectory 2°C (Annual Budget) is based on current ITR model, while updated ITR model uses
1.5°C Trajectory.

Companies’ target disclosures often lack specific information regarding a target’s baseline year,
baseline value for calculating GHG emissions reductions, target coverage, targeted reduction, as
well as targeted year and expected emissions at the target year. These are regarded criticalinformation, without which MSCI ESG Research cannot project a company’s emissions into the
future.
For certain cases, however, where the target description includes some critical information but ismissing one partial element, MSCI ESG Research can use previously reported emissions data or
minimal calculations to complete the target description and process the target into a company’s
future emissions projection.
To provide transparency for targets that used imputed as opposed to disclosed data by companies,
MSCI ESG Research provided an additional factor under the target summary information explaining
what exactly was imputed for each of the targets.

© 2023 MSCI Inc. All rights reserved.

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Exhibit 38: Process flow for incorporating missing climate target data
Step

Missing Data point

Imputation

Description

1

Target Value

Calculate target value
from reported GHG
emissions reduction %If a target has a baseline GHG emission reduction
value and a reduction percentage, target value
can be calculated: (target value = baseline value *(1- reduction %)).

2

Target Value = 0

Impute target value fornet zero targets

For a small set of net-zero targets the target value
is missing – this effectively is zero. - Apply zero as
the target value

Baseline Value

Impute GHG emissions
baseline value for all
targets

For a set of targets, the baseline year is reported
but the baseline value for calculating a GHG
emission target is missing. Use reported or
estimated emission data for the corresponding
year to impute the baseline. - E.g., Imputebaseline value for 2019 (use 2018 reported value)

4

Baseline Year andbaseline value

Impute GHG emissions
baseline year and value
for net zero targets

For net zero targets, baseline year and value forcalculating a GHG emission target are missing.
Use announcement year minus 1 year andreported or estimated emission data for thecorresponding year as the baseline value

5

Target Coverage Ratio

Impute target coverage
ratio as 100% when thetarget is applicable
company wide.

For those companies that disclosed the target isapplicable company wide, the Target Summary
Model assumed the target coverage ratio of suchtargets as 100%.

3

Source: MSCI ESG Research© 2023 MSCI Inc. All rights reserved.

MSCI.COM | PAGE 40 OF 43

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Appendix II: Comparison of yield curve shocks between NGFS phase II andphase III
Exhibit 39: Comparison of yield curve shocks between NGFS Phase II and Phase III for the
GPIF’s Japanese bond holdings

Source: MSCI ESG Research, as of June 2023

Exhibit 40: Comparison of yield curve shocks between NGFS Phase II and Phase III for the
GPIF’s U.S. bond holdings

Source: MSCI ESG Research, as of June 2023

© 2023 MSCI Inc. All rights reserved.

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