MARKET INSIGHTS

Keep the Change:
Analyzing the Increase in ESG Ratings
for U.S. Equities
April 2022

Introduction

Data Sources

Amidst an abundance of industry and academic
research on environmental, social, and governance(“ESG”) investing, we believe one crucial question
merits further exploration: have companies improved their
ESG-related behaviors over time?

We selected the ESG Ratings framework provided by MSCI
Inc. (“MSCI”) and the Russell 1000® Index (“R1000”) as
our key data sources, which in turn informed our decisions
regarding three core parameters: (1) the sample period,(2) the individual pillar scores on which we conducted ourattribution analysis, and (3) the constituent companies in
the R1000 to which we applied the attribution.

The weighted average ESG rating for companies in the
Russell 1000® Index has indeed increased in recent years,
as can be seen in Figure 1, but that isn’t necessarily
indicative of changes in the behaviors of companies. This
shift could simply be an artifact of the evolving
composition of the Russell 1000®, or something akin to“grade inflation” given incremental changes in scoring
rules.

By way of background, MSCI publishes an ESG score on a
0–10 scale for over 8,500 companies. Each of the “E,”
“S,” and “G” pillars of the aggregate ESG score comprises
a number of constituent “key issues,” and pillar scores arederived from the weighted average of the scores assigned
to each key issue in that pillar. MSCI uses the three pillar
scores to compute an overall ESG score, as well as an
AAA–CCC rating, for each company. 1

After conducting an attribution analysis of Russell 1000®
constituents and adjusting for three structural factors, wefind that U.S. equities still experienced a meaningfulincrease in ESG ratings. We also present supplementaryresearch on the distributional concentration of ratingschanges and a case study on carbon emissions, each ofwhich indicates that the aggregate ratings increase wasdriven at least in part by the behavior of individualcompanies.

With respect to the first parameter, sample period, we chose
January 1, 2015 as our start date because MSCI implemented
methodological changes as of that date that had material
impacts on E, S, and G scores, and complete point-in-timedata are not available for periods prior to 2015. The end date
for all data presented is December 31, 2021.
Regarding the second parameter, individual pillar scores,
we chose to focus our analysis on “E&S” scores. MSCI’s G
score methodology materially changed on two separate
occasions after 2015, which noticeably contributed tolarge shifts in individual and weighted average G scores.

We believe this multidimensional analysis offers insights
into developments in ESG scoring methodology and how
company-specific behaviors may have evolved.

Figure 1 R1000 Aggregate Score Change
20%
15%
10%
5%
0%
-5%
-10%
2015

2016

2017

2018
ESG

2019

2020

2021

E&S

Sources: London Stock Exchange Group; MSCI; the D. E. Shaw group.
1

MSCI provides a visual breakdown of its ESG, pillar, and key issue scores at https://www.msci.com/our-solutions/esg-investing/esg-ratings/esgratings-key-issue-framework.

MARKET INSIGHTS | Keep the Change: Analyzing the Increase in ESG Ratings for U.S. Equities

1Figure 1 compares the ESG and E&S scores for all R1000
constituents over the sample period. The two abrupt
moves in the ESG line in 2018 and 2020 highlight thediscontinuities in G scores. Because we concluded it was
not feasible to adjust for those methodological changes ina robust manner, we chose to omit G scores from ourattribution analysis.

sequential adjustments to arrive at an adjusted aggregate
score improvement.

(1) Index Composition
The first potential source of bias we explore is thecomposition of the R1000. The index weights of stocks in
the R1000 shifted during the sample period, in some cases
materially, and those changes together had a meaningful
impact on the index’s aggregate E&S score. For example,
Microsoft Corp.—which consistently received high MSCIESG scores over the period—grew significantly from 1.8%
to 5.7% of the index’s weight. Meanwhile, General
Electric Co., one of the lowest-rated companies by ESG
score, fell from 1.1% to 0.2% of the index’s weight overthe period.

With respect to the third parameter, company selection,
for purposes of consistency we focused on the companies
that were R1000 constituents over the entire sample
period and for which the necessary ESG data wereavailable. 2 For that smaller attribution sample, the total
E&S score increase over the period is 18%, rather than the
17% computed for all R1000 constituents that is depictedby the blue line in Figure 1.

With this in mind, we sought to quantify the effects
of changing weights on the index’s overall E&S score.
As shown in Figure 2, by conducting a modified Brinson
analysis, 3 we find that approximately 5% of the E&Sscore increase over the period resulted from changes inindex weights.

Structural Factors
Our attribution approach attempts to estimate how muchof the raw E&S score increase can be attributed tostructural factors that may have systematically biased thescore, either positively or negatively, and carries out
Figure 2 R1000 Attribution Sample E&S Score Change:
Index Composition and Residual Effects
20%

15%

10%

5%

0%

-5%
2015

2016
Index Composition

2017

2018
Residual

2019

2020

2021

Total R1000 Attribution Sample E&S Score Change

Sources: London Stock Exchange Group; MSCI; the D. E. Shaw group.
2

Our attribution sample comprises 437 companies representing approximately 63% of the R1000 by weight as of January 1, 2015 and 67% as ofDecember 31, 2021. We believe score changes in the sample and the full index track closely. See Figure 11 in the Appendix for a comparison
between the full R1000 and our attribution sample.

3

We employ a modified version of the Brinson attribution described in Gary P. Brinson and Nimrod Fachler, “Measuring Non-U.S. Equity Portfolio
Performance,” The Journal of Portfolio Management (Spring 1985), Vol. 11, No. 3: 73–76. In Figure 2, “Residual” represents the E&S scorechange when holding index weights constant.

MARKET INSIGHTS | Keep the Change: Analyzing the Increase in ESG Ratings for U.S. Equities2(2) Key Issue Scores

weights can result in substantial changes to overall pillar
scores and the relative weightings of each pillar.

A second potential source of bias in the aggregate E&Sscore increase relates to changes in the weights assigned
to the key issues that constitute each of MSCI’s pillars.
Figure 3 plots the three E&S key issues with the largest
total increases and the three with the largest total
decreases in weight in the R1000 attribution sample overthe period. As with the index weightings, some of theseshifts during the sample period were clearly meaningful; in
one case, for example, MSCI eliminated a key issue(Energy Efficiency) altogether. Shifts in key issue score

To capture those potential distortions, we conduct asecond Brinson analysis, as shown in Figure 4. We findthat the E&S score increase, when adjusted for constant
R1000 index weights as reflected in Figure 2, would havebeen 4% larger if the relative weights assigned to key
issue scores had also remained constant over the period.
The attributed value for “Key Issue Score Weight
Allocation Effect” reflected in Figure 4 illustrates the bias
introduced by this structural element.

Figure 3 MSCI E&S Key Issue Score Weights in the R1000 Attribution Sample:
Largest Positive and Negative Moves
12%
10%
8%

Privacy and Data Security

6%

Human Capital Development

4%

Opportunities in Clean Tech

2%

Health and Safety0%

Toxic Emissions and Waste-2%

Energy Efficiency

-4%
-6%

Energy Efficiency key issue score discontinued after 2017

-8%
2015

2016

2017

2018

2019

2020

2021

Sources: MSCI; the D. E. Shaw group.

Figure 4 R1000 Attribution Sample E&S Score Change:
Allocation to Key Issue Scores and Score Changes
20%
Other Positive Contributors

15%

Financing Environmental Impact
Toxic Emissions and Waste

10%

Privacy and Data Security
5%

Other Negative Contributors

0%

Key Issue Score Weight
Allocation EffectTotal R1000 Attribution Sample
E&S Score Change (after
adjusting for index weightcomposition)

-5%
-10%
2015

2016

2017

2018

2019

2020

2021

Sources: London Stock Exchange Group; MSCI; the D. E. Shaw group.

MARKET INSIGHTS | Keep the Change: Analyzing the Increase in ESG Ratings for U.S. Equities3(3) The Effects of Disclosure
Companies generally have increased their reporting of key
ESG metrics over time, particularly in recent years, as
stakeholder focus on ESG has intensified. For example, 346
companies in the R1000 reported carbon emissions data at
the start of 2015; by the end of 2021, that number had
risen to 507. Within our attribution sample of 437 index
constituents, 193 reported emissions data at the start ofthe period compared to 294 at the end.
Focusing on this emissions example, we wanted to assess
whether the relationship between disclosure of carbon
emissions data and MSCI E scores was one that might
have inflated the index’s aggregate E&S score over the

sample period. Figure 5 shows that companies in the full
R1000 that reported carbon emissions for the first time inany calendar year during the period were significantly
more likely to experience an increase in their E score thancompanies that did not alter their reporting of carbon
emissions or ceased reporting altogether.
To estimate the overall co-movement between E&S score
improvement and increased disclosure, for each company
in our sample, we ran a regression of changes in its E&S
score (adjusted for changes in key issue score weights) onchanges in its Bloomberg Finance L.P. (“Bloomberg”) ESG
disclosure score. 4

Figure 5 Distribution of Year-Over-Year E Score Directional Changes:
First-Time and Other Reporters of Carbon Emissions in the R1000(2015–2021)
Other Reporters

First-Time Reporters

13%
29%
39%
26%

62%

32%

Score Increase

Score Decrease

No Score Change

Sources: London Stock Exchange Group; MSCI; the D. E. Shaw group.

4

We relied on Bloomberg’s ESG disclosure score data because MSCI does not report an ESG disclosure score or similar metric. Bloomberg reports
these scores on a 0–100 scale, which we rescaled to 0–10 for interpretability relative to MSCI’s ESG scores. We further lagged this disclosure data
in an effort to more closely align the two data providers’ reporting windows.

MARKET INSIGHTS | Keep the Change: Analyzing the Increase in ESG Ratings for U.S. Equities

4(i.e., exhibited a “beta” of 0.3). The product of that beta
and the weighted average percentage change in scaled
Bloomberg disclosure scores for all companies in our
attribution sample is 5%, meaning that the aggregate E&Sscore increase may be biased higher by up to 5% becauseof the disclosure effect associated with MSCI’s ESG scores.

Figure 6 presents the results of that regression, whichshow a statistically significant (t = 5.3) relationshipbetween E&S score and disclosure.
For every 1 point increase in its scaled Bloomberg
disclosure score over the period, a company tended toexperience a 0.3 point increase in its E&S score

Figure 6 Changes in Adjusted E&S Scores (y-axis) Relative to Changes in
Scaled Bloomberg ESG Disclosure Scores (x-axis)(2015–2021)
6

5

4

3

2

1

0

-1

-2

-3
-3

-2

-1

0

1

2

3

4

5

Sources: Bloomberg; London Stock Exchange Group; MSCI; the D. E. Shaw group.

MARKET INSIGHTS | Keep the Change: Analyzing the Increase in ESG Ratings for U.S. Equities

5Sequentially Adjusting theAggregate E&S Score Change

key issue score weights, and estimated co-movement ofscore improvement with disclosure.

As we have noted, the aggregate E&S score for our
attribution sample increased by approximately 18% on an
unadjusted basis over the seven-year period. Figure 7
shows the results of sequentially adjusting that raw scoreincrease to account for the three structural effects we
discuss above: changes in index composition, changes in

After making those adjustments, we arrive at a residual
score increase of approximately 12%. While otherstructural effects may have influenced this residual in either
direction, it seems plausible to us that changes incompany-specific behaviors explain a meaningful amountof this residual increase. (The case study on carbon
emissions in the penultimate section of this paper considers
that possibility in greater depth.)

Figure 7 R1000 Attribution Sample E&S Score Change with Successive Adjustments(2015–2021)

Weighted Average E&S Score Change

Increase

Decrease

Total+4% adjustment for
constant key issue scoreweights-5% adjustment for
constant index weights

Constant Index Weights
Unadjusted E&S Score-5% adjustment fordisclosure impact

Disclosure Impact

Constant Key Issue Score Weights

Adjusted E&S Score

Sources: Bloomberg; London Stock Exchange Group; MSCI; the D. E. Shaw group.

MARKET INSIGHTS | Keep the Change: Analyzing the Increase in ESG Ratings for U.S. Equities

6

Improvements Cluster among
Lower Scorers
Having adjusted for those three distorting effects, we can
examine how the adjusted E&S score increase is distributed
across our sample. We find that companies that had
relatively low E&S scores at the start of the period are
more likely to have demonstrated score improvement.
Figure 8 assigns each company in our attribution sample
to one of five segments based on its E&S score at thestart of the period: AAA–AA, A, BBB, BB, or B–CCC. We
compute the percentage of companies that transitioned
from one segment to another, as well as the percentagethat remained within the same segment at the end of
the sample period. The observed score increase skews

towards those companies in initially lower-rated cohorts ofthe sample.
Having established that companies with initially lower E&S
scores are more likely to have shown score improvement,
we now examine the relationship between initial E&S score
and the relative size of the score increase. To do so, weassigned each company in the attribution sample to a decile
by its starting E&S 0–10 numerical score, and then plotted
the weighted average score change per decile (after making
the same adjustments described in prior sections). Figure 9shows that companies in the lower deciles (1–3) exhibit asignificantly larger score increase than those in the middle(4–7) or higher deciles (8–10). Although the higher deciles(highest initial scores) decrease on average, the weighted
magnitude of these decreases is less than the corresponding
increases experienced by the lowest scorers.

Figure 8 R1000 Attribution Sample E&S Score Transitions(2015–2021)

Sources: Bloomberg; London Stock Exchange Group; MSCI; the D. E. Shaw group.

Figure 9 R1000 Attribution Sample E&S Score Change by Starting Score Decile(2015–2021)
4

E&S Score Change

3
2
1
0
-1
-2
-3
1

2

3

4

5
6
Starting Score Decile

7

8

9

10

Sources: Bloomberg; London Stock Exchange Group; MSCI; the D. E. Shaw group.
MARKET INSIGHTS | Keep the Change: Analyzing the Increase in ESG Ratings for U.S. Equities

7

Case Study: Carbon Emissions

Conclusion

In the attribution analysis described above, we adjust
aggregate E&S scores for three distinct structural factors.
However, it’s entirely possible that some of the remaining
score increase is driven by structural factors not captured in
our analysis. We conducted a case study on carbon emissions
to evaluate whether companies have indeed changed their
behaviors in ways that lead to higher scores.

This paper applies statistical techniques to shed light on
the observed increase in aggregate ESG scores since 2015.
The results of our sequential adjustments indicate that, of
the approximately 18% unadjusted aggregate E&S score
improvement observed in our attribution sample, roughly
12% remains after accounting for the structural effects
described above. Additionally, we find that score increases
are generally concentrated in issuers that began the
period with relatively low E&S scores, suggesting thatcompanies at the bottom of the score distribution drove
the improvement.

We employed two emissions metrics: carbon intensity(“CI”), as measured by tons of MSCI Scope 1 + 2
emissions 5 per $1 million of sales, and carbon footprint(“CF”), as measured by tons of Scope 1 + 2 emissions per$1 million of market capitalization. We applied those two
metrics to a sample of the R1000 for which carbon
emissions data were available over the 2015–2021 period. 6
Figure 10 shows that, on a weighted average basis, bothemissions metrics declined over the sample period,
whether or not index weights are held constant. These
results suggest that, at least for carbon emissions, companyspecific behavioral changes are captured by the overall E&S
score increase. Although that may not be true for all key
issues driving ESG scores, it is encouraging to see scoresreflect at least certain “real world” ESG changes.

We believe that a multi-dimensional attribution approachis valuable not only for assessing the overall trend in ESG
scores but also in evaluating how such scores map tocompanies’ adoption of ESG-friendly practices. As ESG
investing continues to grow and evolve, it will be criticalfor investors and analysts to apply rigorous approaches to
ESG data, trends, and observations—not only to informtheir own investment decisions, but also to help themunderstand the connections between ESG ratings and ESG
behaviors at the company level.

Figure 10 R1000 Case Study Sample Carbon Intensity and Carbon Footprint

Tons of Carbon Emitted per$1 mn of Sales or Market Capitalization

250

200

R1000 Case Study
Sample CI (constantindex weights)

150

R1000 Case Study
Sample CI

100

R1000 Case Study
Sample CF (constantindex weights)

50

R1000 Case Study
Sample CF

0
2015

2016

2017

2018

2019

2020

2021

Sources: MSCI; Reuters DataScope; the D. E. Shaw group.

5

Scope 1 emissions cover direct emissions from a company’s owned or controlled sources. Scope 2 emissions cover indirect emissions from acompany’s energy consumption (e.g., electricity purchased).

6

Because of differences in data availability, the 581 companies in this case study sample are not the same as those included in the attribution
sample. We believe this case study sample is representative of the full R1000 over this period, as supported by Figure 12 in the Appendix.

MARKET INSIGHTS | Keep the Change: Analyzing the Increase in ESG Ratings for U.S. Equities

8Appendix

that the attribution sample’s slightly higher increase inweighted average score may suggest that the magnitudeof the attributed effects could be somewhat larger for theattribution sample than for the full index.

For various portions of our analysis, we relied on subsets
of R1000 constituents, both for methodological reasons,such as the desire to maintain a constant sample throughout
the period, and because of data availability. As can be seenin the two figures below, the relevant metrics for thoseindex subsets generally track those of the full R1000,
indicating that our conclusions are likely to be applicableto the index itself.

Figure 12 plots the weighted average CI and CF for theemissions-specific case study sample and the full R1000,
indicating a close relationship between those two data
series. For both carbon metrics, the full index and casestudy sample converge over time, and the two series’monthly percentage changes demonstrate correlations ofapproximately 0.87 (CI) and 0.98 (CF). In this case, theobserved decrease in carbon emissions is slightly larger for
the full R1000 than for the case study sample, whichsuggests that changes in company behavior may have had
a greater impact in reducing carbon emissions in thecontext of the full index than in the case study sample.

As can be seen in Figure 11, the aggregate E&S score of
our attribution sample increased by approximately 18%,
compared to the index’s 17%. At any given point in time,
the two data series differ by no more than 1.9%, and themonthly score changes within the two series exhibit acorrelation of 0.92. That said, it’s still important to note
Figure 11 E&S Score Change by Index Sample
20%
15%

R1000

10%

R1000 Attribution
Sample

5%
0%
-5%
2015

2016

2017

2018

2019

2020

2021

Sources: London Stock Exchange Group; MSCI; the D. E. Shaw group.

Tons of Carbon Emitted per$1 mn of Sales or Market Capitalization

Figure 12 Carbon Intensity and Carbon Footprint by Index Sample
250

200

R1000 CI

150

R1000 Case Study
Sample CI

100

R1000 CF50

R1000 Case Study
Sample CF

0
2015

2016

2017

2018

2019

2020

2021

Sources: London Stock Exchange Group; MSCI; Reuters DataScope; the D. E. Shaw group.
MARKET INSIGHTS | Keep the Change: Analyzing the Increase in ESG Ratings for U.S. Equities

9Note Regarding the Use of Certain MSCI Inc. Data
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MARKET INSIGHTS | Keep the Change: Analyzing the Increase in ESG Ratings for U.S. Equities

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