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Comparative analysis of environmental, social and governance (ESG) ratings: do sectors and regions differ?

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Abstract

Sustainable and holistic investment philosophy such as environmental, social and governance (ESG) concepts have now emerged as the subtle, comprehensive and concrete response to the unprecedented surge in environmental, social and financial market sustainable development problems. The main aim of this paper is to perform an in-depth study on ESG ratings world-wide and to granularly analyse how and why they differ within industries and regions as reported by Sustainalytics on 13,589 companies as of December 2022. Perceiving ESG ratings from dual dimensions, we introduce the ‘push–pull effect’ where we identify the rationale pushing corporates for providing their ESG engagements to ESG rating providers and the justification for stakeholders pulling information from these rating providers. Correspondence analysis, nonparametric independent sample Kruskal–Wallis test and Mann–Whitney test are performed as tools of inference. Results reveal that Asia and America are regions demonstrating high ESG risks with European corporates exhibiting low ESG risks. In terms of industry, transportation infrastructure and media, both categorized under low ESG risk, portray a statistically significant difference from other industries. Finally, the sector wise reports clearly evince an overall statistically significant difference between financial and non-financial sector in all regions, the former presenting high risk ESG scores in Asia and North America. Policy implications are set as ESG is a concept which has stepped out of the “awareness creation” stage to an implementation state, imploring policy makers to embark on stringent measures of ensuring ESG compliance to reap stakeholder confidence and ensure sustainable development.

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Authors and Affiliations

Authors

Corresponding author

Correspondence to Rekha Pillai.

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The authors declare that there is no conflict of interest.

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Appendices

Appendix A

See Table 13

Table 13 Number of companies in each sector

Appendix B: Normality test

Tests of normality

 

Kolmogorov-Smirnova

Statistic

df

Sig

ESG

0.038

13,589

0.000

  1. aLilliefors significance correction

Appendix C: Kruskal–Wallis test—to identify the ESG differences among regions

 

Continent

N

Median

Mean Rank

ESG Score

Asia

5994

28.300

7683.11

Europe

2722

21.700

4999.47

Africa

141

27.000

6666.49

Oceania

33

19.400

5815.95

Australia

363

25.000

6366.65

North America

4029

26.100

6709.18

South America

307

27.000

7172.18

Total

13,589

26.200

 

Test statisticsa,b

ESG Score

Chi-square

888.743

Df

6

Asymp. sig.

0.000

  1. aKruskal Wallis test
  2. bGrou** variable: continent

Appendix D: Industry * type of risk crosstabulation

 

Type of risk

Total

Negligible risk

Low risk

Medium risk

High risk

Severe risk

Industry

Aerospace and defense

Count

0

1

18

42

26

87

% within industry

0.0%

1.1%

20.7%

48.3%

29.9%

100.0%

Autocomponents

Count

3

68

117

15

0

203

% within industry

1.5%

33.5%

57.6%

7.4%

0.0%

100.0%

Automobiles

Count

0

15

46

22

0

83

% within industry

0.0%

18.1%

55.4%

26.5%

0.0%

100.0%

Banks

Count

35

159

402

299

37

932

% within industry

3.8%

17.1%

43.1%

32.1%

4.0%

100.0%

Building products

Count

1

15

72

33

0

121

% within industry

0.8%

12.4%

59.5%

27.3%

0.0%

100.0%

Chemicals

Count

2

15

168

216

74

475

% within industry

0.4%

3.2%

35.4%

45.5%

15.6%

100.0%

Commercial services

Count

27

135

184

19

0

365

% within industry

7.4%

37.0%

50.4%

5.2%

0.0%

100.0%

Construction and engineering

Count

0

7

36

130

112

285

% within industry

0.0%

2.5%

12.6%

45.6%

39.3%

100.0%

Construction materials

Count

0

3

28

54

39

124

% within industry

0.0%

2.4%

22.6%

43.5%

31.5%

100.0%

Consumer durables

Count

4

111

73

17

0

205

% within industry

2.0%

54.1%

35.6%

8.3%

0.0%

100.0%

Consumer services

Count

0

137

153

104

1

395

% within industry

0.0%

34.7%

38.7%

26.3%

0.3%

100.0%

Containers and packaging

Count

1

51

28

0

0

80

% within industry

1.3%

63.8%

35.0%

0.0%

0.0%

100.0%

Diversified financials

Count

12

150

327

299

2

790

% within industry

1.5%

19.0%

41.4%

37.8%

0.3%

100.0%

Diversified metals

Count

0

3

24

39

115

181

% within industry

0.0%

1.7%

13.3%

21.5%

63.5%

100.0%

Electrical equipment

Count

0

24

118

78

0

220

% within industry

0.0%

10.9%

53.6%

35.5%

0.0%

100.0%

Energy services

Count

0

9

46

35

0

90

% within industry

0.0%

10.0%

51.1%

38.9%

0.0%

100.0%

Food products

Count

0

19

122

195

160

496

% within industry

0.0%

3.8%

24.6%

39.3%

32.3%

100.0%

Food retailers

Count

0

40

109

28

0

177

% within industry

0.0%

22.6%

61.6%

15.8%

0.0%

100.0%

Health care

Count

0

101

231

185

26

543

% within industry

0.0%

18.6%

42.5%

34.1%

4.8%

100.0%

Homebuilders

Count

0

31

44

2

0

77

% within industry

0.0%

40.3%

57.1%

2.6%

0.0%

100.0%

Household products

Count

0

7

41

48

2

98

% within industry

0.0%

7.1%

41.8%

49.0%

2.0%

100.0%

Insurance

Count

1

65

143

82

2

293

% within industry

0.3%

22.2%

48.8%

28.0%

0.7%

100.0%

Machinery

Count

0

27

153

235

50

465

% within industry

0.0%

5.8%

32.9%

50.5%

10.8%

100.0%

Media

Count

8

184

47

0

0

239

% within industry

3.3%

77.0%

19.7%

0.0%

0.0%

100.0%

Paper and forestry

Count

0

17

42

12

0

71

% within industry

0.0%

23.9%

59.2%

16.9%

0.0%

100.0%

Pharmaceuticals

Count

0

61

290

419

148

918

% within industry

0.0%

6.6%

31.6%

45.6%

16.1%

100.0%

Precious metals

Count

4

3

27

27

41

102

% within industry

3.9%

2.9%

26.5%

26.5%

40.2%

100.0%

Real estate

Count

55

551

364

3

0

973

% within industry

5.7%

56.6%

37.4%

0.3%

0.0%

100.0%

Refiners and pipelines

Count

0

5

50

70

51

176

% within industry

0.0%

2.8%

28.4%

39.8%

29.0%

100.0%

Retailing

Count

3

273

135

6

0

417

% within industry

0.7%

65.5%

32.4%

1.4%

0.0%

100.0%

Semiconductors

Count

0

47

133

81

47

308

% within industry

0.0%

15.3%

43.2%

26.3%

15.3%

100.0%

Software and services

Count

8

248

619

35

0

910

% within industry

0.9%

27.3%

68.0%

3.8%

0.0%

100.0%

Technology hardware

Count

24

265

286

21

0

596

% within industry

4.0%

44.5%

48.0%

3.5%

0.0%

100.0%

Telecommunication services

Count

0

32

96

54

3

185

% within industry

0.0%

17.3%

51.9%

29.2%

1.6%

100.0%

Traders and distributors

Count

0

25

104

29

0

158

% within industry

0.0%

15.8%

65.8%

18.4%

0.0%

100.0%

Transportation

Count

1

77

197

44

5

324

% within industry

0.3%

23.8%

60.8%

13.6%

1.5%

100.0%

Transportation infrastructure

Count

19

82

42

0

0

143

% within industry

13.3%

57.3%

29.4%

0.0%

0.0%

100.0%

Utilities

Count

5

74

189

192

167

627

% within industry

0.8%

11.8%

30.1%

30.6%

26.6%

100.0%

Industrial conglomerates

Count

0

0

10

32

64

106

% within industry

0.0%

0.0%

9.4%

30.2%

60.4%

100.0%

Oil and gas producers

Count

1

5

14

65

153

238

% within industry

0.4%

2.1%

5.9%

27.3%

64.3%

100.0%

Textiles and apparel

Count

2

122

49

0

0

173

% within industry

1.2%

70.5%

28.3%

0.0%

0.0%

100.0%

Steel

Count

0

2

7

50

81

140

% within industry

0.0%

1.4%

5.0%

35.7%

57.9%

100.0%

Total

Count

216

3266

5384

3317

1406

13,589

% within industry

1.6%

24.0%

39.6%

24.4%

10.3%

100.0%

Appendix E: Overview column pointsa for industry-risk analysis

Risk

Mass

Score in dimension

Inertia

Contribution

1

2

Of point to inertia of dimension

Of dimension to inertia of point

1

2

1

2

Total

Negligible risk

0.016

0.962

− 0.834

0.034

0.022

0.030

0.281

0.119

0.400

Low risk

0.240

0.907

− 0.610

0.169

0.302

0.242

0.764

0.195

0.959

Medium Risk

0.396

0.273

0.345

0.053

0.045

0.128

0.362

0.326

0.688

High Risk

0.244

− 0.673

0.584

0.117

0.169

0.226

0.618

0.262

0.881

Severe Risk

0.103

− 1.711

− 1.155

0.252

0.462

0.374

0.788

0.202

0.991

Active Total

1.000

  

0.626

1.000

1.000

   
  1. aSymmetrical normalization

Appendix F: Overview row pointsa for industry risk analysis

Industry

Mass

Score in dimension

Inertia

Contribution

1

2

Of point to inertia of dimension

Of dimension to inertia of point

1

2

1

2

Total

Aerospace and defense

0.006

− 1.174

0.004

0.006

0.013

0.000

0.975

0.000

0.975

Autocomponents

0.015

0.649

0.069

0.005

0.010

0.000

0.809

0.005

0.814

Automobiles

0.006

0.209

0.639

0.001

0.000

0.007

0.143

0.758

0.901

Banks

0.069

0.038

0.420

0.008

0.000

0.033

0.008

0.560

0.568

Building products

0.009

0.151

0.765

0.002

0.000

0.014

0.056

0.809

0.866

Chemicals

0.035

− 0.677

0.502

0.014

0.024

0.024

0.745

0.231

0.976

Commercial services

0.027

0.777

− 0.225

0.015

0.025

0.004

0.699

0.033

0.732

Construction and engineering

0.021

− 1.408

− 0.430

0.029

0.063

0.011

0.936

0.049

0.985

Construction materials

0.009

− 1.141

− 0.123

0.008

0.018

0.000

0.987

0.007

0.994

Consumer durables

0.015

0.841

− 0.475

0.009

0.016

0.009

0.783

0.141

0.923

Consumer services

0.029

0.364

0.198

0.005

0.006

0.003

0.532

0.088

0.621

Containers and packaging

0.006

1.046

− 0.755

0.006

0.010

0.009

0.710

0.208

0.918

Diversified financials

0.058

0.062

0.630

0.011

0.000

0.063

0.014

0.797

0.811

Diversified metals

0.013

− 1.802

− 1.551

0.042

0.066

0.087

0.678

0.283

0.961

Electrical equipment

0.016

0.010

0.883

0.005

0.000

0.034

0.000

0.989

0.990

Energy services

0.007

− 0.048

0.929

0.002

0.000

0.015

0.005

0.992

0.997

Food products

0.037

− 1.091

− 0.220

0.029

0.066

0.005

0.977

0.022

1.000

Food retailers

0.013

0.407

0.453

0.004

0.003

0.007

0.398

0.278

0.676

Health care

0.040

− 0.040

0.480

0.004

0.000

0.025

0.011

0.864

0.875

Homebuilders

0.006

0.768

− 0.090

0.003

0.005

0.000

0.772

0.006

0.778

Household products

0.007

− 0.283

0.985

0.003

0.001

0.019

0.117

0.796

0.913

Insurance

0.022

0.210

0.504

0.003

0.001

0.015

0.225

0.731

0.957

Machinery

0.034

− 0.583

0.676

0.015

0.018

0.042

0.499

0.378

0.877

Media

0.018

1.197

− 1.165

0.029

0.038

0.065

0.574

0.306

0.880

Paper and forestry

0.005

0.404

0.425

0.001

0.001

0.003

0.448

0.279

0.727

Pharmaceuticals

0.068

− 0.666

0.404

0.025

0.046

0.030

0.776

0.160

0.936

Precious metals

0.008

− 1.113

− 0.729

0.008

0.014

0.011

0.721

0.174

0.895

Real estate

0.072

1.019

− 0.709

0.064

0.114

0.098

0.766

0.209

0.975

Refiners and pipelines

0.013

− 1.008

− 0.058

0.009

0.020

0.000

0.998

0.002

1.000

Retailing

0.031

1.037

− 0.773

0.032

0.050

0.050

0.669

0.210

0.879

Semiconductors

0.023

− 0.278

0.090

0.002

0.003

0.001

0.665

0.040

0.705

Software and services

0.067

0.634

0.227

0.033

0.041

0.009

0.539

0.039

0.578

Technology hardware

0.044

0.838

− 0.322

0.022

0.047

0.012

0.901

0.075

0.975

Telecommunication services

0.014

0.113

0.611

0.002

0.000

0.014

0.054

0.884

0.938

Traders and distributors

0.012

0.304

0.645

0.004

0.002

0.013

0.181

0.457

0.638

Transportation

0.024

0.407

0.336

0.006

0.006

0.007

0.440

0.168

0.608

Transportation infrastructure

0.011

1.111

− 0.974

0.018

0.020

0.027

0.477

0.206

0.683

Utilities

0.046

− 0.710

− 0.280

0.017

0.035

0.010

0.913

0.080

0.993

Industrial conglomerates

0.008

− 1.848

− 1.323

0.023

0.041

0.037

0.766

0.221

0.987

Oil and gas producers

0.018

− 1.900

− 1.569

0.058

0.096

0.117

0.714

0.274

0.988

Textiles and apparel

0.013

1.111

− 0.927

0.016

0.024

0.030

0.632

0.248

0.879

Steel

0.010

− 1.837

− 1.222

0.028

0.053

0.042

0.800

0.199

0.999

Active total

1.000

  

0.626

1.000

1.000

   
  1. aSymmetrical normalization

Appendix G: Kruskal–Wallis test—to identify the difference between industries

 

Industry

N

Median

Mean rank

ESG Score

Aerospace and defense

87

35.200

10,383.40

Autocomponents

203

22.900

4738.30

Automobiles

83

27.000

6574.86

Banks

932

27.900

7058.08

Building products

121

27.200

6757.70

Chemicals

475

32.200

9341.11

Commercial services

365

21.000

4139.17

Construction and Engineering

285

37.800

10,978.60

Construction materials

124

35.900

10,382.38

Consumer durables

205

18.900

3867.18

Consumer services

395

25.300

5829.55

Containers and packaging

80

17.900

2933.55

Diversified financials

790

28.300

7069.35

Diversified metals

181

45.000

11,525.26

Electrical equipment

220

27.650

7329.85

Energy services

90

27.650

7440.48

Food products

496

35.800

10,122.18

Food retailers

177

24.600

5832.73

Health care

543

27.200

7205.95

Homebuilders

77

22.300

4278.42

Household products

98

30.400

8412.11

Insurance

293

26.500

6417.90

Machinery

465

31.900

8993.15

Media

239

16.800

2234.91

Paper and forestry

71

24.500

5921.99

Pharmaceuticals

918

32.100

9189.01

Precious metals

102

35.400

10,070.02

Real estate

973

18.100

2940.34

Refiners and pipelines

176

33.800

9885.16

Retailing

417

18.200

3080.79

Semiconductors

308

27.600

7690.30

Software and services

910

23.100

4939.88

Technology hardware

596

20.250

3869.22

Telecommunication services

185

26.600

6822.28

Traders and distributors

158

25.700

6297.29

Transportation

324

23.900

5751.38

Transportation infrastructure

143

16.400

2423.79

Utilities

627

32.600

8910.97

Industrial conglomerates

106

41.400

11,815.24

Oil and gas producers

238

44.050

11,883.43

Textiles and apparel

173

17.400

2539.90

Steel

140

42.250

11,815.75

Total

13,589

26.200

 

Test statisticsa,b

ESG Score

Chi-square

6093.148

df

41

Asymp. sig.

0.000

  1. aKruskal Wallis test
  2. bGrou** variable: industry

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Pillai, R., Islam, M.A., Sreejith, S. et al. Comparative analysis of environmental, social and governance (ESG) ratings: do sectors and regions differ?. J Manag Gov (2024). https://doi.org/10.1007/s10997-023-09692-7

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