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Structural Loopholes in Sustainability-Linked Bonds

Imtiaz Ul Haq *

Djeneba Doumbia

*Corresponding author. Email: iulhaq@ifc.org

The findings, interpretations, and conclusions expressed in this paper do not necessarily reflect the views of the World Bank Group, its Board of Directors, or member states. Please do not share or distribute without authors’ permission.

Private Sector Development Research Network series - March 10th, 2023

Full paper can be accessed here.

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Sustainable Finance: A Growing Market

  • Sustainable finance has grown rapidly in the last few years.
    • Demand driven
  • Investor motivation:
    • ‘Do well by doing good’
    • Sacrifice financial returns for social benefits
  • Why specialized instruments?
    • Transparency around ESG
    • Credibility of ESG commitment

Source: Orden & Calonje (2022)

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Greenwashing

  • High informational asymmetries due to difficulty in identifying, measuring and interpreting sustainability impact, especially so for outsiders.
    • Leads to lack of transparency, reliability, and comparability (Berg et al., 2019)
  • This creates opportunities for firms to obscure their true state of sustainability, making ‘greenwashing’ possible.
  • Weak regulatory and disclosure environment perpetuates this.

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Greenwashing in Sustainable finance

  • How can greenwashing take place with specialized green instruments?
    • Green bonds fund green projects. Not always true…
  • Potential issues:
    • Unsubstantiated: Are projects really green?
      • E.g., HK airport issued a GB to fund development of a third runway.
    • Unambitious: Are projects green enough?
      • E.g., Several Chinese firms issued GBs for ‘clean coal’ plants, slightly better burning coal.
    • Immaterial: Are the right projects green?
      • E.g., German medical diagnostics company issues SLB to increase electric vehicles in its fleet
    • Additionality: Would the project have been funded anyway?
      • E.g., Pearson (education) issued a social bond to fund virtual learning (an existing product)
  • New evidence suggests it may be even worse…
    • Commitment: Is there any project at all?
    • Enforcement: Is the firm accountable to fund the project identified?

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Weakening commitment & enforceability in sustainable finance

  • Green promise: Identification of how proceeds will be used.
  • Disclaims default: Explicit disclaimer to remove default risk
  • Disclaims duty: Explicit disclaimer to remove ‘breach of duty’ risk

Source: Curtis et al., 2023.

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Sustainability-linked debt offers a solution

Differs from green, social and sustainability bonds along 3 dimensions:

  1. Contains pre-determined Sustainability Performance Targets (SPT) that the issuer aims to achieve before the maturity of the bond.
  2. Achievement of these targets is linked to financial incentives (typically the coupon rate) for the issuer
  3. SLB proceeds do not need to be project-specific and hence are fungible.

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Sustainability-linked bonds have grown rapidly

  • Sustainability-linked debt only instrument to embed enforceable commitments.
  • Sustainability-Linked Bonds (SLBs) were the fastest growing sustainable debt instrument in 2021, growing over 8 times in a year.
  • First launched in 2019, and over $100 billion in issuance in 2021.

Source: Orden & Calonje (2022)

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What is a Sustainability-Linked Bond (SLB)?

Sustainability targets

Issuance

Target Date

Maturity

  1. Targets (& KPIs)
  2. Target Date
  3. Financial incentive
  1. Maturity
  2. Coupon rate
  1. Step-up coupon
  2. Step-down coupon
  3. Redemption premium

Step-up coupon penalty

Step-down coupon

+ Redemption premium

Financial Incentives

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Potential issues in SLBs

  • Example: Chanel issued a SLB with a KPI to cut 10% of scope 3 emissions by 2030. This had been already been achieved by time bond was issued.
  • Example: German medical diagnostics company launched SLBs with KPIs related to the percentage of electric vehicles in its fleet.
  • Vulturius et al. (2022), Capital Monitor (2021)

  • Example: A telecom firm issued a SLB where its interest payments will increase by only 3% if targets unmet.
  • Kölbel and Lambillon, 2022; Berrada et al., 2022; Erlandsson et al., 2022

However, this paper uncovers two additional mechanisms that make SLBs less effective:

  • Minimizing the impact of penalties by pushing target cut-off dates closer to maturity date
  • Calling a SLB before maturity to avoid or minimize the penalty

Sustainability targets

(unambitious or immaterial)

Financial Incentives

(inadequate)

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Literature Review

  • Limited work on SLBs, mostly focused on SLB pricing.
    • Mixed evidence on SLB premiums (Kölbel and Lambillon, 2022; Liberadzki et al., 2022; Berrada et al., 2022).
    • Mixed evidence on SLL premiums (Du et al., 2022; Pohl et al., 2023).
  • Little discussion on how bond structure may influence enforcement:
    • Penalty size (Kölbel and Lambillon, 2022; Berrada et al., 2022; Erlandsson et al., 2022).
  • No empirical examination of other SLB features in this context.

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Data

  • Source: Thomson Reuters (Refinitiv) and BloombergNEF.
    • Supplemented with bond prospectuses, company press releases, available investor relations materials, and second-party opinion reports.
  • Sample: All SLBs issued as of end 2021.
    • 228 SLBs, out of which we exclude 20 due to insufficient data.
  • Variables: Bond and firm characteristics

Figure 2: Sustainability-linked bond issuance (US$ Billions)

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Descriptive Statistics

Figure 3: Share of Key Performance Indicators (KPIs), as a percentage of 322 total KPIs

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Descriptive Statistics

Table 2: Bonds with single and multiple penalty structures

Penalty type

Bonds

Penalties

Coupon step-up

153

229

Coupon step-down

3

19

Redemption premium at maturity

40

63

Donation

3

7

Purchase carbon emission credits

3

3

Early redemption

1

1

Total

203

322

[1] Excludes five SLBs for which there are different types of penalties associated.

Figure 4: Share of total coupon step-up penalty amount at bond level, if bond has only step-up penalty

The average coupon rate for SLBs with step-up penalties is 261 bps. The average penalty, however, is only 31.2 bps, which is less than 12 percent of the coupon rate on average.

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Do step-up SLBs have later target dates?

 

(1)

(2)

(3)

(4)

Model 1

Model 2

Model 3

Model 4

Coupon step-up penalty dummy

0.212***

0.235***

0.170***

0.134**

(0.025)

(0.034)

(0.038)

(0.059)

Investment grade dummy

 

0.078***

 

0.099**

 

(0.028)

 

(0.042)

Amount issued (US$ billions)

 

-0.027

 

0.123*

 

(0.041)

 

(0.069)

Tenor (years)

 

-0.009**

 

-0.007

 

(0.004)

 

(0.007)

Total assets (US$ billions)

 

 

0.0003

0.0006

 

 

(0.001)

(0.001)

Leverage (%)

 

 

-0.318***

-0.124

 

 

(0.088)

(0.139)

Public organization dummy

 

 

-0.146***

-0.075

 

 

(0.048)

(0.058)

Constant

0.361***

0.386***

0.645***

0.506***

(0.022)

(0.027)

(0.068)

(0.095)

Observations

248

158

138

80

Adjusted R-squared

0.093

0.053

0.162

0.112

Robust standard errors are in parentheses

*** p<.01, ** p<.05, * p<.1

 

The average target date for step-downs is set at about one-third (36 percent) of the bond’s tenor while for step-ups at 57.2 percent of the bond’s tenor.

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Does step-up penalty amount influence target dates?

 

(1)

(2)

(3)

(4)

Model 1

Model 2

Model 3

Model 4

Coupon step-up penalty (bps)

0.004***

0.003***

0.005***

0.004***

(0.001)

(0.001)

(0.001)

(0.001)

Investment grade dummy

 

0.068**

 

0.084**

 

(0.026)

 

(0.039)

Amount issued (US$ billions)

 

-0.032

 

0.067

 

(0.039)

 

(0.067)

Tenor (years)

 

-0.010**

 

-0.006

 

(0.004)

 

(0.006)

Total assets (US$ billions)

 

 

0.0001

0.0002

 

 

(0.001)

(0.001)

Leverage (%)

 

 

-0.247***

-0.084

 

 

(0.083)

(0.124)

Public organization dummy

 

 

-0.115***

-0.088

 

 

(0.043)

(0.057)

Constant

0.492***

0.562***

0.675***

0.565***

(0.016)

(0.044)

(0.061)

(0.121)

Observations

229

155

125

79

Adjusted R-squared

0.125

0.138

0.229

0.237

Robust standard errors are in parentheses

*** p<.01, ** p<.05, * p<.1

 

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Call Options

  • Insufficient data on call option exercise as SLBs are relatively new (Q3-2019), so we study inclusion.
  • Not all call options are useful to minimize penalties, hence we exclude ‘clean-up’ and ‘make-whole’ calls.
  • Penalties may be imposed on early call if targets unmet:
    • For SLBs with redemption penalty, original penalty applies if bond is called early (regardless of before or after target date).
    • For SLBs with step-ups, only 42.5 percent have some sort of penalty, mostly if targets unmet after target date.
    • Average call penalty (15.4bps) is about half the size of average step-up penalty (31.2bps), and payable only once. Hence call penalties are vastly inadequate in discouraging redemption.
    • There are no step-down SLBs that are callable in our sample, in line with our expectations.
  • Hence, only step-up SLBs can minimize penalty via early call.

Figure 6: Portion of callable bonds among SLBs and green and conventional corporate and municipal bonds

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Are step-up SLBs more likely to be callable and does penalty amount matter?

(2)

(3)

(4)

Model 2

Model 3

Model 4

Step-up SLB dummy

-0.118

0.158**

0.109*

(0.096)

(0.073)

(0.065)

Investment grade dummy

-0.349***

 

-0.158**

(0.071)

 

(0.076)

Amount issued (US$ billions)

-0.010

 

0.044

(0.079)

 

(0.058)

Tenor (years)

0.013

 

-0.002

(0.012)

 

(0.008)

Total assets (US$ billions)

 

-0.006***

-0.002

 

(0.002)

(0.002)

Leverage (%)

 

0.190

0.016

 

(0.128)

(0.117)

Public organization dummy

 

-0.024

-0.075

 

(0.064)

(0.075)

Observations

168

106

86

Pseudo R2

0.152

0.191

0.378

Robust standard errors are in parentheses

*** p<.01, ** p<.05, * p<.1

 

(2)

(3)

(4)

Model 2

Model 3

Model 4

Coupon step-up penalty (bps)

0.002**

0.002

0.002

(0.001)

(0.002)

(0.002)

Investment grade dummy

-0.424***

 

-0.223**

(0.088)

 

(0.104)

Amount issued (US$ billions)

0.034

 

0.040

(0.074)

 

(0.063)

Tenor (years)

0.022**

 

-0.002

(0.009)

 

(0.008)

Total assets (US$ billions)

 

-0.009***

-0.002

 

(0.002)

(0.002)

Leverage (%)

 

0.371*

0.105

 

(0.205)

(0.132)

Public organization dummy

 

0.066

-0.016

 

(0.079)

(0.066)

Observations

131

75

64

Pseudo R2

0.358

0.18

0.454

Robust standard errors are in parentheses

*** p<.01, ** p<.05, * p<.1

 

 

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Setting of first call dates

  • Issuers looking to minimize penalty payouts are best served by setting the first call date close to the target date.
  • Little incentive to call bond before target date as penalties kick in only afterwards.
  • But total penalty amount increases with the duration of time after the target date.
  • 83 percent have their first call date within 6 months of target date.

Figure 7: Distribution of Call dates relative to Target Dates

For visualization purposes, the plot excludes one outlier value of call date at 122 months after the target date.

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Who exploits these structural loopholes?

  • Issuers have more information than outsiders on likelihood of achieving targets, even at issuance.
  • At the very least, issuers have more information on the level of resources they plan to dedicate towards achievement of the targets.
  • Hence, we can expect self-selection into structural features, i.e., less motivated firms that are more likely to resort to these measures.
  • We use previous sustainability performance as a proxy for firm sustainability motivation.
    • Specifically, we use past CO2 emissions as majority of KPIs are related to carbon reduction.

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Table 7: Bond-Level Regression Analysis for Target Period with CO2 Emissions

 

(1)

(2)

(3)

(4)

Model 1

Model 2

Model 3

Model 4

CO2 Emissions (tens of millions tonnes)

0.005***

0.006**

0.008***

0.009***

(0.001)

(0.002)

(0.002)

(0.003)

Amount issued (US$ billions)

 

0.096

 

0.073

 

(0.089)

 

(0.099)

Tenor (years)

 

0.000

 

-0.003

 

(0.008)

 

(0.008)

Total assets (US$ billions)

 

 

-0.001

-0.001*

 

 

(0.001)

(0.001)

Leverage (%)

 

 

-0.221

-0.094

 

 

(0.156)

(0.216)

Public organization dummy

 

 

-0.206**

-0.150

 

 

(0.083)

(0.098)

Constant

0.587***

0.527***

0.877***

0.719***

(0.024)

(0.095)

(0.099)

(0.205)

Observations

60

51

60

51

Adjusted R-squared

0.012

0.057

0.075

0.157

Robust standard errors are in parentheses. *** p<.01, ** p<.05, * p<.1

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Table 8: Bond-Level Regression Analysis on Callability with CO2 Emissions

 

(1)

(2)

(3)

(4)

Model 1

Model 2

Model 3

Model 4

CO2 Emissions (tens of millions tonnes)

-0.0002

-0.001

0.010*

0.012**

(0.004)

(0.005)

(0.005)

(0.005)

Amount issued (US$ billions)

 

0.232**

 

0.227**

 

(0.109)

 

(0.098)

Tenor (years)

 

-0.007

 

0.000

 

(0.014)

 

(0.007)

Total assets (US$ billions)

 

 

-0.006***

-0.006***

 

 

(0.002)

(0.002)

Leverage (%)

 

 

0.192

0.083

 

 

(0.200)

(0.205)

Public organization dummy

 

 

-0.016

0.120

 

 

(0.098)

(0.108)

Observations

88

67

88

67

Pseudo R2

0

0.071

0.084

0.193

Robust standard errors are in parentheses. *** p<.01, ** p<.05, * p<.1

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Conclusion

  • SLBs with step-up penalties have significantly later target dates.
    • Penalty amounts are positively and significantly related to later target dates.
  • SLBs with step-up penalties tend to be more likely to include such call options.
    • Evidence suggests that such call options are designed in a manner to minimize potential penalties.
  • High polluters are more likely to set late target dates and include call options.

  • Implications:
    • We show that current SLB structures may be inadequate to hold issuers accountable for sustainability impact. Hence, investor concerns around greenwashing remain and need to be addressed for SLBs to achieve their potential.
    • Greenwashing concerns may potentially prove to be an even bigger issue for SLBs given that issue proceeds are not restricted for specific uses. Hence, issuers may be tempted by SLB premiums to issue these instruments as an effective strategy to lower the overall cost of capital for the firm, with little thought towards sustainability.

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Structural Loopholes in Sustainability-Linked Bonds

Imtiaz Ul Haq *

Djeneba Doumbia

*Corresponding author. Email: iulhaq@ifc.org

The findings, interpretations, and conclusions expressed in this paper do not necessarily reflect the views of the World Bank Group, its Board of Directors, or member states. Please do not share or distribute without authors’ permission.

Private Sector Development Research Network series - March 10th, 2023

Full paper can be accessed here.