(In)-Credibly Green: Which Bonds Trade at a

Green Bond Premium?∗

Julia Kapraun† & Christopher Scheins‡

This version: May 2, 2019

Abstract This paper provides an in-depth analysis of the green bond premium, so-called

Greenium, using both, primary and secondary market data. We consider a large sample of

over 1,500 green bonds issued worldwide and estimate the di�erences in yields of green and

comparable conventional bonds. Our primary market results reveal a signi�cantly negative

premium of 20�30 bps for green bonds, implying that at issuance, green bonds are trading

at lower yields than their conventional counterparts. This premium, however, varies across

currencies and issuer types and over time. In particular, credibility plays an important role

as bonds issued by more credible entities or bonds denominated in major currencies are issued

at lower yields. Using secondary markets data we �nd green bonds trading at higher yields

except for those issued by governments and supranational institutions. Further, bonds listed on

exchanges with a dedicated green bond segment trade at up to 13 bps lower yields, pointing out

the importance of transparency and clear standards for the growth of the green bonds market.

Finally, we reveal the relevance of the overall sustainability reputation of the issuer for the

acceptance of green bonds by investors. Here, we �nd the di�erence in yields between green

and conventional bonds to be higher (i.e., lower prices for green bonds) for the issuers coming

from both, the top and the bottom 30% based on the overall ESG rating, which might be due

to investors fearing green�labeling or green-washing e�ects.

Keywords: Green bonds, Sustainable investing, Green premium, Green exchanges

JEL Classi�cation: C33, G12, G14, G20, Q56

∗We thank Climate Bond Initiative for providing access to their data set and supporting the researchproject. We are also grateful for comments from Christian Schlag, Steven Ongena, Hannes Wagnerand Andreas Hoepner, and participants of the research seminars at Goethe University Frankfurt, Zurichuniversity, the EU conference �Promoting Sustainable Finance� in Brussels and Climate Bond Initiativeannual conference in London. Any errors, misrepresentations, and omissions are our own.†Corresponding author. Goethe-Universität Frankfurt, Theodor-W.-Adorno-Platz 3, 60323 Frankfurt,

email: julia.kapraun@hof.uni-frankfurt.de. Tel.: +49(0)69798 33728‡Goethe-Universität Frankfurt, Theodor-W.-Adorno-Platz 3, 60323 Frankfurt, email:

christopher.scheins@hof.uni-frankfurt.de.

1 Introduction

The conference on climate change held in Paris in 2015 paved the path for environmen-

tally sustainable growth and set a road map for countries to follow in order to keep the

average temperature from rising by more than 2 degrees Celsius by 2030. Three years

later, the most recent Emissions Gap Report published by UN Environment Programme1

revealed this target to appear illusory. Not only that most countries stayed far below their

Nationally Determined Contributions, but the total annual greenhouse gases emissions

reached a record high in 2017. To achieve the temperature goals of the Paris Agreement

countries will need to triple their e�orts and increase e�ectiveness of domestic policy.

Within this framework, green bonds, whose use of proceeds is earmarked to �nance or re-

�nance environmentally sustainable projects, are seen as one of the key catalysts bearing

the potential to drive the shift to a low-carbon global economy. Glomsrød and Wei (2018)

estimated that the diversion of capital from fossil industries to the green �nance sectors,

in particular through green bonds, would increase the world GDP and drastically reduce

the GHG emissions. Further evidence on the potential of green bonds in guaranteeing

economic sustainable growth is provided by Flaherty et al. (2017).

Our study is motivated by the ongoing debate about the credibility of green bonds and

the willingness of investors to pay a higher price for a green bond compared to the

conventional one. Our main research questions are (a) is there a di�erence in yields

between green and conventional bonds; (b) is there a variation across investors (primary vs

secondary markets), markets (currencies), issuers (corporates vs governments) and time;

and (c) are there any green bonds, which appear to be more reliable (�greencredible�) and

thus, trade at higher prices.

Over the past few years, the global market for green bonds increased signi�cantly and

reached 2017 volumes of about $155 bn, issued by governments, supranationals, and cor-

porates from di�erent sectors in over 30 di�erent currencies. With the rapidly growing

number of green bond issuers across the globe, the need for more transparency, regulation

1https://www.unenvironment.org/resources/emissions-gap-report-2018

1

and clear standards increases. Issuing green bonds is still a non-standardized process, and

each issuer and country can decide on the criteria making its bonds green. Though the

green bond principles have become the leading framework for issuance of green bonds2,

and EU Commission is working on a Proposal for a EU Green Bond Standard, these

guidelines are still voluntary, and there is no harmonized framework for eligible green

projects or yearly reporting. Many investors fear labeling e�ects or even green wash-

ing and question the �greencredibility� of issuers, which have a reputation of the major

polluters (e.g., from sectors such as transportation or nuclear power producers) or coun-

tries with the lowest environmental liability3. Though some studies �nd green bonds

value-enhancing and attracting new investor clientele (e.g., Flammer (2018)), based on

interviews with practitioners, Reed et al. (2019) claims green bonds to have not realized

a price premium due to investors not trusting the green label.

To investigate the existence of the green bond premium, so-called Greenium, we rely

on the analysis of both, primary and secondary market data across the full spectrum of

global green bonds. To the best of our knowledge, we are the �rst to collect and analyze a

large amount of the most recent and complete data on green bonds from di�erent sources.

Our initial data set contains 2,114 green bonds with a total issuance value of $487 bn with

the majority of these bonds issued within the last 2 years. To assess the pricing e�ect

of the green label, we, �rst, estimate the di�erence in the Yield at Issuance for green

and conventional bonds by controlling for di�erent bond characteristics and time e�ects.

Thereby we enlarge the available data set by computing the issuance yield from other

bond characteristics. This allows us to consider 1,520 green and 202,394 conventional

bonds in a �xed e�ects regression analysis, where we regress the Yield at Issuance on a

green dummy variable and di�erent controls.

In a next step, we consider bond prices and yields on the secondary market. While

the results on the primary markets can be driven by the strong institutional demand,

2See https://www.icmagroup.org/green-social-and-sustainability-bonds/green-bond-principles-gbp/ forthe most recent guidelines

3https://www.theguardian.com/world/2018/apr/17/poland-violated-eu-laws-by-logging-in-biaowieza-forest-says-ecj

2

sustainable investments have not reached same dimensions among private investors4. In

particular, these investors might question the greencredibility of di�erent issuers or not be

willing to pay a higher price for a green bond of the same issuer. To disentangle the green-

ness e�ect from the issuer speci�c e�ects, we match every green bond with corresponding

conventional bonds of the same issuer, same currency, same coupon type and same se-

niority. We then estimate the di�erence in yields for every green-conventional bond pair.

In contrast to other studies, we do not rely on option-based data or construct synthetic

conventional bond data, which both signi�cantly reduce the data sample. Our matching

method allows us to compare 4,609 bond pairs. Finally, we test for the credibility channel

to reveal possible reputational e�ects on the green bonds market.

Our study provide an in-depth analysis of several key issues with regards to the pricing of

green bonds. The results from primary market reveal a signi�cantly negative premium of

20− 30 bps for green bonds, implying that at issuance, green bonds are trading at lower

yields than their conventional counterparts. The e�ect is much stronger for green bonds

issued in USD than in EUR (41bps vs 17bps) and not signi�cant for green bonds issued in

CNY. We further observe varying premia across di�erent issuer types. In particular, we

�nd very high negative premia for green bonds issued by more reliable issuance entities

such as governments or supranationals, while the premia for corporate green bonds are

much smaller or even not signi�cant anymore after controlling for di�erent issue size

e�ects. We further �nd a lot of variation in premia over time. While there are months

in a raw with signi�cantly lower yields for green bonds during the hype period after

the Paris Agreement 2016 to 2017, in the last 2 years, there are only few months with

a non-zero green bond premium, and these usually are due to a single large issuance

by a government or supranational entity (e.g., government bonds issued by France in

January 2017 or Belgium in February 2018). This result indicates that though, through

the high institutional demand on the primary markets, green bonds trade at a higher

price than conventional ones on average, reputation aspects should be taken into account

when assessing the pricing implications for green bonds. These aspects are particularly

4So for instance, Union Investment reports 38bn euro in institutional portfolios, while there are only 3bnin private portfolios (see Boersenzeitung on February 15, 2019).

3

relevant in our secondary market analysis, where we even observe a positive premium for

green bonds. Here only green bonds issued by governments or supranational institutions

are traded at a small but signi�cant premium of -2 bps, while corporate bonds have on

average 43 bps higher yields than conventional bonds. This �nding clearly underlines the

importance of the issuer's credibility for the greenness reputation of the bond. Further,

we �nd the di�erence in yields between green and conventional bonds to be higher for

more liquid bonds with larger issue sizes. Most interestingly, we observe a signi�cant

e�ect of the listing of the bond, as green bonds listed on an exchange with a dedicated

green market segment (i.e., Luxembourg or London Stock Exchange) trade at up to 13

bps lower yields, on average. This indicates that green bonds on dedicated markets

appear to be more credible through additional visibility and transparency, and reveals

the importance of exchanges for the market growth. Finally, we reveal the relevance of

the overall sustainability reputation of the corporate issuer for the acceptance of green

bonds by investors. Here, we �nd the di�erence in yields between green and conventional

bonds to be higher (i.e., lower prices for green bonds) for the issuers coming from the

top and bottom 30% based on the overall ESG rating. A rationale explanation for this

�nding might be that on the one hand, investors fear green�washing e�ects for bonds

coming from companies with a rather bad ESG reputation and green labeling e�ects for

bonds issued by companies with a very good sustainability reputation.

Our paper contributes and adds to the growing literature on the pricing impact of in-

vestor's preferences for sustainable assets. Many recent studies provide evidence that

investors generally value sustainability (Hartzmark and Sussman (2019)) and are willing

to pay for non-pecuniary characteristics of investments (Barber et al. (2018)). The results

on the pricing implications for green bonds are, however, mixed. Some few studies report

green bonds trading at a lower yield than conventional bonds. For instance, Ehlers and

Packer (2017) analyze the credit spread at issuance of 21 green bonds; Nanayakkara and

Colombage (2018) or Preclaw and Bakshi (2015) apply option-adjusted spread data to

measure the credit spreads of green and conventional bonds; Karpf and Mandel (2018)

use Oaxaca-Blinder regression for municipal green bonds and �nd the premium to be

4

negative from 2015 on; or most recently, Zerbib (2019) reports a small negative green

bond premium of -2 bps for a global set of green bonds on the secondary market and

Baker et al. (2018) �nd higher prices for green municipal bonds at issuance. Other studies

(e.g., Karpf and Mandel (2017), Hachenberg and Schiereck (2018) or reports from CBI5,

or other practitioner's reports) document a contrary �nding on the sign of the premium

or even no signi�cant di�erence in yields. However, most of these studies rely only on

a very small set of bonds (less than 150, which accounts for less than 10% of the whole

sample) issued before the hype issuance years 2017 and 2018. Further, some do not take

time e�ects or other relevant bond characteristics such as currency or issuer characteris-

tics into account. Finally, none of the studies so far provided a full picture of the pricing

implication on both, primary and secondary markets or explored the greencredibility

channel.

2 Green bonds market

For this study we collect a large amount of data on green bonds from three di�erent

sources6. The initial data set contains 2,114 green bonds7, with a total issuance value of

$487 bn. A brief overview over some characteristics of the green bonds in our data set

can be found in Table 1. Around 75% of all green bonds in our sample have an issuance

volume below $350m. The average green bond is issued at a premium, with an average

maturity of 8.75 years, coupon of 3.40% and an issuance yield of 3.27%.

In 2007 the European Investment Bank pioneered the Green Bonds market by issuing

the �rst Climate Awareness Bond. 10 years later, more than 2,000 Green Bonds have

been issued in 30 di�erent currencies worldwide. The majority of these bonds followed

the Paris Agreement of 2015 with over 300 bonds issued yearly with increasing issuance

volumes. Figure 1 reports the yearly issuance volumes split per issuer type.

5See https://www.climatebonds.net/resources/reports/20186A list provided by CBI; Bonds from Bloomberg whose �Use of Proceeds� contains Green; Bonds fromReuters that are classi�ed as green

7We excluded more than thousand mortgage bonds issued by Fannie Mae with the average size of $23m

5

25% 50% Mean 75% 95% N

Coupon(%) 1.38 3.25 3.40 5.00 8.00 2,069Experienced 0.00 1.00 0.64 1.00 1.00 2,114GreenEX 0.00 0.00 0.21 0.00 1.00 2,114Issue Price 99.86 100.00 100.40 100.00 111.03 1,828Issue Yield 1.49 3.01 3.27 4.69 7.80 1,787Maturity(Years) 4.00 5.01 8.75 10.01 29.82 2,100Volume($Million) 11.02 65.55 234.22 302.07 890.04 2,111

Table 1: Descriptives of our dataset on green bonds.Coupon (%) is the size of the annual coupon of the bonds; Experienced is a dummy variable that isone if the bond is issued not on the same day as the �rst green bond of this issuer; greenEX is a dummyvariable that is one if the bond is listed on a green exchange; Issue Price is the price of the bond atissuance; Issue Yield is the yield to maturity of the bond at issuance, which is computed if no data wasprovided by Reuters; Maturity (Years) is the di�erence between the Issue Date and Maturity Date inYears; Volume ($Million) is the issue volume of the bond converted in million USD.

2010 2012 2014 2016 2018

Year

0

20

40

60

80

100

120

140

bnUSD

CORP

SOVR

SUPR

Figure 1: Volume of green bonds by issuer type

While the �rst green bonds were issued by supranationals8, by the end of 2018, corpora-

tions from di�erent sectors (e.g., energy, �nancials) and government entities are among

the largest issuers. Table 2 displays the top 10 Issuers with respect to the number of

bonds issued and issuance volumes. Nearly half of the corporate green bonds come from

8European Investment Bank (EIB) and World Bank

6

Issuer bnUSD # Issued Sector

European Investment Bank 40.19 49 Banking ServicesWindMW GmbH 29.37 80 Electric Utilities & IPPsÉlectricité de France S.A. 26.19 18 Multiline UtilitiesIBRD 17.00 158 Banking ServicesIndustrial Bank Co Ltd 16.93 7 Banking ServicesKfW 14.74 18 Banking ServicesMexico City Airport Trust 12.00 8 Collective InvestmentsInternational Finance Corp 8.46 77 Investment Banking & Investment ServicesNRW Bank 7.86 10 Banking ServicesShanghai Pudong Development Bank Co Ltd 7.59 3 Banking Services

Table 2: Top 10 Green Bond Issuer.Issuer is the most frequently used name for each Parent Identi�er, bnUSD is the USD equivalentissue volume, Number Issued is the number of Green Bonds that were issued by the Parent Identi�er,Sector is the most frequently named sector for each Parent Identi�er.

0-19 20-39 40-59 60-79 80-100

ESG Score

0

10

20

30

40

50

60

70

Frequency

Figure 2: ESG ratings for green bonds issuers

Banks, followed by Corporate Financial Services and Electric Utilities sector. Interest-

ingly, while most of these issuers have a solid reputation of sustainability in general,

there are several green bonds coming from companies with very low sustainability rank-

ings. Figure 2 depicts a histogram for ESG ratings based on available data for 126 issuers

from Thomson Reuters database. Thereby, the average company has an average score of

63.68 (score between 0 and 100), 25% of the issuers have a score below 53 and 10% have

a score above 83.

7

Alternative Energy

8%

Clean Transport

15%

Energy E�ciency

18%

Other23%

Eligible Green Bond Projects

35%

Green Amount Issued (bnUSD)

Alternative Energy

13%

Clean Transport

13%

Energy E�ciency

11%

Other

39%

Eligible Green Bond Projects

25%

Green Number Issued

Figure 3: Use of Proceeds of green bonds

Most of the green bonds from these issuers �nance renewable energy projects, energy

e�cient buildings or used to �nance clean transport and sustainable water management

projects, as can be seen from Figure 3.

Green Bonds are issued in every major currency across the globe, though there is a

strong focus on the Americas, Asia, and Europe. Figure 4 presents the number of bonds

and issuance for di�erent currency markets. Most and largest bonds are issued in USD

($157bn), Euro ($146bn), Chinese Yuan ($75bn) or the Swedish Krona ($23bn). Though

there are more than twice as many green bonds issued in USD compared to those issued

in EUR, these have lower issuance volumes, on average. With 16 per cent of the world's

green bonds China is emerging as a key player in the green bond market, though the

Chinese guidelines on the green bond issuance deviate from the international standard.

In particular, only 50% of proceeds are required to be invested in sustainable projects,

while it is the case for over 90% in Europe.9

In our sample we have in total 559 di�erent issuers. Figure 5 displays a histogram of the

9See https://www.bourse.lu/sustainability_standards_and_labels for di�erent green bond stan-dards.

8

SEK5%

Other

13%

CNY

16%

EUR 33%

USD

34%

Green Amount Issued (bnUSD)

SEK11%

Other

30%

CNY9%

EUR

15%

USD

35%

Green Number Issued

Figure 4: Green Bonds issued by currency

number of green bonds per issuer. More than 50% of the issuers in our sample have issued

one single Green Bond so far, while 5% issuers account for 50% of all issued bonds. 36%

of all issuers have only Green Bonds, which will be particularly relevant for our analysis

of the secondary bond market, where we compare Green and conventional bonds of the

same issuer.

In the last few years many exchanges have launched dedicated segments exclusively for

green bonds, which improved the liquidity and transparency of the green bonds market

and provided access to di�erent types of investors. More importantly, Green exchanges

increase credibility of the Green label as bonds listed in dedicated segments are usually

required to meet certain standards with respect to reporting, external reviews etc. For

instance, Luxembourg Green exchange, one of the �rst dedicated green bond platforms,

require issuers to align with Green Bond Principles, the CBI Climate Bonds Standard

eligibility taxonomy or another related frameworks10. Table 3 provides an overview of

green bonds from our sample listed on such Green exchanges.11

10See https://www.bourse.lu/sustainability_standards_and_labels for an overview of variousgreen bond standards.

11The list of Exchanges with a green bond segment is, however, not complete, as we only have information

9

1 2-4 5-10 >10

Number of Issues

0

50

100

150

200

250

300Frequency

Figure 5: Number of Green Bonds per Issuer

Exchange Number bnUSD

Luxembourg Stock Exchange 113 56.22Frankfurt Stock Exchange 89 53.44Milan Stock Exchange 39 34.40London Stock Exchange 59 11.17Stockholm Stock Exchange 61 4.24Oslo Stock Exchange 12 2.13Taipei Exchange 15 1.33

Table 3: Number and Issuance Volume of Green Bonds in our sample that are traded onthe Green Exchanges

3 Data and Methodology

3.1 Data

One of the most important steps of our analysis is the collection of all relevant data

on Green and conventional bonds and their issuers. To this end, we �rst obtain a list

on the bonds in our sample per end of 2018 with existing information on the listing.

10

of ISINs of Green bonds, by taking the union of a list provided by the Climate Bond

Initiative (CBI), bonds that are classi�ed as green in Reuters and bonds with �green�

use of proceeds �ag on Bloomberg. Over the last years, Fannie Mae, a US government-

owned entity that provides a secondary market for home mortgages, issued a lot of green

bonds, however we could not obtain any trading characteristics for the most of them. In

addition, these bonds are usually relatively small and, therefore, we excluded all of them

for our analysis. Our �nal set consists of 2,114 Green bonds.

Next, we collect ISINs of conventional bonds with di�erent coupon types, issued after

2009 and which started with all combinations that are present in the ISO 31661 alpha-2

list12. Though we focus on Fixed Coupon Plain Vanilla Bonds (FXPV) in our analysis,

we also included other bond types for issuers, which also issued at least one green bond.

This gives us a universe of 408,997 Green and conventional bonds in total.

Finally, we downloaded main characteristics of these bonds, i.e. the issue date, maturity

date, coupon, yield at issuance, amount issued, currency, sector, ratings from di�erent

agencies and others using Reuters and Bloomberg as our primary data sources. Summary

statistics for the bonds used in our primary and secondary analyses can be found in Table 5

and Table 6 in the following sections.

3.2 Primary market

To reveal possible di�erences in expected returns on Green and conventional bonds, in

this section we focus on Yields at Issue following Baker et al. (2018). Our basic panel

regression model is

Yi,t,b =7∑

k=1

αk + β ·Greeni,t,b +5∑

k=1

ck + εi,t,b (1)

12The �rst two letters of any ISIN can be used to identify most countries of origin with the help of theISO 31661 alpha-2 list, i.e. US is the two letter abbreviation for the United States and DE is the twoletter abbreviation for Germany. We extended the list with XS, as this abbreviation is frequently usedfor international issues

11

50% 75% 95% Mean Max

Conventional 1 2 5 1.98 157Green Bonds 1 1 2 1.32 33

Table 4: Number of bonds issued on the same day by the same issuer

where Yi,t,b is the yield at issuance of a bond, αk are Issuer, YearMonth, Currency, Rating,

Seniority, Maturity and Issue size �xed e�ects, and Greeni,t,b is our main variable, which

is 1 if the bond is labeled as green, and ck are di�erent controls. We include an indicator

variable Experienced which is one for all green bonds issued not on the same day as

the �rst green bond of the same issuer. Table 4 displays the summary statistics for the

number of bonds (Green and conventional) issued by companies on the same day. While

most of the companies issue only one green bond at the same time (mean of 1.32), there

are issuers which issue the whole range of green bonds (e.g., Quantum solar Park issued

33 bonds in October 2017). We further include 4 variables describing the most common

use of proceeds, i.e., Eligible Green Bond Projects, Clean Transport, Renewable

Energy and Energy E�ciency.

In this analysis we consider only bonds with available data on either Issue Yield or

Issue Price. We focus on Fixed Coupon Plain Vanilla Bonds, which allows us the exact

calculation of the Issue Yield using maturity, coupon rate and frequency and issue price

information. We end up with 1,520 Green and 202,394 conventional bonds in total. In

some speci�cations our sample is further reduced due to unavailable data on e.g., rating or

seniority. Table 5 provides descriptive statistics for the green (Panel A) and conventional

(Panel B) bonds used for this analysis.

The characteristics for green bonds are very much similar to our full sample in Table 1.

An average green bond in our sample has a maturity of 9 years, issuance volume of

$288m and is issued at a premium. 19% of all bonds are listed at Green exchanges. The

corresponding conventional bonds in Panel B have similar maturities and slightly higher

coupons and yields. Due to several extreme outliers the mean Issue Price and Issuance

volumes are signi�cantly higher than those for the green bonds, though when we compare

the 50 and 75 percentiles, the relationship changes.

12

Panel A: Descriptives of the Green Bonds

25% 50% Mean 75% 95% N

Coupon(%) 1.60 3.40 3.50 5.00 7.76 1,520Experienced 0.00 1.00 0.66 1.00 1.00 1,520GreenEX 0.00 0.00 0.19 0.00 1.00 1,520Issue Price 99.79 100.00 100.67 100.00 112.86 1,513Issue Yield 1.60 3.16 3.38 4.70 7.75 1,520Maturity(Years) 4.00 5.25 9.04 10.01 29.90 1,520Volume($Million) 15.07 99.92 288.13 426.49 1,000.00 1,518

Panel B: Descriptives of the Conventional Bonds

25% 50% Mean 75% 95% N

Coupon(%) 1.88 3.40 3.68 5.00 8.19 202,394Issue Price 100.00 100.00 140.59 100.00 115.21 198,282Issue Yield 1.69 3.00 3.46 4.50 8.21 202,394Maturity(Years) 3.01 5.56 7.63 10.01 20.01 202,354Volume($Million) 12.74 49.76 472.64 200.00 1,150.00 201,946

Table 5: Descriptives of Bonds used in our primary regressions.Coupon (%) is the size of the annual coupon of the bonds; Experienced is a dummy variable thatis one if the bond is issued not on the same day as the �rst green bond of this issuer; greenEX is adummy variable that is one if the bond is listed on a green exchange; Issue Price is the price of thebond at issuance; Issue Yield is the yield to maturity of the bond at issuance; Maturity (Years)is the di�erence between the Issue Date and Maturity Date in Years; Volume ($Million) is the issuevolume of the bond converted in Million USD.

13

In a sub-sample analysis we consider bonds issued in three major currencies to reveal

possible di�erences across markets and obtain 261 green bonds in EUR, 392 green bonds

in USD and 180 green bonds in CNY with available data on Issue Yield. We further

include a regression analysis for di�erent issuer types such as corporates, government

and supranational entities. Out of 1,520 green plain vanilla bonds 784 are issued by

corporates, 322 by supranationals such as e.g., European Investment Bank, and 414 by

government entities.

3.3 Secondary market

In our secondary market analysis, we study the determinants of the green bond premium,

here measured as the di�erence in the Mid quotes between Green and conventional bonds

yields, in more detail. One of the challenges in this analysis is to properly de�ne the

relevant data sample of Green and conventional bonds. To this end, for every green

bond we look for conventional bonds, issued by the same Issuer, with the same Rating,

Seniority, Currency and Bond Type. We focus on pairs of conventional and green bonds,

instead of triplets, as the Maturity di�erence between the green bond and the conventional

is constant and can be controlled for, by either using the Maturity di�erence or using pair

�xed e�ects. Further, we only take the comparable bonds that are closest with respect

to squared Maturity di�erences to the green bond to form a pair. Finally, we restrict

our list of comparables to contain at most 10 conventional bonds for each green bond.

This is mostly driven by data availability issues and the e�ort to have a similar weighting

of small issuers and issuers that have issued several thousand bonds in our sample13.

Previous approaches (e.g., used in Zerbib (2019) or Helwege et al. (2014)) use option-

based data or compare green bonds to synthetic conventional bonds. To create these

synthetic bonds, at least two comparable bonds are required. However, these methods

signi�cantly reduce the data sample and conclusions derived from less than 10% of the

sample might be questionable. In contrast, our methodology allows us to compare up to

13The biggest issuer in our sample has issued 16k bonds, with less than 1% of them classi�ed as Green,while around 300 issuers in our sample have issued only one green bond.

14

Panel A: Descriptives of the Green Bonds.

25% 50% Mean 75% 95% N

Coupon(%) 1.00 2.12 2.51 3.51 6.33 647Experienced 0.00 1.00 0.71 1.00 1.00 647GreenEX 0.00 0.00 0.32 1.00 1.00 647Issue Price 99.55 99.87 99.50 100.00 100.00 639Issue Yield 1.00 2.16 2.55 3.55 6.20 639Maturity(Years) 5.00 5.09 7.39 10.01 15.01 646Volume($Million) 112.44 407.30 441.21 511.82 1,250.00 647

Panel B: Descriptives of all conventional Bonds.

25% 50% Mean 75% 95% N

Coupon(%) 1.09 2.31 2.61 3.62 6.25 2,810Issue Price 99.51 99.89 99.33 100.00 100.16 2,707Issue Yield 1.34 2.52 2.78 3.80 6.25 2,702Maturity(Years) 5.00 7.01 8.87 10.01 27.69 2,812Volume($Million) 62.31 371.42 1,058.64 955.15 3,855.24 2,814

Table 6: Descriptives of Bonds that are used in our secondary market regression analysis.Coupon (%) is the size of the annual coupon of the bonds; Experienced is a dummy variable thatis one if the bond is issued not on the same day as the �rst green bond of this issuer; greenEX is adummy variable that is one if the bond is listed on a green exchange; Issue Price is the price of thebond at issuance; Issue Yield is the yield to maturity of the bond at issuance; Maturity (Years)is the di�erence between the Issue Date and Maturity Date in Years; Volume ($Million) is the issuevolume of the bond converted in Million USD. Note, that the conventional bonds can be used multipletimes and thus N does not match Table 10.

4,609 Green-conventional bond pairs and to control for di�erent �xed e�ects.

Thus the number of pairs we analyze is higher than in many other studies for several

reasons: we only need one comparable bond which allows issuers that only have few

bonds to appear in our sample; we only need bid and ask yield data for one comparable

bond. The latter is a rather important point, as we were able to obtain bid and ask yields

for only around one quarter of our pairs, through Reuters. For our analysis, we use the

mid quotes of both bonds in each pair and calculate the spread between the Green and

conventional bond, henceforth called GMC. Further variables that we calculate are the

bid-ask spread for green and conventional bonds, as well as the di�erences between the

bonds with respect to Maturity, Coupon, and Issue Size. Detailed statistics about the

15

available data used in our secondary sample can be found in Table 6.

To pursue the credibility channel we include an indicator variable greenEX which is 1

if the bond is Green and listed on an exchange with a dedicated green bonds market

segment. To take into account the ESG rating of an issuer, we create dummy variables

for di�erent ESG rating categories. To this end, we collect ESG ratings from Reuters (the

ESGScore) and from Bloomberg (the Sustainalytics rank, the Robecosam total stability

rank and the ESG disclosure score) for in total 122 issuers in our sample. We then

calculate the average of the four scores (or those that are available) for each issuer and

create a high (ESGHigh), a medium (ESGMedium) and low (ESGLow) dummy if

the average is in the top 30%, middle 40% or lower 30% of all issuers, respectively.

We obtain in total 777 green bonds with at least one comparable conventional bond issued

by the same company. 4,609 bond pairs result from each bond being compared to up to

10 out of 3,504 conventional bonds. Interestingly, green bonds issued by companies which

also issue conventional bonds, appear to have shorter maturities, much larger issuance

volumes and are issued at a discount in contrast to the average green bond from our

primary analysis in Table 5.

4 Results

4.1 Results primary market

Table 7 presents our main results for the total sample of 1,520 green bonds. After ac-

counting for di�erent Fixed E�ects (Models 2�4) all speci�cations support the prediction

that Green bonds are issued at a lower yield of 20 to 34 basis points than comparable

conventional bonds.

In Model (5) we consider pricing e�ects on bonds being issued after the very �rst Green

bond of the same issuer. Though insigni�cant, the negative coe�cient indicates that

bonds issued by experienced companies seem to appear more credible and trade at lower

yields at issuance. In Model (6) we control for di�erent types of Green projects and �nd

16

IssueYield

(1) (2) (3) (4) (5) (6)

Green −0.015 −0.198∗∗∗ −0.201∗∗∗ −0.338∗∗∗ −0.266∗∗∗ −0.457∗∗∗(0.060) (0.058) (0.063) (0.078) (0.067) (0.125)

Experienced −0.098(0.113)

Energy E�ciency −0.076(0.165)

Alternative Energy −0.035(0.179)

Eligible Green Bond Projects 0.158(0.137)

Clean Transport 0.194(0.205)

Issuer FE No Yes Yes Yes Yes YesYearMonth FE Yes Yes Yes Yes Yes YesCurrency FE No Yes Yes Yes Yes YesRating FE No No No Yes Yes NoSeniority FE No No Yes Yes Yes YesMaturity FE No No Yes Yes Yes YesIssue Size FE No No Yes Yes Yes Yes

Green Bonds 1,520 1,520 1,328 787 787 1,170Observations 203,914 203,914 165,631 82,357 82,357 53,032R2 0.017 0.771 0.789 0.672 0.672 0.753Adjusted R2 0.016 0.758 0.774 0.654 0.654 0.731

Table 7: Primary Market AnalysisThe table shows results of the Fixed E�ects regressions of bonds Yield at Issuance in basis points forGreen and conventional bonds. The Issue Yield of Green and conventional �xed coupon plain vanillabonds is regressed against a Green indicator, which is 1 if the Bond is a green bond and 0 otherwise.Experienced is a dummy variable that is one if the bond is issued not on the same day as the �rst Greenbond of this issuer; Energy E�ciency, Renewable Energy, Clean Transport and Eligible GreenBond Project are dummy variables indicating the use of proceeds for the corresponding bond. Weinclude Issuer �xed e�ects, YearMonth �xed e�ects, Currency �xed e�ects, Rating, Seniority, Maturityand Issue size �xed e�ects, to take into account substantial di�erences between issuers, the yield curve,di�erent interest rate environments in di�erent countries and the in�uence of ratings on the yield atissuance. The Maturity �xed e�ects are three buckets for short-term (less than 5 years), medium (between5 and 10 years) and long term (more than 10 years) time to Maturity. The Issue Size �xed e�ects arethe deciles of the issue (in USD) in comparison to all other issues that occurred before or in the samemonth as the Issue.

these also to be insigni�cant, though the coe�cient on the Green variable doubles in

comparison to Model (3). We further observe that categories Energy E�ciency and

Renewable Energy seem to be more accepted as green projects thanClean Transport

or a rather general category of Eligible Green Bond Project.

17

To shed more light on the di�erent currency and issuer type e�ects Table 8 presents

results of Model (3) of Table 7 for di�erent sub-samples. First, in Models (1) to (3) we

observe a strong variation in the premia across currencies. While the coe�cient on the

Green dummy for EUR denominated bonds is similar to the full sample (17bps), the

result for USD denominated bonds is more than double as high (41bps). Interestingly,

Green Bonds issued in Chinese currency CNY appear to be less attractive and trade at

similar yields as their conventional counterparts. This might be an indication that Green

bonds, which follow international (and not local Chinese) Green Bond Principles are more

recognized among investors.

IssueYield

(1) (2) (3) (4) (5)

Green −0.171∗∗∗ −0.410∗∗∗ 0.053 0.053 −0.310∗∗∗(0.052) (0.077) (0.050) (0.068) (0.101)

Subsample EUR USD CNY CORP SOVR+SUPRIssuer FE Yes Yes Yes Yes YesYearMonth FE Yes Yes Yes Yes YesCurrency FE No No No Yes YesSeniority FE Yes Yes Yes Yes YesMaturity FE Yes Yes Yes Yes YesIssue Size FE Yes Yes Yes Yes Yes

Green Bonds 261 392 180 784 544Observations 32,194 48,952 21,354 100,174 65,457R2 0.647 0.718 0.753 0.824 0.726Adjusted R2 0.615 0.696 0.721 0.804 0.722

Table 8: Primary Market Analysis (sub-samples)The table shows results of the Fixed E�ects regressions of bonds Yield at Issuance in basis points forGreen and conventional bonds. The Issue Yield of Green and conventional �xed coupon plain vanillabonds is regressed against a Green indicator, which is 1 if the Bond is a green bond and 0 otherwise.Experienced is a dummy variable that is one if the bond is issued not on the same day as the �rst Greenbond of this issuer; Energy E�ciency, Renewable Energy, Clean Transport and Eligible GreenBond Project are dummy variables indicating the use of proceeds for the corresponding bond. Weinclude Issuer �xed e�ects, YearMonth �xed e�ects, Currency �xed e�ects, Rating, Seniority, Maturityand Issue size �xed e�ects, to take into account substantial di�erences between issuers, the yield curve,di�erent interest rate environments in di�erent countries and the in�uence of ratings on the yield atissuance. The Maturity �xed e�ects are three buckets for short-term (less than 5 years), medium (between5 and 10 years) and long term (more than 10 years) time to Maturity. The Issue Size �xed e�ects arethe deciles of the issue (in USD) in comparison to all other issues that occurred before or in the samemonth as the Issue.

In our second sub-sample analysis in Models (4) and (5), we consider green bond premia

18

Figure 6: Green bond premium over time

for di�erent types of issuers. After controlling for the di�erent �xed e�ects, we �nd

very high negative premia of around 31 bps for green bonds issued by governments and

supranationals, while the premia for corporate green bonds are much smaller or even not

signi�cantly di�erent from zero. Green bond investors, thus, rely more on the greenness

of bonds issued by o�cial entities.

In our �nal analysis with primary data, we investigate the variation of the premia over

time. To this end, we consider the coe�cient on the Green×YearMonth interaction

term in Model (3) in Table 7. We depict our result in Figure 6 starting from the end

of 2014 due to unavailability of su�cient data points before this time period. What we

�nd is that the premium is highly volatile over time. While there are months in a raw

with signi�cantly lower yields for green bonds during the hype period after the Paris

Agreement 2016 to 2017, in the last 2 years months with a non-zero Green coe�cient are

scarce and depend on single large issuances (e.g., government bonds issued by France in

January 2017 or Belgium in February 2018).

19

This result emphasizes the complexity of the pricing implications for green bonds as we

can not generalize the negative premium for all green bonds at all times just because of

the green label, and in particular, it again, underlines the importance of the credibility

of the issuance entity.

4.2 Results secondary market

Our results from the primary market analysis are based on a broader sample of green

and conventional bonds coming from companies issuing only green, only conventional or

both types of bonds. In this section we want to disentangle the green e�ect from other

possible e�ects on the bond price as much as possible. To this end, we focus only on

those green and conventional bonds, which are issued by companies with an experience

in both types of bonds. We have already seen in Table 6 that these bonds are usually

much larger than the average green or conventional bond in our total sample. Further,

the proportion of the Experienced green bonds, i.e., bonds issued not as the very �rst

green bond of this company, is higher for this sample (71% vs. 66%).

Having 777 and 3,504 bonds in our sample, we redo our regression analysis in equation

(1), where we now regress the Yield to Maturity on the Green dummy variable. Here

we also include a liquidity control (BidAsk), as this is particularly important on the

secondary market. We further include all �xed e�ects speci�ed in section 3.2 with the

exception of the Rating FE, which would signi�cantly reduce our sample.

Our main result for this analysis can be found in Table 9 in Model (1), while Models

(2)-(6) present our sub-sample analysis. In contrast to our main result using primary

data in Table 7 Model (3), where particularly strong demand by institutional investors

drives the result, we �nd the coe�cient on the Green variable to be signi�cantly posi-

tive for the full sample. On the secondary market, green bonds trade at 14 bps higher

yields than comparable conventional bonds, indicating that investors on these markets

have either lower demand for green investments or do not trust the green label in general

and have additional requirements on the issuer. Models (2) to (4) con�rm our results

20

Yield to Maturity

(1) (2) (3) (4) (5) (6)

Green 0.141∗∗∗ 0.251∗∗∗ 0.121∗∗∗ 0.224∗∗∗ 0.435∗∗∗ −0.020∗∗∗(0.003) (0.003) (0.004) (0.007) (0.006) (0.003)

BidAsk 0.312∗∗∗ 0.490∗∗∗ 0.294∗∗∗ 0.030 0.281∗∗∗ 0.428∗∗∗

(0.024) (0.019) (0.019) (0.044) (0.019) (0.049)

Subsample FULL EUR USD CNY CORP SOVR+SURPIssuer FE Yes Yes Yes Yes Yes YesYearMonth FE Yes Yes Yes Yes Yes YesCurrency FE Yes No No No Yes YesSeniority FE Yes Yes Yes Yes Yes YesMaturity FE Yes Yes Yes Yes Yes YesIssue Size FE Yes Yes Yes Yes Yes Yes

Green Bonds 777 191 304 49 408 369Conventional Bonds 3,504 1,136 1,171 163 1,724 1,780Observations 2,666,070 949,923 861,516 37,316 1,258,488 1,407,582R2 0.721 0.685 0.547 0.597 0.653 0.806Adjusted R2 0.721 0.685 0.547 0.595 0.653 0.806

Table 9: Secondary Market AnalysisThe table shows results of the Fixed E�ects regressions of bonds Yield to Maturity in basis points forgreen and conventional bonds. The Issue Yield of green and conventional �xed coupon plain vanillabonds is regressed against a Green indicator, which is 1 if the Bond is a green bond and 0 otherwise,and the corresponding BidAsk spread.

21

on the currency e�ects, with green bonds issued in USD having higher yields of 12 bps,

while bonds issued in CNY and EUR have on average 22-25 bps higher yields than their

conventional counterparts. Most interesting is the result for the corporate vs sovr/govt

sub-samples in Models (5) and (6). Here only green bonds issued by governments or

supranational entities are traded at a small but signi�cant premium of -2 bps, while cor-

porate bonds have on average 43 bps higher yields than conventional bonds. This �nding

clearly underlines the importance of the issuer's credibility for the greenness reputation

of the bond.

In our �nal analysis we investigate the determinants of the di�erence in yields between

green and conventional bonds in more detail. To this end, we compare mid yields of green

bonds with up to 10 comparable conventional bonds of the same issuer, thus, ruling out

all possible factors at the issuer level, which might have an impact on the corresponding

bond price.

The results of this regression analysis of the Green-minus-Conventional (GMC) vari-

able on di�erent controls are presented in Table 10. First, we observe a signi�cant positive

e�ect of the liquidity in terms of Bid-Ask spreads on the green bond premium. Across all

samples, a higher spread on green bonds is associated with a higher yield of up to 47 bps

for the green bond, and, thus, a lower price compared to the conventional one (except for

(Model (3) with CNY bonds). Further, we consider the e�ects of di�erences in coupons,

maturity and issuance sizes. Intuitively, the larger is the di�erence in coupons and ma-

turities between green and conventional bonds, the larger is the di�erence between the

corresponding yields to maturity. Further, the larger is the issuance size on the green

bond compared to the conventional one the lower is the yield required by the investors.

One of the interesting �ndings in this analysis is the e�ect of our Green exchange dummy

variable. Green bonds, listed on the exchanges with a dedicated green market segment,

such as for instance, in Luxembourg or London, trade at up to 8 bps (full sample in

Model (1)) and up to 13 bps (government and supranationals sub-sample in Model (5))

lower yields than their conventional counterparts. One possible explanation for this result

might be the higher visibility and transparency for those bonds provided through these

22

GMC

(1) (2) (3) (4) (5) (6) (7)

Constant 0.094∗∗∗ 0.076∗∗∗ 0.102∗∗∗ −0.220∗∗∗ 0.090∗∗∗ 0.115∗∗∗ 0.057∗∗∗

(0.002) (0.002) (0.003) (0.008) (0.002) (0.002) (0.002)

dBA 0.424∗∗∗ 0.465∗∗∗ 0.466∗∗∗ 0.044 0.455∗∗∗ 0.158∗∗ 0.336∗∗∗

(0.031) (0.013) (0.012) (0.029) (0.017) (0.066) (0.046)

greenEX −0.076∗∗∗ −0.039∗∗∗ −0.078∗∗∗ −0.133∗∗∗ 0.079∗∗∗ 0.017∗∗∗

(0.001) (0.002) (0.002) (0.001) (0.002) (0.002)

dcoupon 0.025∗∗∗ 0.032∗∗∗ 0.140∗∗∗ 0.131∗∗∗ −0.013∗∗∗ 0.076∗∗∗ 0.095∗∗∗

(0.001) (0.001) (0.003) (0.004) (0.001) (0.002) (0.002)

dmaturity 0.082∗∗∗ 0.126∗∗∗ 0.067∗∗∗ 0.085∗∗∗ 0.083∗∗∗ 0.080∗∗∗ 0.130∗∗∗

(0.000) (0.001) (0.000) (0.007) (0.000) (0.001) (0.001)

dsize −0.045∗∗∗ −0.035∗∗∗ −0.030∗∗∗ −0.007∗∗ −0.046∗∗∗ −0.034∗∗∗ −0.051∗∗∗(0.001) (0.000) (0.001) (0.003) (0.001) (0.001) (0.001)

ESGHigh 0.132∗∗∗

(0.003)

ESGLow 0.111∗∗∗

(0.004)

Subsample FULL EUR USD CNY SOVR+SURP CORP CORP

Green Bonds 649 186 210 33 344 305 165Pairs 4,609 1,439 1,581 229 2,560 2,049 1,096Observations 1,604,958 553,594 524,180 23,114 951,028 653,930 403,535R2 0.416 0.704 0.231 0.257 0.591 0.161 0.219Adjusted R2 0.416 0.704 0.231 0.257 0.591 0.161 0.219

Table 10: Determinants of the Green bond premiumThe dependent variable Green-minus-Conventional (GMC) is the mid yield spread between the pairsof green and conventional bonds. The dBA is the di�erence between the bid-ask-spread for green andconventional bonds; greenEX is an indicator which is one if and only if the green bond in the pair istraded at a green exchange; dcoupon is the di�erence in percent between the green and conventionalbonds coupon; dmaturity is the di�erence in years between the green and conventional bonds timeto maturity; dsize is the di�erence between the green and conventional bonds issue size; ESGHigh isan indicator which is one if and only if the issuers' combined ESG Score is within the top 30% of allissuers; ESGLow is an indicator which is one if and only if the issuers' combined ESG Score is withinthe bottom 30% of all issuers.

23

platforms. But also additional requirements from the exchanges such as a certi�cation

or third party opinion, or the alignment with one of the well-accepted Green Bond stan-

dards, increase the reliability of the green bonds market. However, the positive e�ect of

the Green exchange does not hold in Models (6)-(7), where we observe a positive coef-

�cient on the dummy variable, i.e., higher yields to maturity for green bonds, issued by

corporates. There might be di�erent explanations for this �nding. First, the ratio of cor-

porate green bonds listed on such exchanges is much lower than that of government and

supranational bonds (one third vs. more than one half). Second, the variation between

di�erent characteristics of corporate issuers is higher than that between o�cial entities.

There might be also other unobservable e�ects which have a higher impact on corporate

bonds. We can already see the reduction of the magnitude in the coe�cient by including

additional variables related to sustainability in Model (7). Here, we present our results for

a smaller set of green-conventional bond pairs (half of the sample) with available data on

ESG rankings. Interestingly, we �nd bonds issued by corporations within both, top and

bottom 30% in ESG ratings, to trade at higher yields of 11�13 bps than bonds, issued by

corporations in the middle 40%. The willingness of investors to pay for greenness of the

bond, thus, does not linearly increase with the ESG rating of the issuer, but seems to be

rather a parabolic function. A rationale explanation for this, at the �rst sight, unexpected

�nding might be that on the one hand, investors fear green�washing e�ects for bonds com-

ing from companies with a rather bad ESG reputation. On the other hand, they are not

willing to pay higher prices for green compared to conventional bonds issued by the same

issuer with a very good ESG reputation, since these companies in general spend money

on sustainable projects. The green label appears here to be rather a marketing name

without a fundamental change in the company's practices. A natural implication will be

that there might be no need for those companies to issue both types of bonds any more.

On the one hand, if the issuance costs for green bonds (certi�cation or reporting costs)

remain to be noticeably higher than those for conventional bonds, companies with top

ESG ratings will stop issue green bonds. On the other hand, with increasing liquidity,

established issuance processes and increasing demand and acceptance for green bonds on

24

the market, the demand for conventional bonds might decrease, in general. The result for

companies with very low sustainability ratings is more intuitive, as in particular, insti-

tutional investor apply top�down approach in their asset selection process, and specify,

thus, �rst the pool of suitable companies and then the corresponding instruments. This

result underlines the importance of the overall sustainability reputation of the issuer for

the acceptance of green bonds by investors.

25

5 Conclusion

With emerging green bonds market, the need for more transparency, uniform standards

regarding use of proceeds, certi�cation and reporting becomes more urgent. Many in-

vestors fear green�washing or green�labeling e�ects and particularly, private investors,

are skeptical about the sustainability hype. Though recent studies provide evidence that

investors generally value sustainability and are willing to pay for non�pecuniary charac-

teristics of investments, the existing results on so�called green bond premium are mixed.

In this paper, we provide an extensive and up-to-date analysis of the green bond premium

on di�erent markets and across di�erent investors and issuers. Using data on more than

1,500 green and 200,000 conventional bonds we reveal about 20�30 bps lower yields at

issuance for green bonds. This negative premium varies, however, across currencies and

issuer types and, particularly, over time. It is higher for bonds issued by governments

or supranationals, for bonds denominated in USD or EUR or bonds issued during the

hype years 2016-2017. For corporate bonds, the results are much weaker, indicating lower

institutional demand and higher issuance challenges for these bonds.

In our secondary market analysis, where we consider over 4,609 green�conventional bond

pairs of the same issuer, we �nd the di�erence in yields between green and conventional

bonds to be positive (i.e., lower prices for green bonds) in general. Only bonds, issued

by governments or supranational institutions trade at lower yields (-2 bps) than their

conventional counterparts. Further, we �nd the overall sustainability reputation of the

corporate issuer to be very important for the acceptance of green bonds by investors.

Here we observe positive premia for both, bonds issued by companies with a very low

and a very high ESG rating. A rationale explanation for this �nding might be that on

the one hand, investors fear green�washing e�ects for bonds coming from companies with

a rather bad ESG reputation, and green labeling e�ects for bonds issued by companies

with a very good sustainability reputation. Finally, we reveal the increasing importance

of the green bond exchanges as market catalysts, as bonds listed on exchanges with a

dedicated green market segment trade at signi�cantly lower yields.

26

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