Global shocks and green bonds issuance: An empirical evidence from firm-level panel data

Azhgaliyeva, Dina; Kapsalyamova, Zhanna Working Paper Global shocks and green bonds issuance: An empirical evidence from firm-level panel data ADBI Working Paper, No. 1447 Provided in Cooperation with: Asian Development Bank Institute (ADBI), Tokyo Suggested Citation: Azhgaliyeva, Dina; Kapsalyamova, Zhanna (2024) : Global shocks and green bonds issuance: An empirical evidence from firm-level panel data, ADBI Working Paper, No. 1447, Asian Development Bank Institute (ADBI), Tokyo, https://doi.org/10.56506/EWVX8548 This Version is available at: https://hdl.handle.net/10419/301952 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by-nc-nd/3.0/igo/ ADBI Working Paper Series GLOBAL SHOCKS AND GREEN BONDS ISSUANCE: AN EMPIRICAL EVIDENCE FROM FIRM-LEVEL PANEL DATA Dina Azhgaliyeva and Zhanna Kapsalyamova No. 1447 May 2024 Asian Development Bank Institute The Working Paper series is a continuation of the formerly named Discussion Paper series; the numbering of the papers continued without interruption or change. ADBI’s working papers reflect initial ideas on a topic and are posted online for discussion. Some working papers may develop into other forms of publication. The Asian Development Bank refers to “China” as the People’s Republic of China. Suggested citation: Azhgaliyeva, D. and Z. Kapsalyamova. 2024. Global Shocks and Green Bonds Issuance: An Empirical Evidence from Firm-Level Panel Data. ADBI Working Paper 1447. Tokyo: Asian Development Bank Institute. Available: https://doi.org/10.56506/EWVX8548 Please contact the authors for information about this paper. Email: [email protected], [email protected]u.kz Dina Azhgaliyeva is a senior research fellow, Asian Development Bank Institute, Tokyo, Japan. Zhanna Kapsalyamova is an assistant professor, Department of Economics, Nazarbayev University, Nur-Sultan, Kazakhstan. The views expressed in this paper are the views of the author and do not necessarily reflect the views or policies of ADBI, ADB, its Board of Directors, or the governments they represent. ADBI does not guarantee the accuracy of the data included in this paper and accepts no responsibility for any consequences of their use. Terminology used may not necessarily be consistent with ADB official terms. Discussion papers are subject to formal revision and correction before they are finalized and considered published. Asian Development Bank Institute Kasumigaseki Building, 8th Floor 3-2-5 Kasumigaseki, Chiyoda-ku Tokyo 100-6008, Japan Tel: +81-3-3593-5500 Fax: +81-3-3593-5571 URL: www.adbi.org E-mail: [email protected] © 2024 Asian Development Bank Institute ADBI Working Paper 1447 Azhgaliyeva and Kapsalyamova Abstract This paper investigates the determinants of corporate green bond issuance using annual firm-level data for 300 issuers of green bonds, which issued green bonds over the period 2017–2021. Using the Poisson fixed-effects models we find that bond-specific characteristics, such as maturity, coupon rate, and currency are important determinants of the green bond issuance. Issuers of green bonds prefer longer maturity. Thus, governments can promote green bonds by stimulating demand for them from long-term investors such as pension funds. The issuance of green bonds in EURO, USD, CNY, JPY, SEK currencies has a positive impact on their issuance. Governments can promote green bonds by stimulating local demand for them, that way issuance in local currency will be more attractive. Or governments can make it easier to finance green projects using green bonds in foreign currency by denominating revenues to foreign currency using policy instruments, such as a feed-in tariff. More green bonds are issued with a higher coupon rate to attract sufficient demand for them. Thus, policies that increase revenue from green projects, such as feed-in tariffs or subsidized loans, can promote financing projects using green bonds. The effect of the COVID-19 pandemic is positive but insignificant. Keywords: green bonds, COVID-19, green finance, bond maturity, coupon rate, currency JEL Classification: G15, G18, G28, G38 ADBI Working Paper 1447 Azhgaliyeva and Kapsalyamova Contents 1. INTRODUCTION .......................................................................................................... 1 2. LITERATURE REVIEW ................................................................................................ 2 3. DATA ............................................................................................................................ 3 4. METHODOLOGY ......................................................................................................... 4 4.1 Green Bond Characteristics ............................................................................. 5 4.2 Firm Characteristics ......................................................................................... 6 5. RESULTS ..................................................................................................................... 6 5.1 Main Results ..................................................................................................... 6 5.2 Robustness Check ........................................................................................... 8 6. CONCLUSION ............................................................................................................. 9 REFERENCES ...................................................................................................................... 11 APPENDIX A ......................................................................................................................... 14 ADBI Working Paper 1447 Azhgaliyeva and Kapsalyamova 1 1. INTRODUCTION Human-induced climate change has increased the probability of extreme events such as heatwaves, drought, heavy rainfall events, storms, and hurricanes (IPCC 2021). Limiting global warming to 1.5°C requires significant investments (IPCC 2022). Green bonds could play an effective role in drawing financial resources toward addressing such challenges. However, global shocks, such as the COVID-19 pandemic, war conflicts, etc. pose risks to the further development of the green bond market (Narayan 2020). The effects of such shocks on the issuance of corporate green bonds are understudied. This paper provides a comprehensive quantitative assessment of the COVID-19 pandemic on the issuance of green bonds at the firm level. The literature on the effects of global shocks on the issuance of corporate green bonds is limited in scope. Existing studies investigate the effects of oil price shocks on green bonds issuance (Azhgaliyeva, Kapsalyamova, and Mishra 2022), distinguishing between crude oil supply and demand shocks. Azhgaliyeva, Kapsalyamova, and Mishra (2022) find that both demand and supply shocks leading to the increase in the oil prices increase the issuance of corporate green bonds. Yang et al. (2022), studying the effects of armed conflicts on renewable energy finance, find a negative effect of the conflicts on renewable energy finance and green innovation. Flammer (2021) studies three major incentives to issue corporate green bonds, such as “signaling,” “greenwashing,” and “cost of capital” arguments. Companies issue green bonds because they want to send the signals regarding their environmental commitment (“signaling argument”), or they would rather prefer to present themselves as environmentally responsible without undertaking any rigorous commitments (“greenwashing argument”), or get access to cheaper financing (“cost of capital argument”). Flammer (2021) finds that corporate green bonds play a role in signaling the environmental commitment of the companies and does not find any evidence of “greenwashing.” We use annual data from green bond-issuing firms over the period 2017 to 2021. The data are sourced from the Bloomberg terminal and Compustat dataset by the Wharton Research Data Services. We include bonds that are labeled “green,” which are bonds that use the proceeds for green projects (Climate Bonds Initiative [CBI] 2016). To study the effects of the COVID-19 pandemic we use the Oxford stringency index and the binary variable that reflects the COVID-19 period. We show the effects of the COVID-19 pandemic and green bonds issuance at the issuer-level. The paper contributes to the existing literature in several ways. First, it provides additional evidence on the determinants of green bonds issuance at the firm level (Flammer 2020, 2021; Karpf and Mandel 2017; Zerbib 2019). Second, it contributes to the literature that studies the effects of the global shocks on energy finance, such as firm-level corporate green bonds (Azhgaliyeva, Kapsalyamova, and Mishra 2022; Yang et al. 2022). Third, the paper contributes to the literature that studies the relationship between environmental sustainable governance indicators and firm-level issuance of green bonds. Finally, the study contributes to the broader literature on finance that studies the effects of firm-level characteristics on the issuance of corporate green bonds. The remainder of the paper is structured as follows. Section 2 reviews the literature. Section 3 and 4 explains the data and methodology respectively. Section 5 discusses the results. Section 6 concludes. ADBI Working Paper 1447 Azhgaliyeva and Kapsalyamova 2 2. LITERATURE REVIEW The COVID-19 pandemic showcased the vulnerability of the global financial system to extreme events and natural disasters (Arif et al. 2022). High volatility in financial markets and pandemic-related significant losses in the stock markets demonstrated the need for safe-haven assets and portfolio diversification. During the COVID-19 pandemic, green bonds demonstrated “hedging and safe-haven potential” due to their marked differences from conventional bonds and diversification benefits (Arif et al. 2022; Naeem and Karim 2021; Nguyen et al. 2021). Likewise, Naeem and Karim (2021) find that green financial assets provide larger diversification opportunities compare to Bitcoin, implying that green investors pursue their green investments and avoid the financial risks, especially during turbulent times. Han and Li (2022), comparing portfolios with and without green bonds in the US and European markets, find that green bonds improve the risk and return profile of the portfolios in those markets. Reboredo, Ugolini, and Ojea-Ferreiro (2022), studying the de-risking ability of green bonds for low-carbon stocks in the People’s Republic of China (PRC), Europe, and the US, find that green bonds entail a de-risking capacity for low-carbon investments in the PRC and Europe, while they have no de-risking capacity in the US. Hacıömeroğlu, Danışoğlu, and Güner (2022), studying the performance of green and conventional bonds during the COVID-19 pandemic, find that primary market yields on green and brown bonds declined, while the yields on green corporate bonds declined more compared to conventional bonds, pointing towards a stronger demand for the former. They also find that corporate green bonds have safe-haven potential. The results are overall consistent with other literature on the resilience of social impact investing (Lins Servaes, and Tamayo 2017) that find that firms with high corporate social responsibility (CSR) intensity had higher stock returns compared to firms with low CSR during the 2008–2009 financial crisis. Yi et al. (2021), investigating the impact of COVID-19 on the PRC’s green bond market, find that the COVID-19 pandemic significantly increased the cumulative abnormal return of the green bonds. Guo and Zhou (2021) find that the green bonds have a great potential “to hedge against tail risks for traditional assets.” Elsayed et al. (2022) studying the interdependence between green bonds and financial markets, find that diversification benefits of green bonds exist in the short term. The hedging properties of green bonds reduce in the long term. Zerbib (2019) finds that the green bonds premium is either close to zero in several markets or is negative. Similarly, Löffler, Petreski, and Stephan (2021) find that yields for green bonds are 15–20 basis points lower than for conventional bonds, implying that a “greenium” exists. Teti et al. (2022) also find that the issuance spread of green bonds is 35 to 40 basis points lower than that of comparable conventional bonds. The studies explain such difference in spreads through the lenses of two theories: preferences of pro-environmental investors and the asset pricing theory. Investors engaged in sustainable and responsible investment (SRI) activities tend to be more concerned about environmental effects rather than payoffs. According to the asset pricing theory, lower yields of green bonds are due to the lower risks of green bonds. That is in contrast to Karpf and Mandel (2017), who find that the spread between brown and green bonds is positive and significant. The authors argue that the greenness features of the bonds are penalized by the markets, since green bonds have lower prices. That is supported by Wu (2022), who finds no negative green bond premium in the PRC or globally. ADBI Working Paper 1447 Azhgaliyeva and Kapsalyamova 3 Studies on the determinants of green bond issuance are rare. Cicchiello et al. (2022) study green bond issuance by examining the determinants of firms’ decisions over green and conventional bonds issuance in Europe. They find that the probability of issuing a green bond is affected by the corporate short-term debt repayment capability, debt maturity structure, and the presence of independent directors. They find that board gender diversity increases the green bond issuance. Barua and Chiesa (2019) study the determinants of green bond issuance, such as the bond characteristics and firm characteristics. They find that coupon rate has a negative and significant effect on the issue size of the bonds. Collateral security is likely to have a positive effect on the issue size. Bond credit rating also has a positive and significant effect on bonds issuance. The firm characteristics, such as firm size and firm profitability have a positive and significant effect on the issue size, whereas the firm’s revenue growth has a negative and statistically significant effect on the issue size. Another study by Lin and Su (2022) investigates the determinants of the issuance of green bonds in the PRC. They find that the costs and the size of bonds issuance have a negative and significant effect on the probability of green bonds issuance. The issuance of green bonds by corporates is preferred to the issuance of conventional bonds in the presence of poor financing conditions. Corporates that require large-scale funding would prefer conventional debt financing instruments. Firms with high environmental responsibilities would prefer green bonds. Some studies investigate whether green bonds are effective instruments in addressing climate change, especially during the times of economic distress (Flaherty et al. 2017). Flammer (2020) finds that the issuance of certified green bonds issuance has a positive and significant effect on the financial performance of firms in the long run. The issuance of green bonds leads to a reduction of companies’ CO2 emissions and increase their environmental ratings. Our study relates to the bulk of growing literature that investigates the determinants of the green bond issuance at the firm level. We also discuss the effects of the COVID-19 pandemic on the issuance of green bonds. 3. DATA Data on green bond issuance and on firm characteristics were sourced from the Bloomberg terminal and from the Compustat dataset by the Wharton Research Data Services, respectively. Our sample includes data from 1,778 green bond issuers from 2017 to 2021 (but the authors plan to update with 2022 in January 2023 and include a War variable). We include firm-level data of green bond issuers who issued bonds over the period 2017–2021. We also included a COVID-19 variable, which is measured using two variables: (i) as a binary variable (equals 1 in 2020–2021); or (ii) the country level annual average stringency index, which measures the strictness of “lockdown style” policies (Hale et al. 2021). The sample data is a balanced panel data with 1,778 firms over the period 2017–2021. Compustat data are firm-level annual data. However, Bloomberg data are green bondlevel data. In order to be able to merge both datasets, Bloomberg data were converted from daily green bond-level data to annual firm level. The amount of green bonds issued per firm i in country j per year t, 𝐵!"#, is calculated as a sum of all bonds issued in a year t per firm i in country j, 𝑏!"#: 𝐵!"# =∑𝑏!"# ⬚ ⬚. Annual firm-level coupon rate and maturity 𝑀!"# are calculated using an average of coupon rate and maturity 𝑚!"# , weighted by the share of issued green bonds %!"# &!"# :'𝑒.𝑔.,𝑀!"# =∑(𝑚!"# %!"# &!"#) ⬚ ⬚. ADBI Working Paper 1447 Azhgaliyeva and Kapsalyamova 4 Table 1: Summary Statistics Variable Obs Mean Std. Dev. Min Max Dependent variable Amount issued, share of assets 1,778 0.42 2.49 0 58.14 Green bond characteristics Maturity, years 1,778 1.27 3.35 0 60 Coupon, % 1,778 0.62 1.62 0 14 Currency: Other 1,778 0.80 0.40 0 1 CNY 1,778 0.05 0.21 0 1 EUR 1,778 0.08 0.27 0 1 JPY 1,778 0.04 0.19 0 1 SEK 1,778 0.02 0.14 0 1 USD 1,778 0.02 0.15 0 1 Issuer characteristics Size 1,778 11.85 2.85 2 19 Profit 1,768 0.07 0.05 0 0 Dividend 1,778 1.00 0.07 0 1 Leverage 1,733 2.09 15.32 –53 628 Tangibility 1,488 0.29 0.27 0 1 COVID, binary (=1 if t≥2020) 1,778 0.40 0.49 0 1 COVID, stringency index 0 100 Sector: Utility 1,778 0.18 0.38 0 1 Energy 1,778 0.05 0.21 0 1 Financial 1,778 0.46 0.50 0 1 Industrial, material, and technology 1,778 0.19 0.39 0 1 Other sectors 1,778 0.13 0.34 0 1 Note: N = 1,778; number of countries = 38; number of years = 5 (2017–2021). 4. METHODOLOGY The firms do not issue green bonds every year; therefore, the data contain many zero values. To exploit the unique nature of the data, we apply the Poisson fixed-effects estimator, as it provides robust estimation of conditional mean parameters (Wooldridge 2010). The model is specified as follows: &!"# '!"# =exp1𝛽𝑋!"# + 𝛾𝑌!"# + 𝛿𝐶𝑂𝑉𝐼𝐷"# + 𝜇!" + 𝑢!"#?, where the dependent variable &!"# '!"# is the annual issuance of green bonds as a share of total assets of firm i in country j in year t.'𝐶𝑂𝑉𝐼𝐷"# is measured using two indicators: First, using an indicator that is equal to one if'𝑡 ≥ 2020 and zero otherwise; second, using an annual average stringency index of country j in year t. 𝑋!"# is a vector of green bond characteristics; 𝑌!"# is a vector of firm characteristics. 𝜇!" are fixed effects and 𝑢!"# is the error term. The variance-covariance matrix of the estimates is obtained using the Huber/White/Sandwich linearized estimator. We also test for the presence of endogeneity in the regression. The Hausman test does not find evidence of endogeneity. 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Description of Firm Characteristics Variables Firm Characteristics Description Moody’s credit risk rating Credit rating from the highest quality Aaa (minimal risk) to the lowest quality C (in default)a ESG reporting score Bloomberg ESG reporting score, which varies from zero (not reporting at all) to 100 (the full reporting). ESG reporting Binary variable which equals one if ESG information is reported and zero otherwise Size Logarithm of total assets Profit Operating income before depreciation/total assets Dividend Binary variable, which equals one if a firm paid dividends or zero otherwise Leverage Total debt, as a share in total assets Tangibility Property, plant and equipment/Total assets a For more information see here https://www.moodys.com/sites/products/productattachments/ap075378_1_1408_ki.pdf. ADBI Working Paper 1447 Azhgaliyeva and Kapsalyamova 15 Table A2: Correlation Matrix lnta 1 0.3827* tltd 1 – 0.1932* – 0.0746* tangib~y 1 0.5270* – 0.1964* 0.0453 roi 1 – 0.0619* – 0.2142* 0.0093 0.0458 roa 1 0.8926* 0.0869* – 0.0543* – 0.0981* 0.0845* ssale 1 – 0.0076 – 0.0157 – 0.039 – 0.0975* 0.4830* 0.6819* fcf 1 0.0843 0.4026* 0.0302 0.7306* 0.2848* 0.2353* 0.0926 leverage 1 – 0.1419* – 0.013 – 0.0458 – 0.0393 0.0275 0.1269* – 0.0372 – 0.0105 dividend 1 – 0.0003 . – 0.1071* 0.0575* 0.0605* – 0.0836* – 0.0206 – 0.1235* – 0.1915* profit 1 – 0.0307 – 0.0606* 0.8710* 0.0578 0.6369* 0.5103* 0.4232* 0.0995* – 0.1347* 0.2276* Size 1 – 0.1347* – 0.1235* – 0.0372 0.2353* 0.4830* – 0.0981* 0.0093 – 0.1964* – 0.1932* 1.0000* 0.3827* esgrep~3 1 0.1383* – 0.0156 – 0.0126 0.0076 . 0.0544 0.1540* 0.1848* – 0.0816* – 0.0189 0.1383* 0.0417 esgdis~2 1 – 0.0929* 0.1686* 0.0147 – 0.0301 – 0.0588 0.2928* 0.0815 0.0444 0.0909* – 0.0545 – 0.1643* 0.1686* 0.1099* maturi~n 1 – 0.1282 – 0.0105 – 0.0875 0.0683 0.053 – 0.0373 0.032 – 0.0463 0.0427 0.013 0.0843 0.0381 – 0.0875 – 0.0134 cpn2 1 – 0.1456* 0.0271 – 0.1149* – 0.3489* 0.0011 – 0.0312 0.0618 – 0.1153 – 0.0884 – 0.0698 – 0.0468 0.0507 0.0529 – 0.3489* – 0.03 amtiss~d – 0.1334* 0.1162* – 0.1473* 0.0775 0.1720* – 0.2091* 0.0291 – 0.032 – 0.2227 0.0949 – 0.1512* – 0.0982* – 0.2744* – 0.1833* 0.1720* 0.1343* cpn2 maturity_d~n esgdisclos~2 esgreporti~3 size profit dividend leverage fcf ssale roa roi tangibility tltd lnta capex