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. 2023 Jan 10;53:103638. doi: 10.1016/j.frl.2023.103638

How reactive is investment in US green bonds and ESG-eligible stocks in times of crisis? Exploring the COVID-19 crisis

Javier Perote a,⁎, José D Vicente-Lorente b, Jose Angel Zuñiga-Vicente c
PMCID: PMC9829434  PMID: 36643777

Abstract

This study examines how green bonds and environmental, social and governance (ESG) stock market returns have reacted to the COVID-19 crisis in the US. Unlike the Standard and Poor's (S&P) 500 index, the response of green bonds and ESG markets to pandemic progress is nonlinear: A low (large) level of confirmed new cases of COVID-19 has a positive (negative) impact. Furthermore, the implemented containment policies (stringency measures and vaccination campaigns) are positively valued, but their simultaneous use is perceived by investors as a bad signal. Overall, our findings question the resilience of investments in green bonds and ESG markets.

Keywords: ESG indices, Green bonds, Sustainable investment, COVID-19 pandemic, Stringency index

1. Introduction

The lively interest in sustainability is leading to a swift expansion of the ways to make socially responsible investments and the emergence of a large number of sustainability-themed financial products (Sandberg et al., 2009; Yen et al., 2019). The value of these investment products in international capital markets amounted to $3.2 trillion in 2020, which represented an 80% growth compared to 2019. Within these products, sustainable funds and green bonds reached values above $1.7 trillion and $1 trillion, respectively (United Nations Conference on Trade and Development, 2021). This ongoing demand for sustainability-themed financial products reflects the increasing concerns of investors in relation to social and environmental challenges, e.g., poverty and social exclusion, as well as gender equality and climate change, among others.

The global crisis caused by COVID-19 has more than ever brought sustainability concerns into the limelight, and thus provides an excellent opportunity for examining the potential success of sustainable investment when facing adverse and unexpected shocks (Albuquerque et al., 2020; Cardillo et al., 2022; Goldstein et al., 2021; Ramelli and Wagner, 2020). According to experts, the coronavirus crisis has aroused even more interest in these financial instruments as helpful vehicles for the so-called “green recovery”. In this context, large asset managers are also playing a key role in prioritizing the incorporation of environmental, social and governance (ESG) factors into more sustainable investment options in closer alignment with the new investor preferences (Zhan and Santos-Paulino, 2021).

Our study seeks to answer the following research question: How do investment-complying ESG criteria respond to the evolution of a crisis and its containment measures? To this end, we examine how green bonds as well as ESG and more conventional financial markets have reacted to the crisis caused by the spread of the COVID-19 disease in the US. Since the onset of the COVID-19 pandemic, a growing number of researchers have been interested in examining its potential impact on the evolution of investments in sustainability-themed financial products. However, the extant findings are not conclusive. Some studies find that the markets linked to the investment in sustainable products exhibit better behavior (whether in terms of returns, risk, volatility or hedging effectiveness) compared to conventional markets during the specific COVID-19 pandemic period examined (e.g., Broadstock et al., 2021; Yi et al., 2021), while others report either underperformance of the former type of markets (e.g., Cui et al., 2022; Dutta et al., 2021; Folger-Laronde et al., 2022), do not find significant differences (e.g., Capelle-Blancard et al., 2021; Chiappini et al., 2021; Demers et al., 2021; Pavlova and de Boyrie, 2022), or even note contradictory results (e.g., Gianfrate et al., 2021; Hacıömeroğlu et al., 2022; Omura et al., 2021; Umar and Gubareva, 2021; Umar et al., 2021).

Four critical factors for the lack of consensus can be identified. The first concerns to the specific sample period, i.e., most studies focus their attention on the first quarter of 2020 or very specific time windows rather than longer periods that take into account the different waves of the pandemic, as in this research. In this regard, our study sheds light on the response of green bonds and ESG index returns to the daily evolution of COVID-19 infection cases in the US, from the onset of the pandemic outbreak until February 2022, i.e., capturing the incidence of the most severe waves of the pandemic. Second, the set of indicators used as proxies for relevant factors of the pandemic in the stock market is diverse, including new COVID-19 confirmed cases or deaths (Al-Awadhi et al., 2020; Ashraf, 2020; Cao et al., 2021), the aggregated number of COVID-19 cases and/or deaths (Apergis and Apergis, 2022; Narayan et al., 2021), news on COVID-19 propagation (Umar & Gubareva, 2001; Umar et al., 2021), and administrative actions against the pandemic (Narayan et al., 2021; Zaremba et al., 2021). Third, although most previous works use different econometric techniques, all of them assume the existence of a linear relationship between the evolution of the pandemic and the performance of sustainable investment (thus discarding potential nonlinear linkages). We address this relevant feature by explicitly considering the impact of a severe movement in new infected cases and the interaction effects between the policies implemented in response to the spread of the pandemic. Finally, differences can be partially due to the country and market under analysis. Our research is restricted to the US market and the indices included in the Standard and Poor's (S&P) Global database in order to facilitate a straightforward comparison with prior research conducted in the same country.

In line with past studies (e.g., Gianfrante et al., 2021; Hacıömeroğlu et al., 2022; Rouatbi et al., 2021), and given the research target, our methodology relies on regression analysis. We use the daily reported new infected cases as a proxy for COVID-19 propagation, and the stringency index and vaccinations as the degree of containment measures (e.g., Rouatbi et al., 2021; Xie et al., 2022). However, unlike previous works, we propose a non-linear (quadratic polynomial) relationship between the new confirmed COVID-19 cases and stock returns. By relaxing the assumption that pandemic severity exerts a linear effect on stock performance, we may contribute to better understanding the inconclusive or contradictory results of extant empirical evidence. Furthermore, we explore the role of the progress of vaccinations campaigns and its interaction with other governmental policies implemented to contain the spread of COVID-19. Previous findings confirm that positive news on clinical trials on the vaccine was highly celebrated by stock markets at a global level (e.g., Chan et al., 2022), and the progress of vaccination campaigns also contributed to reducing volatility in financial markets (e.g., Rouatbi et al., 2021). Yet, to the best of our knowledge, the role of vaccinations on stock returns and its potential interaction with other containment policies remains uncharted. Although we have growing evidence on the negative or weakly positive impact of governmental reactions to the COVID-19 crisis on stock returns (Aggarwal et al., 2021; Cheng et al., 2022; Zaremba et al., 2021), we are not aware of any evidence on the interactions between the pharmaceutical solutions (i.e., COVID-19 vaccines), and other anti-COVID-19 measures approximated by the stringency index.

For comparison's sake, we estimated several models using as a dependent variable the daily returns of green bonds and ESG investments, as well as the S&P 500 and Dow Jones Industrial Average indices. As independent variables, we included the new confirmed cases and the quadratic transformation, in addition to the new vaccinations and their interaction with the stringency index − all of them in logarithms − as well as a set of variables approximating the state of the economy.

Our results show that new daily confirmed cases of COVID-19 have an overall positive effect on green bonds and ESG investment returns, although extreme variations (captured by a quadratic nonlinear form) exert a negative effect. This means that, while a “regular” (i.e., expected) evolution of the pandemic is relatively well digested by green bond and ESG markets (i.e., they anticipate the gains of sustainable investment in the long term), drastic variations in new COVID-19 cases have a deeper, instantaneous, and negative effect on the value of socially and environmentally responsible investments. Our findings also corroborate the relevance of both types of containment measures: new vaccinations and stringent governmental policies, considered in isolation, have positive and significant effects on stock returns. Yet, we also find a significant negative effect of their interaction. These results strengthen the logic that the relevant factors of the pandemic crisis exert non-linear effects on stock markets. In essence, vaccination and rigorous administrative actions are viewed as effective by stock markets but should be taken as substitutes, i.e., as the vaccination rate increases, only less stringent policies are positively valued by investors.

This nonlinear response to the COVID-19 daily reported information is also found for the Dow Jones index, which incorporates 30 of the biggest US industrial, technological, and financial firms. However, when considering returns related to a broader index, such as the S&P 500, the main effects of the evolution of the pandemic vanish. Therefore, firms considering ESG factors, as well as some big companies in particular (which may also comply with ESG criteria), seem to be more reactive to the evolution of the pandemic. These results help reconcile the apparently contradictory evidence of the under/out-performance of sustainable investment, which may be compatible once the effects of “extreme events” and the “efficiency of the measures” have been controlled for.

The remainder of the paper is organized as follows: Section 2 presents the model and the data, Section 3 describes the mains results and, finally, Section 4 concludes this work.

2. The model and the data

2.1. The model

Since we investigate the reaction of US green bonds and ESG indices to the spread of the COVID-19 disease in terms of the US economy, we merge two different databases. The S&P 500 Global data set records the dependent variables of our models, selected from a wide range of US ESG stock indices and green bonds. Daily returns (r t) are obtained from the prices (pt) as follows:

rt=100[ln(pt)−ln(pt−1)] (1)

The “Global Development Indicators” database of the World Bank provides the data for our independent variables. As a proxy for pandemic progress, we opted for the log transformation of “new COVID-19 confirmed cases” (cases t), collected at a daily frequency and excluding weekends for a consistent merge with data from stock and bond market returns. Our choice of this variable instead of other alternatives, such as “new deaths”, is based on the following considerations. First, the count of daily deaths is strongly determined by past new cases which will ultimately result in recoveries or deaths in the future. In fact, the number of new cases can be viewed as an anticipated good predictor of future deaths. In other terms, the information conveyed to stock markets by the new cases is timelier and more valuable than that provided by the new deaths. Second, this choice is supported by the previous findings of Ashraf (2020), who concludes that new cases of COVID-19 have a more significant effect on stock market returns than new deaths. As a proxy for the policies implemented to fight against the spread of the pandemic, we used the stringency index (stringency t), which is a composite measure based on indicators related to restrictions on citizen mobility and workplace closures, ranging from 0 (“no measures”) to 100 (“the strictest measures”). In addition, the new daily vaccinations (vaccinations t) are also used as another policy to fight against the pandemic implemented during the last waves of the pandemic. As a methodological novelty, we consider the interaction between both variables to examine their role as complementary vs. as substitutes. These variables have also been used in prior studies (e.g., Rouatbi et al., 2021), but, to the best of our knowledge, we have no evidence on this issue so far.

Finally, we use different explanatory variables for controlling the state and expectations of the economy, the market uncertainty, and alternative investments. In particular, the returns of exchange rates of the dollar with respect to the yuan (yuan t) and euro (euro t), the interest rates of 10-year US Treasury bonds (interest t) and Bitcoin (bitcoin t), and the logarithm of the Chicago Board Options Exchange Market Volatility Index (CBOE VIX) (vix t) for realized market volatility are selected. All of these variables are observed at a daily frequency and computed in logarithms or differences of logarithms. The data for these control variables were downloaded from Macrotrends/YCharts data sets. The full description of both the dependent and independent variables is provided in Table A.1 in the Appendix.

All econometric models have been estimated by ordinary least squares and they are represented in the following equation:

rt=β0+β1casest+β2casest2+β3stringencyt+β4vaccinationst+β5stringencytvaccinationst+β6yuant+β7eurot+β8interestt+β9bitcoint+β10CBOEvixt+ut (2)

where βi is the marginal effect of each variable and u t is the model disturbance which satisfies the usual assumptions.

2.2. The data

The period under analysis covers March 3rd, 2020, to January 28th, 2022, a total of 459 daily observations, after excluding weekends and missing observations. The descriptive statistics of the variables are displayed in Table 1 . All ESG indices and green bond returns considered exhibit the typical stylized features of financial returns, i.e., high volatility, positive skewness and leptokurtosis.

Table 1.

Descriptive statistics of the variables.

Variable Mean Std. Dev. Median Max. Min. Skewn. Kurtosis
Dow Jones Global US Select ESG RESI (returns) -0.0306 1.4649 0.0627 8.9164 -10.240 -0.9822 13.2134
S&P Green Bond US (returns) -0.0031 0.3667 0.0066 2.0127 -2.4099 -1.1626 9.8837
Dow Jones (returns) 0.0675 1.7564 0.1056 10.7643 -13.8418 -1.1165 17.7230
S&P500 (returns) 0.0829 1.6735 0.1606 8.9683 -12.7652 -1.0717 15.4041
New COVID-19 cases (logs) 11.0463 1.3481 11.1073 14.1289 2.9444 -2.0539 9.5869
Squared COVID-19 new cases (logs) 123.83 26,523 123.372 199.627 8.6697 -0.7033 3.2977
New_vaccinations (logs) 8.2510 6.9634 13.4885 15.3289 0.0000 -0.3332 -1.8766
Stringency index (logs) 4.0926 0.2177 4.1352 4.3236 2.4078 -3.4204 19.9835
Bitcoin price in USD (returns) 0.0032 0.0453 0.0025 0.1684 -0.3103 -0.7567 6.2246
Dollar/yuan (returns) 0.0002 0.0023 0.0001 0.0142 -0.0099 0.0158 4.2951
Dollar/euro (returns) 0.0000 0.0043 0.0001 0.0139 -0.0206 -0.3304 1.3901
US Treasury 10-year bond (returns) 0.0012 0.0565 0.0026 0.3890 -0.3045 0.0783 13.0959
CBOE VIX (logs) 3.1644 0.3239 3.1131 4.4151 2.7087 1.2059 1.7319
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3. Results

Table 2 presents the parameter estimates of the regression in Eq. (2) for two dependent variables: the returns of green bonds (S&P Green Bond US Select Index) and the returns of an ESG real estate index (Dow Jones Global US Select ESG Real Estate Securities Index [RESI]). For comparison purposes, we also include the results for the two most popular indices conventionally used to represent the US stock market behavior, the Dow Jones Industrial Average and the S&P 500 indices.

Table 2.

Impact of COVID-19 pandemic on stock market daily returns.

S&P Green Bonds Dow Jones Global US Select RESI (Real Estate) Dow Jones Industrial Average S&P500
New COVID-19 cases 0.2848
(0.080)		 1.8867
(0.026)		 1.8980
(0.045)		 1.1894
(0.187)
New COVID-19 cases2 -0.6673
(0.073)		 -4.3941
(0.024)		 -4.6122
(0.034)		 -3.0481
(0.140)
Stringency 0.5278
(0.008)		 3.2516
(0.002)		 3.3735
(0.004)		 2.6350
(0.017)
Vaccinations 0.1337
(0.042)		 0.8060
(0.019)		 0.9015
(0.018)		 0.6890
(0.057)
Stringency × Vaccinations -0.0331
(0.035)		 -0.1942
(0.018)		 -0.2176
(0.017)		 -0.1675
(0.053)
Yuan 43.7652
(0.000)		 155.5397
(0.000)		 88.4035
(0.003)		 99.2845
(0.001)
Euro 44.4962
(0.000)		 97.4591
(0.000)		 20.7002
(0.209)		 14.3638
(0.361)
Interest -1.2556
(0.000)		 4.4095
(0.000)		 16.9344
(0.000)		 15.1419
(0.000)
Bitcoin 0.5457
(0.033)		 2.2357
(0.093)		 7.4761
(0.000)		 8.3484
(0.077)
CBOE VIX -0.1796
(0.000)		 -0.9780
(0.000)		 -0.8363
(0.005)		 -0.8896
(0.002)
Intercept -0.9133
(0.075)		 -6.0592
(0.024)		 -5.8051
(0.051)		 -3.6781
(0.194)
R-squared 0.602 0.314 0.415 0.415
F-statistic 68.34
(0.000)		 20.66
(0.000)		 31.80
(0.000)		 31.73
(0.000)
LogLK 19.672 -743.61 -786.22 -764.24
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P-values in parentheses.

The first main result is linked to the impact of new cases of COVID-19, which seems to exert a positive effect on all dependent variables, except for the S&P 500. However, our evidence reveals that this effect is non-monotonic. In fact, the effect of the squared term of “new cases” –in logs– is negative and statistically significant. Furthermore, the consideration of this quadratic term is crucial for identifying the market reaction to the daily evolution of the pandemic: A controlled (explosive) evolution of the pandemic is interpreted by the ESG/green bond markets as good (bad) news, and thus makes yields increase (decrease) with the expectations of a faster (slower) recovery of the economy.1 The nonlinear (quadratic polynomial) relationship between both the ESG index and green bond returns and variables related to the daily spread of the pandemic is also statistically significant for the “blue chip” stocks likely represented in the Dow Jones Industrial index, but not for the S&P 500, whose reaction is statistically undetermined.

This result is robust along a wide set of green assets after controlling for a reasonable set of variables representing different aspects of the economy or the markets. For instance, exchange rates (of the yuan and euro) capture the consequences of the relative performance of these main economies on the future evolution of their financial markets. Our findings show that a depreciation of the dollar with respect to both the yuan and euro has a positive impact on the US ESG markets considered. On the other hand, US Treasury 10-year interest rates exert a positive (negative) impact on ESG stocks (bonds). This variable captures the impact of expectations on monetary policy and thus has a positive (negative) relation to green bond yields (ESG stock indices). Bitcoin has been considered as an alternative for investment that may be appealing in times of market turmoil (Omane-Adjepong and Alagidede, 2021). However, we find a positive covariation of Bitcoin returns with market indices, a signal of market integration. Finally, market uncertainty, measured as the volatility of the CBOE (VIX), exerts a negative effect on ESG and green bond markets.

The second main result is related to the effect of the policies implemented to fight against the pandemic measured in terms of either the stringency index or new vaccinations. Both variables have a positive impact on both green bonds yields and ESG indices, as well as on general market indices. However, the interaction between both variables exerts a negative impact on all the markets considered. This reveals that both policies are substitutes and the need to strengthen the restrictions regardless of the increase in vaccinations is definitely a negative signal for the investors. Therefore, the positive effect of the stringency index and the vaccinations become moderated by the joint effect of both policies as a proxy for their relative inefficacy as complements from the investors’ standpoint.

4. Conclusions

This research uses an original data set that combines daily information on new confirmed cases of COVID-19 and variables related to the policies implemented against the pandemic, as well as the daily returns of green bond/ESG markets in the US from March 3rd, 2020, to January 28th, 2022. This allows for establishing a closer connection between the daily evolution of the COVID-19 crisis, taking into account the most severe moments of the pandemic, and the subsequent daily reaction of US financial markets, particularly the green bond and ESG indices, are analyzed.

The main empirical contributions of this study are the following: First, we find that the response of green bond and ESG stock markets to the evolution of the COVID-19 pandemic is not linear but better fitted to an inverted “U-shape” relationship. Assuming that this non-linear pattern holds, imposing a linear specification may lead to inconclusive or even contradictory results depending on the pandemic severity (proxied by the new confirmed cases) which fluctuates widely along the pandemic period. For instance, if the sample (period) corresponds to one of the peaks of the waves of contagion, it is likely that the effect of the quadratic term will dominate the linear term and therefore a (restricted) linear specification can yield a negative effect of new cases on stock returns. Conversely, the estimated linear effect of such a restricted model will lead to support a positive (or a weaker negative) effect when the sample is characterized by a low-to-moderate progress of spread of the disease. Finally, whether the sample comprises a mix of both regimes (i.e., peaks and valleys of the evolution of new cases), the assumedly linear effect will be undetermined and/or statistically non-significant.

Most of the published empirical studies have used data from the early stages of the pandemic, likely to correspond to the (first) expansive cycle of contagions. Early works focused on the pandemic's impact on financial markets document a negative reaction of stock markets to new confirmed COVID-19 cases and deaths, assuming a linear relationship (e.g., Al-Awadhi et al., 2020; Ashraf, 2020; Topcu and Gulal, 2020). Our findings on the non-linear linkage impact of pandemic progress and stock returns may be useful for understanding and reconciling, to some extent, the controversial or inconclusive empirical evidence for this issue. In line with previous studies using data from the US (e.g., Gianfrante et al., 2021; Omura et al., 2021) and China (e.g., Broadstock et al., 2021; Yi et al., 2021), our findings show a significant and positive impact of a crisis situation related to the COVID-19 crisis on the returns of green bonds and ESG stock markets. This positive effect occurs when the number of cases confirmed is low-moderated. However, as the number of confirmed cases moves from moderate to high levels, this impact becomes negative, i.e., as the severity of the pandemic (crisis) situation increases. Therefore, the significant fall in returns of green bonds and ESG indices during the worst moments of the COVID-19 pandemic also reflects a strong negative sentiment among environmentally friendly investors. These findings are in line with results obtained by prior studies conducted in the US (e.g., Cui et al., 2022; Dutta et al., 2021; Umar and Gubareva, 2021; Umar et al., 2021). Interestingly, the nonlinear specification offers similar results in some “qualified” and narrow stock markets other than green/ESG indices such as the Dow Jones, but fails to be an accurate representation of the S&P 500.

On the other hand, the progress in vaccinations along with administrative anti-COVID-19 actions were positively valued by investors in the US financial markets. In this vein, our evidence adds to previous studies supporting the net benefit of government efforts to contain the pandemic crisis (Ashraf, 2020; Chang et al., 2021; Kizys et al., 2021). Interestingly, our findings on the substitutive nature of both types of containment measures stress the need to find and maintain a desirable balance between policies that can be good when considered individually, but harmful when implemented together.

In summary, our findings question the resilience of investments in green bonds and ESG markets when extreme negative variations occur in the evolution of COVID-19 and a battery of simultaneous restrictive crisis containment measures are implemented by the government. However, although investors in sustainable markets react in many cases quite similarly to those who invest in more traditional markets, they are also more reactive (either positively or negatively) to daily news on the COVID-19 evolution than the average investors in the US stock market (S&P 500).

Funding

This study was financially supported by the University of Salamanca (Program I.A., 2022) and Ministry of Science and Innovation (Spain) (Reference: PID2021-124641NB-I00).

CRediT authorship contribution statement

Javier Perote: Conceptualization, Methodology, Formal analysis, Software, Validation, Visualization, Writing – original draft, Writing – review & editing, Funding acquisition. José D. Vicente-Lorente: Conceptualization, Methodology, Formal analysis, Software, Validation, Visualization, Writing – original draft, Writing – review & editing. Jose Angel Zuñiga-Vicente: Conceptualization, Methodology, Data curation, Visualization, Supervision, Writing – original draft, Writing – review & editing, Funding acquisition.

Declaration of Competing Interest

None

Acknowledgments

We are grateful for the valuable comments from the participants of the International Conference in Sustainable Finance held in Madrid, 15–16 September 2022.

Footnotes

1

The estimated signs of the coefficients for the linear and quadratic terms (positive and negative, respectively) reflects an ‘U-inverted’ link between the net effect of the (log) new cases and the stock market returns. Since the logarithm of new cases is always greater than one in our sample, the net effect of a given increase (reduction) in the number of new cases will be related to a more than proportional decrease (increase) on stocks returns.

Appendix

Table A.1

Table A.1.

Data description.

Variable Description
S&P Green Bond Select Index Designed to measure the performance of US dollar-denominated, green-labeled bonds from the S&P Green Bond Index (daily log differences x 100).
Dow Jones Global US Select ESG RESI (Real Estate) Designed to measure the performance of publicly traded real estate securities in the Dow Jones Global Select RESI that meet sustainability criteria (daily log differences x 100).
S&P500 Tracks the stock performance of 500 large companies listed on stock exchanges in the US, eligible under market capitalization, liquidity, domicile, and public float, among other criteria.
Dow Jones Industrial Average Tracks the stock performance of 30 prominent companies listed in the US. It is price-weighted, unlike stock indices (such as the S&P500) which use market capitalization (daily log differences x 100).
COVID-19 cases New COVID-19 cases confirmed (daily login logs).
Vaccinations New daily vaccinations (in logs).
Stringency Stringency index (in logs); computed and registered by Ritchie et al. (2020).
Euro US dollar/euro exchange rate (daily log differences).
Yuan US dollar/yuan exchange rate (daily log differences).
Interest Interest rates of 10-year US Treasury bond (daily log differences).
Bitcoin Bitcoin price in US dollars (daily log differences).
CBOE VIX Index designed to measure the 30-day expected volatility of the US stock market, derived from real-time, mid-quote prices of the S&P500® Index (SPX℠) call and put options (in logs). This index is typically considered the world's premier barometer of equity market volatility and it is often referred to as the market's “fear gage”.
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Source: Bitcoin data were collected from https://finance.yahoo.com. The remaining data were extracted from S&P Global® (https://www.spglobal.com).

Data Availability

  • Data can be downloaded from free webpages.

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