The Influence of ESG Performance on Yield Spreads: A Comparative Study of Sukuk and Conventional Bonds in Emerging Dual Financial Systems

Abstract

This study comparatively examines the determinants of yield spreads for Sukuk and conventional bonds, with a particular focus on the role of firms’ environmental, social, and governance (ESG) performance. Using a dataset comprising 744 bond-year observations from issuers in countries with prominent dual financial systems—namely, Saudi Arabia, UAE, Turkey, Malaysia, and Indonesia—over the period 2008 to 2022, this analysis identifies distinct mechanisms that influence yield spreads in these asset classes. For robustness, the sample excludes financial institutions to prevent industry-weight distortion and to account for their distinct risk–return profiles, which require differentiated valuation approaches for conventional bonds and Sukuk. Drawing primarily on decoupling, information asymmetry, and legitimacy theories, our empirical results reveal that robust ESG performance is significantly associated with lower yield spreads for both Sukuk and conventional bonds. Moreover, the study explores the moderating effect of investment horizons on the ESG–yield spreads relationship, uncovering evidence of differentiated investor behavior in relation to yield curve positioning. These findings, robust across various regression specifications, underscores the pivotal role of ESG factors as firm-level drivers of financing costs, offering new insights for scholars, policymakers, and practitioners in the sustainable finance domain.

1. Introduction

The growing prominence of sustainability means that the integration of Environmental, Social, and Governance (ESG) is becoming a subject of “when” rather than “whether” it will penetrate and eventually revolutionize the mainstream practices of the business and financial sectors. An emerging trend in investment practice is the increasing integration of ESG considerations into investors’ decision-making processes alongside traditional financial metrics [1]. Nonetheless, consensus on the impact of ESG factors on investment outcomes remains elusive, with diverging evidence highlighting their roles in driving equity returns, companies’ valuations, the cost of capital, systematic risks, idiosyncratic volatility, and investment portfolio liquidity [2,3,4,5,6,7,8,9,10]. Still, there remains limited scholarly attention on the impact of ESG factors within the Sukuk market, despite its increasing prominence as a significant segment of the global financial landscape [11]. Therefore, our study aims to bridge this gap by providing empirical evidence drawn from the Sukuk market.

Sukuk offers a compelling context for this study. Although often regarded as the Islamic counterpart to conventional bonds—sharing features such as maturity term, coupon rate, yield–price relationship, and credit risks—Sukuk’s distinct underlying structures and contractual provisions continue to stimulate scholarly debate [12,13]. Despite a surge in research on ESG integration within conventional financial markets, the Sukuk market remains relatively underexplored. This oversight can be attributed to several factors. Primarily, Sukuk, as Islamic financial instruments, are typically confined to specific regions and exhibit unique structural characteristics dictated by Shariah law, which has directed academic attention toward conventional bonds where data availability and established methodologies prevail [14]. Furthermore, the nascent nature of the Sukuk market, compounded by regulatory and reporting challenges, has hindered comprehensive analysis of ESG factors. Accordingly, while ESG considerations have been extensively examined in the context of green bonds and sustainable investments, their impact and dynamics within the Sukuk market—particularly regarding their effect on yield spreads (as bonds constitute debt instruments on a corporate balance sheet, rising yield spreads indicate higher debt cost associated with weaker credit and default profile)—remain poorly understood [15,16].

The link between Sukuk and ESG investment is evident, as Shariah-compliant instruments not only enable international diversification but also align with ethical investment principles and sustainability values. A key aspect of Sukuk issuance is Shariah screening, which excludes firms involved in unethical activities (e.g., alcohol, tobacco, weapons, pork, or gambling). This “sin-free” criterion reinforces the responsible nature of Sukuk, paralleling green bonds within the growing emphasis on ESG criteria [17]. Consequently, Sukuk are increasingly attractive to socially conscious investors seeking ethical, sustainable alternatives in global capital markets.

This study examines the impact of ESG factors on yield spreads via two key channels. First, the legitimacy channel posits that robust ESG performance mitigates credit and default risks—by reducing legal, reputational, operational, and regulatory concerns—thereby narrowing yield spreads, while weaker ESG performance heightens these risks and widens spreads [18]. Second, ESG metrics reduce information asymmetry, enabling investors to make more informed decisions that further influence yield spreads [19,20]. Collectively, these channels suggest that a weak ESG profile leads to an unfavorable risk premium and wider yield spreads, whereas strong ESG performance is associated with a lower risk premium and reduced spreads.

Moreover, recognizing that ESG activities are integral to firms’ long-term stakeholder engagement, this study examines how different investment horizons moderate the ESG–yield spread relationship. Drawing on preferred habitat theory—which posits that investors favor specific maturities based on their mandates, institutional settings, or perceived risks—we categorize investment horizons into short-term, lower medium-term, upper medium-term, and long-term segments. This categorization allows us to investigate how yield spreads respond to variations in ESG performance across the yield curve. Although the asymmetrical effects of ESG on yield curves remain underexplored, our research sheds light on these dynamics.

Our study contributes to the literature on several fronts. First, it bridges the gap in understanding Sukuk yield spreads by integrating ESG factors into their evaluation. Employing panel regression models—including advanced dynamic panel methods—and leveraging a unique dataset of 744 bond-level observations from issuers in Malaysia, Indonesia, Saudi Arabia, UAE, and Turkey for the period of 2008–2022, this research broadens the scope of sustainable finance literature. Our findings reveal a negative association between firms’ ESG performance and yield spreads, with the social pillar showing the most significant impact. These insights offer valuable implications for academic inquiry and policy formulation in Islamic finance.

Second, although numerous studies have documented differences between Sukuk and conventional bonds, few have closely examined the dynamics of Sukuk yield spreads [21]. The relationships established for conventional bonds may not directly apply to Sukuk, given their unique economic and structural characteristics. By focusing primarily on Sukuk, this study offers fresh insights that can enhance asset allocation and risk management strategies, thereby benefiting policymakers and investors, including asset managers. Drawing on decoupling hypotheses and investor preferences, our findings reveal significant differences in the determinants of yield spreads between Sukuk and conventional bonds.

Finally, this study advances the literature by examining how investment horizons moderate the relationship between firms’ ESG practices and yield spreads. Our findings indicate that the impact of ESG activities varies along the yield curve, with distinct effects emerging for shorter term horizons compared to longer periods across both Sukuk and conventional bonds. These results reveal notable ESG-investing patterns related to yield curve positioning, underscoring the critical role of investment horizons in shaping ESG investment decisions. Overall, our study provides robust evidence that the transmission of ESG effects is significantly influenced by the investment horizon.

This paper is structured as follows. Section 2 reviews the relevant literature, while Section 3 details the hypothesis development. Section 4 describes the data and research methodology, and Section 5 presents the results. Finally, Section 6 and Section 7 discuss the key findings and offer concluding remarks and implication.

2. Literature Review

2.1. Sukuk, an Emerging Asset Class

Sukuk, derived from the Arabic term “Sack”, is commonly translated as Islamic investment certificates [22]. While they are often referred to as “Islamic bonds” due to their conceptual resemblance to conventional bonds, a more precise understanding is that Sukuk represent “certificates of equal value” tied to underlying tangible assets, usufructs, or services [23]. In contrast to conventional bonds, which are purely debt instruments, Sukuk are structured to comply with Shariah (Islamic law), thereby prohibiting the payment or receipt of interest (riba) and requiring asset-backed or asset-based transactions [24].

By design, Sukuk differ fundamentally from conventional bonds in three major respects: (i) the absence of interest-based returns, (ii) the focus on real economic activity, and (iii) the avoidance of repugnant (haram) activities, such as gambling or the production of alcohol and other forbidden goods [17]. The concept of profit sharing lies at the core of Islamic finance, thereby dictating the mode of returns on Sukuk. Mudarabah, Murabahah, and Ijarah are common contract types underlying Sukuk structures, reflecting profit-and-loss sharing, cost-plus sales, and asset-leasing paradigms, respectively [17]. Consequently, the performance of Sukuk is directly tied to the actual cash flows generated by an underlying asset or project, in stark contrast to conventional bonds, which hinge on predetermined interest payments [25].

A critical feature of Sukuk lies in Shariah’s injunction against purely speculative or virtual securities, mandating that all financial products be anchored in tangible, real-economy assets [17]. As such, derivatives or other structured instruments without clear underlying assets are generally not permissible within Islamic finance. This asset-backing principle is intended to promote transparency, reduce excessive uncertainty (gharar), and align financial returns with actual economic productivity rather than purely financial engineering.

Another central aspect of Sukuk issuance involves Shariah screening for activities considered unethical or harmful—such as the production or sale of alcohol, tobacco, weapons, pork, or involvement in gambling. Firms engaged in these sectors are excluded from Shariah-compliant financing, reinforcing the “sin-free” and often “carbon-free” nature of many Sukuk issuances. In this respect, Sukuk increasingly parallel green bonds, as both align with the rising emphasis on Environmental, Social, and Governance (ESG) criteria in contemporary investment strategies [26]. The Shariah requirement to avoid repugnant activities resonates with broader responsible investing frameworks, underscoring Sukuk’s growing appeal to socially conscious investors seeking ethical, sustainable alternatives in global capital markets.

The emergence of Sukuk is deeply rooted in the cultural and institutional context of Islamic finance in Muslim-majority countries. Governments’ active participation is instrumental in advancing Sukuk development by establishing legal frameworks for Shariah-compliant contracts, Islamic benchmark yield curves and indices, and institutionalizing compliance through scholar boards and standards, underscoring the distinct evolution of Sukuk markets relative to other conventional financial markets [27]. This oversight not only meets the religious and ethical expectations of Muslim investors but also fosters thriving Sukuk markets in supportive jurisdictions.

2.2. Foundation and Frontiers in Sukuk Studies

Over the past two decades, research on Sukuk has grown markedly compared to conventional bonds [28,29]. Early studies examined Sukuk’s unique features—such as liquidity profiles, return dynamics, risk, volatility, and issuance processes—to understand how Islamic finance principles like the prohibition of riba and asset-backing requirements distinguish Sukuk from interest-bearing instruments. Pioneering work by [30] highlighted Sukuk’s innovative asset ownership structure, while ref. [31] contrasted its asset-purchase model with the fixed-interest framework of conventional bonds.

Subsequent research has examined the behavior and performance of Sukuk versus conventional bonds under varying market conditions. For instance, ref. [32] demonstrated that including Sukuk in a Eurobond portfolio can reduce risk, while studies by [33,34,35] confirmed their potential to enhance portfolio efficiency. Additionally, ref. [36] found that liquidity risk premia for Sukuk are influenced by a hold-to-maturity strategy, and research by [37,38] indicates that during economic uncertainty, Sukuk may decouple from conventional bonds, offering hedging benefits. Finally, ref. [39] revealed that macroeconomic shocks affect these instruments differently, suggesting that Sukuk can serve as a stabilizing force in volatile markets.

A significant strand of research examines issuance decisions and the firm-level determinants distinguishing Sukuk from conventional bonds. Ref. [40] found that in the GCC region, firm-specific factors—such as ownership structure, corporate governance, and compliance—more strongly influence Sukuk issuance, whereas conventional bonds tend to be driven by credit ratings. Ref. [41] corroborate that while broader market motivations guide conventional bond issuance in general, Sukuk issuers are additionally influenced by strategic and religious imperatives inherent to Islamic finance. Such dynamics underscore the interplay between corporate characteristics and the regulatory or cultural environments that shape Sukuk adoption.

In addition to direct Sukuk–conventional bond comparisons, recent studies have examined cross-market correlations among equities, commodities, and other asset classes. Ref. [42] reveal that Sukuk tend to be net recipients of return and volatility spillovers—particularly from equity markets—while conventional bonds exhibit weaker spillovers. This finding supports [43]’s assertion regarding the interconnectedness of financial markets and the critical role of volatility transmission in portfolio risk management. Although some critics [44,45,46] argue that certain Sukuk structures share characteristics with conventional bonds (e.g., coupon rates, maturity terms, or yield–price mechanisms), an expanding literature [35,38,39] consistently documents meaningful differences in how Sukuk respond to market stresses and macroeconomic shocks, reinforcing their distinct risk–return profiles and issuance motivations.

Overall, the literature on Sukuk has evolved from comparative structural analyses to a more multifaceted examination of risk, return, diversification potential, and the socio-cultural drivers underlying their development. These diverse findings highlight Sukuk’s growing importance in global capital markets, while also sparking debates over the extent to which their Shariah-compliant frameworks translate into genuinely distinct financial outcomes relative to conventional bonds.

2.3. Theoretical Framework on Sukuk, Conventional Bond, and ESG Interplay

Recent research in the conventional bond market has increasingly focused on exploring the relationship between sustainability practices and the cost of debt. Refs. [18,47] employ quantitative methods to investigate whether firms with robust ESG practices can secure lower debt costs. Similarly, ref. [10] examine both the direct impact of ESG performance on firms’ ability to obtain cheaper financing and the indirect effects mediated by credit rating agencies’ assessments of ESG factors.

Somewhat comparable to our study, ref. [44] found that corporate governance mechanisms significantly reduce yield disparities between Sukuk and conventional bonds, suggesting that enhanced transparency and board independence lower the perceived risk of Sukuk. However, their analysis primarily focused on corporate governance, omitting other crucial sustainability pillars. In contrast, ref. [28] observed that Sukuk yield spreads are generally lower than those of conventional bonds—indicating comparatively lower risk—by emphasizing various firm-specific factors. These equivocal findings leave unresolved the question of how ESG practices collectively underpin the differences between Sukuk and conventional bond yield spreads, thereby motivating further investigation.

The decoupling hypothesis serves as the primary theoretical framework to explain differences between Sukuk and conventional bonds. This perspective posits that Islamic assets differ from conventional instruments not only in their underlying features but also in their behavior, owing to a unique risk–return profile derived from asset-based or asset-backed financing as opposed to the interest-based nature of conventional financing [31,48]. The existing literature on decoupling demonstrates that Sukuk offers diversification benefits relative to conventional bonds, largely due to lower volatility and distinct dynamic correlation patterns [39]. While empirical findings on decoupling are mixed—with most studies focusing predominantly on return and volatility correlations [49,50,51]—there remains a notable gap in research examining Sukuk yield spreads, despite their critical role in pricing mechanisms.

The decoupling hypothesis is complemented by the investor taste perspective advanced by [14,52], which suggests that preferences for specific asset characteristics can lead to portfolio allocations that deviate from those predicted by expected utility maximization [53]. In this context, taste-based investors may include those with an Islamic mandate, a need for risk diversification, or a personal faith-based commitment. This perspective implies that Sukuk exhibits a unique demand distribution that produces a distinctive risk–reward profile, as evidenced by its yield spreads. Furthermore, ref. [14] concluded that investors’ non-pecuniary preference for Shariah-compliant features is a key determinant in the valuation of Sukuk.

Meanwhile, the literature on ESG in asset pricing is expanding [54,55,56]. Legitimacy theory posits that firms must secure societal approval through stakeholder engagement—particularly via environmental and social practices—which directly affects their credibility and cost of capital [57,58,59]. When firms fail to meet ESG expectations, they risk higher business and financing costs due to increased scrutiny, resource constraints, and reputational damage [57]. To address these pressures, firms adopt either a substantive approach—reflecting genuine adherence to social norms—or a symbolic approach, which can border on greenwashing if used merely to enhance reputation [60,61,62]. These dynamics raise critical questions regarding the agency costs of ESG practices, as conflicts among management, shareholders, and debtholders may undermine the benefits of ESG initiatives despite their potential to reduce information asymmetry and lower debt costs [20,63,64,65].

Moreover, while legitimacy and information asymmetry theories explain ESG’s role in asset pricing, they do not capture its differential effects along the yield curve. Preferred habitat theory suggests that fixed-income investors, particularly long-term institutional players [64,65,66,67], favor investments with specific maturity profiles. This implies that Sukuk investors are influenced not only by Shariah compliance but also by investment horizon considerations. Integrating decoupling and preferred habitat theories, our framework tests for a preferred duration among Sukuk investors and its impact on yield spreads.

Additionally, stakeholder salience theory underscores that long-term institutional investors significantly shape corporate social performance, further reinforcing the interplay between investment horizons and ESG outcomes [68,69,70]. This synthesis offers a nuanced perspective on how ESG factors drive yield spreads and informs our investigation of ESG impacts in both Sukuk and conventional bonds.

However, while individual frameworks—such as legitimacy theory, agency cost theory, information asymmetry, and stakeholder salience theory—each shed light on specific channels through which ESG engagement affects financial outcomes, together, they offer a comprehensive perspective on their joint impact on yield spreads, underscoring the central contribution of this ESG–Sukuk yield spread study. Legitimacy theory posits that firms engage in ESG practices to secure social approval and avoid reputational and monetary costs associated with non-compliance [57,58,59]. This drive for legitimacy, whether pursued substantively (genuine adoption of best practices) or symbolically (emphasis on image or appearance enhance stakeholder perceptions) [60,61,62], influences investor confidence and, ultimately, the cost of financing. In parallel, agency cost theory and information asymmetry suggest that robust ESG disclosure can alleviate conflicts among management, shareholders, and debtholders by reducing hidden risk, thereby lowering the cost of debt [19,63,71]. Yet, these theories alone do not account for how investor preferences—especially those aligned with long-term horizons due to stakeholder salience and preferred habitat theories [64,65,66,67,68,69]—moderate the relationship between ESG performance and yield spreads. In the context of Sukuk, whose investor base is uniquely shaped by both Shariah compliance and duration-driven preferences, this integrated framework becomes crucial. By combining these theoretical strands, our study proposes that robust ESG performance not only reduces perceived risk and agency costs but also aligns with the long-term investment horizons favored by key institutional investors. This, in turn, results in lower yield spreads for both conventional bonds and Sukuk, while also revealing nuances in market pricing that may differ by asset type. Hence, the synthesis of these theories enables a deeper exploration of the multi-dimensional effects of ESG engagement, offering a unique contribution to the literature by linking these mechanisms explicitly to variations in yield spreads across different financial instruments.

3. Hypothesis Development

3.1. Decoupling of Sukuk and Conventional Bond Spread

One crucial perspective in the Islamic literature is the Sukuk–conventional bond decoupling. Despite the mixed finding generated across the literature as mentioned in the theoretical framework, prior studies still demonstrate a good amount of empirical evidence that Sukuk remains a unique and alternative asset class to its conventional peers [32,34,36,37]. Ref. [44] reveals a generally different pattern of Sukuk yield spread compared to conventional bonds. Nonetheless, despite the rising recognition, the coverage of empirical studies remains inadequate in most areas, as compared to the conventional space, especially over the ESG fronts and their impacts on the Sukuk. This study therefore aims to build on the foundation laid in the existing academic reservoir by investigating the comparative impacts over Sukuk against conventional bonds through the lens of the firm’s ESG activities.

The controversy over yield spread decoupling arises over the basis of valuation that is traced to the underlying structuring differences (Sukuk is partly derived from its underlying assets as compared to the conventional bond reflective mainly of the issuer’s creditworthiness) [25,27,72]. Structure-wise, the former also must adhere to a strict ethical filter and legal requirement before issuance [44]. Therefore, a more differentiated approach, as underlined by both theoretical and empirical grounds, to Sukuk yield spread is the adopted stance for this study on the impacts of ESG.

3.2. The Impact of ESG Performance on the Yield Spread

The growing attention on responsible investment reflects a heightened awareness among the investing community of financial and reputational risks linked to their decisions, with market scrutiny increasingly shifting its focus to investors’ role in the past financial crises and recession. As it shows, the incentives for ESG integration in investment decision should not only be borne out of ethical concerns, but of the lasting impacts for investment performance and viability [73]. One key argument for the consideration of ESG factors, or the concept of ESG investing, is the realization of inherent externalities associated with the investment that is usually not fully captured in the traditional financial analysis in which focus tends to be on short-term results and earnings, e.g., wealth destruction at BP caused by the oil spill in the Gulf of Mexico [74]. Therefore, ESG investing provides an avenue to measure such risks and opportunities as spillover from firms’ activities that would otherwise result in un- or mis-pricing of the investment.

The tremendous growth of signatories with the United Nations-backed Principles for Responsible Investment (UNPRI) witnesses the official recognition of the importance of ESG issues [75]. While PRI is not regulatory nor overly prescriptive in nature, the broader proliferation of ESG adoption represents an accelerated momentum toward becoming a norm in investment decisions, with the onboarded investors implementing key ESG principles into their internal operations and policies based on guided principles. Ref. [76] find that 90% of global investors had incorporated ESG information in their investment processes. Furthermore, the increasing investor accountability by society also means that investors could gain legitimacy through making their ESG stance central to their brands [77]. For instance, by rejecting projects with ESG concerns, institutional investors appeal to their stakeholders with their long-term commitment to sustainability and governance principles [78].

Despite the wide acceptance of ESG relevance for firms and investors, its impacts on yield spread remains a difficult issue in academia. A review of the literature on the determinants of conventional yield spread in the context of ESG impacts reveals largely contrasting conclusions [20,79,80]. Still, it requires greater understanding of the impact of ESG as driving mechanism in the Sukuk universe. Of notable relevance to our Sukuk spread study is [44], whose study investigates the unilateral governance metric and its impacts on the yield spreads. Their finding points to the mixed evidence of the significance of institutional ownerships and board of director characteristics, i.e., the proxy for governance measure, in association with the corporate yield spreads. Thus, by focusing on each individual dimension of the ESG metrics and a composite measure, we posit our first hypothesis as follows:

H1. 

There is a negative relationship between firms’ ESG performance and Sukuk yield spread (and vis-à-vis conventional bonds).

3.3. The Moderating Effect of Investment Horizon on the Relationship Between ESG Activities and Yield Spread

The investment horizon forms a crucial factor in investment decision-making. Due to different investors’ demand patterns, individual investors display tendencies toward different investment horizons [81]. This is also in line with preferred habitat theory. Therefore, the observed yield spreads of conventional bonds and Sukuk could be understood as a culmination of the investment behaviors of individual investors with different time horizons. With ESG investing rising as one of the dominant investment themes, the yield spread study should reveal the investor dynamic with regard to the investment horizon. Prior studies identify a significant link between the investment horizon and the selection of strategy themes, although these subjects are merely confined to equity and mutual funds with large conflicting outcomes [82,83]. Ref. [84] show that the investor’s choice of value strategy over growth strategy tends to increase as the investment horizon increases, the results of which are confounded by a different outcome in [85]. In a study of asset allocation between stocks and conventional bonds, ref. [86] concludes that investors find stocks to be more appealing (less risky) than conventional bonds in the longer horizon due to the mean reverting property.

Eventually, the yield spread variation reflects the effects of the interaction between ESG impact and investment horizon. Aligned with preferred habitat theory, we posit that the ESG impacts on the Sukuk yield spread would be inconsistent and incongruent throughout the yield curve due to investment horizons of various investor groups. This study holds the view that regardless of the strategies being pursued by investment managers, i.e., duration matching, holds to maturity, yield curve trading, etc., the yield curve reflects the byproducts of interactions of investors and practitioners along the spectrum of maturities and yields, for both Sukuk and conventional bonds. Therefore, the impacts of ESG factors that run diagonally to investors’ decisions shall be measured along the yield curve.

Although the conceptual link is well established between ESG activities and the investment horizon, the empirical finding on this front remains scarce. Therefore, this study extends the existing literature by offering insights into the interplay effect of the ESG activities and the investment horizon, primarily on the Sukuk yield spread. Thus, premised on the fact that firm’s commitment to ESG tends to be value-accretive in the long run, which also coincides with the preferred habitat of long-term investors, we posit our second hypothesis:

H2. 

The effects of firms’ ESG performance is more pronounced in the longer investment horizons for Sukuk (and vis-à-vis conventional bonds).

4. Research Design

4.1. Data and Sample Construction

The sample begins with all non-financial firms from the countries with prominent dual financial systems that are aligned with the objective of Sukuk study. The country constituents of the study comprise Saudi Arabia, UAE, Turkey, Malaysia, and Indonesia.

Table 1. Total observations by instrument and country.

Panel A: Instrument type
Security			Count
Conventional Bonds			348
Sukuk			396
Total			744
Panel B: Sukuk and Conventional bonds per country
Country	Bond	Sukuk	Count
Malaysia	100	247	347
Indonesia	216	101	317
Saudi Arabia	24	0	24
UAE	16	0	16
Turkey	40	0	40
Total	396	348	744

reports the number of observations based on instrument type and country. The final sample consists of 744 bond-year unbalanced observations, representing 204 tranches of Sukuk and conventional bond issuances and covering the period of 2008–2022. Both active and matured securities are maintained in the sample to avoid any survivorship bias.

The ESG scores used in this study are sourced from the LSEG database, which aggregates firm-level metrics across environmental, social, and governance dimensions. Under the LSEG methodology, each pillar is assigned a predetermined weighting based on industry standards and relevance to sustainability performance, and the composite score incorporates a penalty mechanism for controversies (LSEG data are retrieved from firms’ publicly reported information in annual reports, corporate social responsibility disclosures, and their websites)—thereby reflecting both positive ESG initiatives and potential areas of concern. Although alternative providers such as MSCI or Sustainalytics offer different scoring frameworks with varying data coverage, update frequency, and weighting schemes, we selected LSEG for its comprehensive integration of quantitative and qualitative data. We acknowledge that this choice introduces limitations regarding cross-provider comparability and sensitivity to specific controversies, suggesting that future research could benefit from employing multiple ESG data sources to validate and refine these findings [87].

The sample excludes all financial institutions for two robustness purposes. First, the inclusion of financial institutions would result in distortion of constituent weight across the industry due to the dominating issues of financial-sector conventional bonds and Sukuk. Second, the wide disparity in the corporate model between financial institutions and non-financial firms in terms of risk–return dynamic would mean that the approach to valuing the conventional bonds and Sukuk should be targeted and differentiated [88]. This criterion filters out all observations which are issues from financial institutions.

Next, all nonstandard, or non “pure-vanilla” Sukuk or conventional bonds are excluded. The elimination includes all floating rate paper, index-linked securities, convertibles, hybrids, perpetuals, and securities with embedded options. Then, securities attached with governmental sponsor, corporate guarantor, or credit enhancement are removed from the study, as these observations tend not to reflect the underlying fundamentals of the corporate entity. Given the strict requirement for complete data availability, a further filter is applied to eliminate any registries with missing values across all ESG and other variables after performing cross-check with company’s financial reports.

The data observation is specified in annual form to match the frequency of ESG observations. Where the yield spread data of Sukuk and conventional bonds is available only in daily and monthly intervals, the data will be transformed into the yearly unit by taking an arithmetic mean over a given year.

4.2. Dependent Variable

Yield spread is the key dependent variable of this study. It is defined as the difference between the yield to maturity of a conventional bond or Sukuk and that of a corresponding sovereign bond or Sukuk with similar characteristics (e.g., maturity, type) [89,90]. Also known as credit spread, yield spread serves as a proxy for the cost of debt, reflecting a firm’s default risk (default or credit risks remain a crucial element in asset pricing, closely watched by market practitioners) [28,44,91]. Unlike yield to maturity, yield spread remains relatively stable in the absence of inflationary aspect, which can introduce uncertainty (the uncertain elements may be the source of controversial concerns under Shariah principles) and complicate credit risk measurement. Moreover, the yield spread approach offers a market-based measure of financing costs, in contrast to accounting-based cost-of-debt measures that capture interest expenses imposed by lenders rather than investor-driven risk perceptions. This study employs yield spread data exclusively from the LSEG database.

4.3. Independent Variable

4.3.1. ESG Measure

This study investigates the impacts of firms’ ESG performances on the yield spread. LSEG is the key database for ESG data. LSEG provides a quantitative metric for environmental, social, and governance pillars based on firms’ performance, commitment, and effectiveness across 10 measurable themes, including resource use, emissions, environmental product innovation, workforce, human rights, community, product responsibility, management, shareholders, and CSR strategy. A composite ESG score is also obtained for the sample firms, computed based on the comprehensive evaluation of ESG performances after discounting any ESG controversies, i.e., negative stories gleaned from global media [87]. We employ both dimensional scores and composite ESG measures in this study.

4.3.2. Control Variable

We incorporate three additional vectors of variables in our yield spread model, controlling for firm-specific, issue-specific, and macroeconomic risk factors. These vectors have demonstrated robust links with credit spread or credit risk in the existing literature [18,28,92,93]. All control variables are retrieved from the LSEG and Bloomberg databases.

Firm-specific control variables capture the different firm-related risk factors for yield spread. Firm size is directly associated with the business and financial risks, with larger firm size generally implying greater financial flexibility and funding accessibility, translating into lower credit costs or yield spreads [18,94]. Firm size is measured as the natural logarithm of total assets. Leverage, measured as the ratio of total debt to total equity, is associated with firms’ solvency risks, with higher leverage indicating greater debt accumulation and putting into question its repayment capabilities [94,95]. In the same vein, the interest gearing ratio (the ratio of the firm’s interest expense over its operating income) serves as an indicator of debt-servicing risks. Both leverage and interest gearing are expected to be positively associated with credit spreads [94,95,96]. Return on assets, proxied by the ratio of operating income over total assets, effectively measures a firm’s level of efficiency in allocating resources and generating sufficient return for meeting its financial needs, including debt obligation [97,98]. Lastly, firm liquidity indicates the short-term solvency risks. This study uses the book-value current ratio as the liquidity proxy by taking the current assets over the current liabilities. It is likely that firms with higher return on assets and stronger liquidity positions benefit from lower credit spread as a testament to greater financial flexibilities.

It has been shown that the issue-specific (or bond-specific) characteristics also explain the yield variation across bond issues. Years to maturity of Sukuk or conventional bonds is included in the model, with longer maturity being associated with greater default risks [99,100].

Macroeconomic variables control for influences caused by broader economic condition. Sovereign credit default swap (CDS) measures the sovereign credit risks and is expected to have a positive relationship with corporate credit spreads. We use the 5-year CDS from Bloomberg in this study due to the higher liquidity and market-referencing level of such a variant [100]. In the environment of high uncertainties for sovereign creditworthiness, it is likely that individual firms also encounter rising default probabilities due to risk transference from macroeconomic and sovereign vulnerabilities [101,102].

4.4. Model Specification

The baseline regression model takes the form

Log(Spread_i,t) = ∝_I + β₁ ESG_i,t + β₂ X_i,t + β₃ Y_i,t + β₄ Z_i,t + v_t + ε_i,t

where Log(Spread_i,t) is the natural logarithm of the yield spread for Sukuk i or conventional bond i in year t; ESG represents the performance measure of each individual dimension, i.e., environmental, social, and governance pillars, as well as the composite ESG measure; X, Y, and Z are the vectors of all control variables, namely, firm-specific, issue-specific, and macroeconomic variables respectively; v is the dummy variable accounting for time-fixed effects, while ε is the error term.

All ESG variables are lagged in all models. The lagged variables are crucial to alleviate the potential endogeneity problem due to a bidirectional causality between yield spread and ESG. Lagged ESG variables are commonly adopted in studies of ESG impact on the cost of debt [18,92]. Additionally, firm-specific variables are also specified in lagged value, given the lagged relationship between firms’ data and yield spread. Lagging the ESG and firm-specific variables ensures that the reported ESG and financial data become fully public information at time t, i.e., the yield spread has incorporated and reflected such information.

Meanwhile, issue-specific and macroeconomic variables are the contemporaneous explanatory factors for yield spreads and will take on the synchronous form in the model. For instance, years of maturity for Sukuk and conventional bonds is a standalone factor. Similarly, sovereign credit risks (i.e., sovereign CDS) mainly capture developing events at the macro level with unidirectional impacts on the individual firms.

Lastly, the time-fixed effects are included to control for different economic cycles and monetary policies that result in the changes in interest rate levels by global central banks. To avoid overfitting, other cross-sectional fixed effects are not included. Instead of using issue-level dummies, two different sets of regression are generated for Sukuk and conventional bonds.

5. Results

5.1. Descriptive Statistics

Table 2. Key data and variable descriptions.

(a) Yield Spreads and ESG variables
		All		Sukuk		Conventional Bonds
Variable	Definition	Mean	Std Dev	Mean	Std Dev	Mean	Std Dev
Yield Spread (LN)	Natural logarithm of yield spread	4.92	0.69	4.54	0.65	5.25	0.55
Yield Spread (basis point)	Yield spread of conventional bonds and Sukuk	171.69	121.14	114.73	83.26	221.74	127.06
Environmental score	Environmental pillar measure, ENV	40.62	21.57	43.42	21.53	38.16	21.34
Social score	Social pillar measure, SOC	55.15	18.32	60.23	14.29	50.69	20.22
Governance score	Governance pillar measure, GOV	53.44	19.68	59.19	17.32	48.38	20.26
ESG composite score	ESG composite measure, ESGC	51.53	13.86	55.79	12.36	47.79	14.04
(b) Control variables
		All		Sukuk		Conventional Bonds
Variable	Definition	Mean	Std Dev	Mean	Std Dev	Mean	Std Dev
Firm size (LN)	Natural logarithm of total assets, SIZE	22.73	1.05	22.43	0.69	23.00	1.23
Firm size (USD million	Firm’s total assets (in million)	22,900	76,600	7910	10,200	36,100	103,000
Leverage	Ratio of total debt to total equity, LEVERAGE	1.48	1.90	1.10	0.59	1.81	2.50
Interest gearing	Ratio of interest expenses to operating income, INTGEAR	1.17	7.60	2.32	10.96	0.16	1.06
Return on asset	Ratio of operating income to total assets, ROA	0.07	0.08	0.04	0.03	0.09	0.10
Firm liquidity	Current ratio (current assets to current liabilities), CR	1.36	0.82	1.40	0.87	1.32	0.78
Years to maturity	Conventional bonds’ and Sukuk’s maturity, MATURITY	6.92	4.53	6.59	3.58	7.21	5.21
Country CDS	Credit default swap of country, CDS	90.64	74.70	69.72	36.28	109.02	92.81

The sample consists of 744 bond-year observations over the period 2008 to 2022.

presents the summary statistics for the primary and control variables in panels (a) and (b), respectively. On average, Sukuk yield spreads are tighter, with a mean value of 114 basis points, compared to 221 basis points for conventional bonds, and they also exhibit lower variability, as evidenced by their reduced standard deviation. This result suggests, at face value, a “better” credit quality for Sukuk issuers. In terms of ESG measures, Sukuk-issuing firms generally outperform their conventional bond counterparts across all metrics. Among the three ESG pillars, the social performance is the highest, averaging 60.23% for Sukuk issuers, followed by governance at 59.19%, and environmental performance at 43.42%. A similar performance pattern is observed for conventional bonds. The aggregated ESG scores are 55.79% for Sukuk and 47.79% for conventional bonds, which may be skewed downward by the comparatively lower environmental ratings. These findings align with expectations, as Sukuk-issuing firms are subject to Shariah-compliant requirements that often emphasize social responsibilities. Regarding control variables, it is noteworthy that while the combined sample shows an average firm size of USD 22.9 billion, the average size of Sukuk-issuing firms is notably smaller at approximately USD 7.9 billion—roughly one-fifth of the size of conventional bond issuers.

Table 3. Pearson correlations between ESG and control variables.

Panel A: Correlation matrix for Sukuk
	ENV	SOC	GOV	ESGC	SIZE	LEVERAGE	INTGEAR	ROA	CR	MATURITY	CDS
ENV	1
SOC	0.3789	1
GOV	0.3095	0.3297	1
ESGC	0.7267	0.8017	0.665	1
SIZE	−0.0242	0.0374	−0.3823	−0.2416	1
LEVERAGE	−0.4671	0.0471	−0.4074	−0.2376	0.085	1
INTGEAR	0.3835	0.3821	0.3666	0.5139	−0.1313	−0.1786	1
ROA	−0.1901	−0.4097	−0.0752	−0.3236	−0.0231	−0.0186	−0.2273	1
CR	0.3164	−0.1748	0.0449	0.0027	−0.0804	−0.5961	−0.0092	0.0876	1
MATURITY	−0.1574	−0.0992	−0.2965	−0.3226	0.6107	0.027	−0.2095	0.0569	−0.0715	1
CDS	−0.32	−0.2414	0.2217	−0.1746	−0.0856	0.1043	−0.123	0.1576	−0.1263	0.1142	1
Panel B: Correlation matrix for conventional bonds
	ENV	SOC	GOV	ESGC	SIZE	LEVERAGE	INTGEAR	ROA	CR	MATURITY	CDS
ENV	1
SOC	0.0417	1
GOV	0.1519	0.4521	1
ESGC	0.4656	0.8263	0.7042	1
SIZE	0.3714	−0.4051	0.0725	−0.1222	1
LEVERAGE	−0.0098	0.2224	−0.1781	0.0885	−0.2701	1
INTGEAR	0.2153	−0.0219	0.0551	0.095	0.0434	−0.0152	1
ROA	0.1662	−0.3783	0.0411	−0.1606	0.644	−0.4907	0.0746	1
CR	0.3905	−0.4593	−0.2256	−0.265	0.2953	−0.3144	0.1681	0.2313	1
MATURITY	0.1191	−0.156	0.1629	0.0025	0.4597	−0.2342	−0.0172	0.3895	0.121	1
CDS	0.1862	0.1447	0.1304	0.1908	−0.1751	−0.019	0.0684	0.1019	0.0777	−0.0351	1

The sample consists of 744 bond-year observations over the period 2008 to 2022.

presents the Pearson’s correlation coefficients among the study’s key variables. None of the pairwise correlations between ESG and control variables exceeds 0.80, indicating that multicollinearity is not a concern (variance inflation factors (VIFs) were computed, and the results confirmed that multicollinearity is not a concern) [103].

5.2. Empirical Results

The analysis employs a panel data model estimated via a fixed effects estimator with robust standard errors clustered at the issue level, thereby accounting for unobserved heterogeneity, autocorrelation, and potential cross-sectional correlation between the Sukuk and conventional bond groups. Two separate regression series are generated—one for Sukuk and another for conventional bonds. The primary test results are presented in

Table 4. Fixed effect regressions on ESG performance–yield spread: Sukuk and conventional bond.

	Sukuk Yield Spread					Conventional Bond Yield Spread
Independent Variables	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)
Environmental pillar score		0.001					−0.001
		(0.002)					(0.001)
Social pillar score			−0.006 ***					−0.004 ***
			(0.002)					(0.001)
Governance pillar score				−0.003 *					−0.001
				(0.002)					(0.001)
ESG combined score					−0.003					−0.005 ***
					(0.002)					(0.002)
Firm size (LN)	−0.260 ***	−0.255 ***	−0.260 ***	−0.285 ***	−0.276 ***	−0.094 **	−0.091 **	−0.066 *	−0.094 **	−0.078 **
	(0.0442)	(0.045)	(0.044)	(0.046)	(0.046)	(0.037)	(0.038)	(0.038)	(0.037)	(0.037)
Leverage	−0.135 ***	−0.135 **	−0.130 **	−0.181 ***	−0.140 ***	0.017 **	0.017 **	0.016 *	0.016 *	0.014
	(0.0520)	(0.052)	(0.051)	(0.057)	(0.052)	(0.008)	(0.008)	(0.008)	(0.008)	(0.008)
Interest gearing	0.0107 ***	0.010 ***	0.013 ***	0.012 ***	0.012 ***	−0.022	−0.020	−0.020	−0.020	−0.015
	(0.00215)	(0.002)	(0.002)	(0.002)	(0.002)	(0.021)	(0.021)	(0.021)	(0.021)	(0.021)
Return on assets	−0.221	−0.136	−1.121	−0.443	−0.573	0.998 ***	0.988 ***	0.916 **	0.912 **	0.839 **
	(0.721)	(0.740)	(0.773)	(0.727)	(0.774)	(0.366)	(0.367)	(0.363)	(0.378)	(0.366)
Firm liquidity	0.132 ***	0.135 ***	0.111 ***	0.108 ***	0.118 ***	0.160 ***	0.163 ***	0.118 ***	0.151 ***	0.131 ***
	(0.0327)	(0.033)	(0.033)	(0.035)	(0.035)	(0.027)	(0.028)	(0.030)	(0.029)	(0.028)
Maturity	−0.00633	−0.006	−0.006	−0.009	−0.007	−0.011 **	−0.010 **	−0.011 **	−0.010 **	−0.009 **
	(0.00786)	(0.008)	(0.008)	(0.008)	(0.008)	(0.005)	(0.005)	(0.005)	(0.005)	(0.005)
CDS	−0.00169	−0.001	−0.007	−0.003	−0.004	0.000	0.000	0.001	0.000	0.001
	(0.0134)	(0.014)	(0.013)	(0.013)	(0.014)	(0.000)	(0.000)	(0.000)	(0.000)	(0.000)
Constant	10.48 ***	10.277 ***	11.212 ***	11.424 ***	11.195 ***	7.165 ***	7.111 ***	6.702 ***	7.217 ***	6.998 ***
	(1.340)	(1.398)	(1.346)	(1.420)	(1.457)	(0.840)	(0.850)	(0.845)	(0.842)	(0.833)
Observations	348	348	348	348	348	396	396	396	396	396
R-squared	0.678	0.678	0.687	0.682	0.680	0.581	0.581	0.591	0.582	0.591
Time-effect	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Hausman prob	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000

This table reports the baseline regressions using the Fixed-effect model. The dependent variables are the Sukuk and bond yield spreads. In all models, the dependent variables are the Sukuk and bond yield spreads, and the independent variable is firm ESG. More comprehensive definitions of the variables can be found on the Table 2. Numbers in brackets are the t-statistics based on the robust standard errors. Year and country fixed effects are controlled in all models. Robust standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.

, with columns 1–5 for Sukuk and columns 6–10 for conventional bonds. In each series, the baseline model—including only the control variables—is reported in columns 1 and 6. The second specification, shown in columns 2 and 7, incorporates the environmental pillar as the first dimensional measure. Subsequent specifications (columns 3–5 for Sukuk and columns 8–10 for conventional bonds) sequentially add individual sustainability measures as well as the composite ESG score. All fixed effects regressions further include time-specific effects to capture period-specific influences.

Overall, the primary findings from the estimations of both Sukuk and conventional bonds reveal notable differences in their relationships with key variables, indicating that sustainability factors are significant determinants of yield spreads. Moreover, the results show that while some effects of firm ESG performance are parallel between Sukuk and conventional bonds, other impacts diverge between the two segments.

In particular, the analysis consistently demonstrates that firms’ social performance exerts a statistically significant negative effect on yield spreads for both asset classes, with significance at the 1% level. For instance, in models (3) and (8), the coefficients for the social pillar score are −0.006 for Sukuk and −0.004 for conventional bonds, respectively. This implies that a one-unit increase in the social score is associated with a decrease in yield spreads by 0.006 basis points for Sukuk and 0.004 basis points for conventional bonds. These robust findings support the hypothesis that higher social performance is linked to lower yield spreads, offering valuable empirical insights into the role of social factors in green finance.

This negative association can be interpreted through a risk management lens: firms with strong social performance tend to exhibit lower volatility in asset values and reduced exposure to negative or reputational events, which, in turn, minimizes default or credit risk. In contrast, firms that fail to meet social responsibilities—exposed through incidents such as product boycotts, employee strikes, punitive damages, and litigation—face increased costs of debt, as adverse events negatively impact their credit ratings and widen yield spreads. For example, following the Gulf of Mexico oil spill, BP’s bonds traded at spreads over 30 basis points higher, effectively reclassifying them into the junk grade category. These findings underscore the importance of social performance as a critical component of ESG, with significant implications for yield spreads and overall funding costs.

Unlike the social pillar, the firm governance score exhibits a significant inverse relationship with Sukuk yield spreads only. As indicated in model (4), a one-unit increase in the governance score is associated with a reduction in Sukuk yield spreads by 0.003 basis points, significant at the 10% level. In contrast, model (9) reveals that the governance variable does not have a statistically significant effect on conventional bond spreads. Although this result for conventional bonds contradicts the study’s hypothesis, the weak explanatory power of the governance coefficient is not entirely unexpected. More generally, Sukuk issuances inherently adhere to higher governance standards—characteristics that are highly valued by their investors. Conventional bond investors, on the other hand, typically represent a more heterogeneous group, for whom governance metrics may be less critical. These contrasting results underscore the distinct nature of Islamic financial instruments relative to conventional bonds and highlight the differential role of governance in shaping investor perceptions across these markets. Consistent with this perspective, [18] found an insignificant relationship between governance and the cost of debt. These findings underscore the need for further research to unravel the detailed mechanisms through which ESG factors affect financial outcomes.

Meanwhile, neither Sukuk nor conventional bonds exhibit a significant relationship between firms’ environmental scores and yield spreads. This may suggest that investors assess environmental performance within a broader institutional context rather than solely through firm-level practices, as supported by institutional theory [104]. Alternatively, the result may reflect greenwashing, where superficial sustainability efforts undermine investor confidence in the authenticity of environmental claims—a phenomenon documented by previous research [71,79]. Consequently, widespread skepticism regarding environmental performance may explain the absence of a clear link between environmental scores and yield spreads.

Lastly, the combined ESG measure (ESGC) shows a significant impact on conventional bond spreads, while no association is observed with Sukuk spreads. This diveregence may stem from offsetting effects among the individual ESG dimensions in the Sukuk market. Overall, the study’s findings indicate that the impact of firm ESG performance on yield spreads for conventional bonds is largely consistent with that for Sukuk, albeit with some nuances. The results highlight the significant influence of ESG activities, as evidenced by the interplay of individual ESG dimensions, and support the hypothesis that ESG performance is a pertinent determinant for both Sukuk and conventional bond yield spreads. Moreover, these outcomes align with prior research [10,18,47,92] that documents a negative relationship between sustainability factors and various aspects of corporate performance, underscoring both the transformative potential of sustainable practices and the complexities they introduce into business performance and investment management.

The impact of control variables on yield spreads varies between Sukuk and conventional bonds. In the Sukuk market, all firm-specific variables—namely, firm size (SIZE), leverage (LEVERAGE), interest gearing (INTGEAR), and firm liquidity (CR)—exert a statistically significant influence on yield spreads at the 1% level, except for return on assets (ROA). In contrast, for conventional bonds, ROA is significant at the 1% level, while interest gearing is not.

Interestingly, the coefficient on LEVERAGE is negative in the Sukuk models, in contrast to the positive effect observed for conventional bonds. This result can be understood through the lens of growth deepening and operational scaling unique to Islamic finance. While conventional finance typically interprets higher leverage as a marker of elevated financial risk—leading to wider yield spreads—Sukuk adhere to Shariah principles emphasizing risk-sharing and ethical practices. As a result, increased leverage among Sukuk issuers may signal efficient debt utilization that supports expansion and the attainment of scale economies, particularly for smaller, emerging firms operating below their optimal scale [105]. For example, our sample indicates that Sukuk issuers have an average firm size of approximately USD 7.9 billion, compared to USD 36.1 billion for conventional firms, with mean gearing ratios of 1.10x versus 1.81x, respectively, indicating that Sukuk issuers are considerably smaller. In this context, higher leverage among Sukuk-issuing firms can be interpreted by investors as a positive signal of strategic growth and improved operational efficiency, thereby reducing the perceived risk premium and leading to narrower yield spreads compared to conventional bonds. Similarly to our findings, ref. [28] found a significant negative relationship between firm leverage and Sukuk yield spreads.

Another unexpected finding is the significant positive relationship between firm liquidity and yield spreads. One plausible explanation is that a high liquidity ratio may indicate inefficient resource use, such as cash hoarding due to a lack of profitable investment opportunities or poor working capital management. Investors may view this inefficiency as a sign of operational weakness or strategic inflexibility, thereby increasing the perceived risk and demanding a higher risk premium, which results in wider yield spreads. This explanation is consistent with prior research by [92], which also documented a positive link between liquidity measures and credit spreads.

Meanwhile, ROA does not significantly affect yield spreads in Sukuk models, whereas in conventional bond models, higher ROA is significantly associated with increased yield spreads. This may be because higher ROA in conventional bonds signals increased risk-taking or earnings volatility, as aggressive strategies can elevate default risk. Additionally, if high ROA reflects unsustainable practices or earnings management, investors may demand a higher risk premium, resulting in wider spreads.

Bond maturity (MATURITY) exhibits a significant negative association with conventional bond yield spreads only. Longer maturities tend to attract long-term investors, reducing sensitivity to short-term fluctuations and lowering the risk premium, while also mitigating refinancing risk through extended repayment horizons.

Macro-level indicators such as credit default swap (CDS) spreads do not significantly affect the yield spreads for either Sukuk or conventional bonds. This finding reinforces the notion that both markets remain predominantly domestic—with limited foreign investor participation—and that the relative movement of corporate yields against sovereign benchmarks is largely driven by micro or firm-level factors.

Overall, the adjusted R² values consistently hover around 68% for Sukuk and 58% for conventional bonds, whether analyzing individual ESG dimensions or aggregate metrics.

From an investor’s perspective, holding ESG-performing assets reduces the costs of debt, thereby failing to reject the hypothesis, H1.

5.3. Robusness Tests

Additionally, a series of robustness tests are employed by deploying a battery of empirical techniques, including the one-step system GMM (GMM), random effects model (RE), and the pooled OLS (POLS) approach.

Table 5. Baseline regression results.

	Sukuk Yield Spread				Conventional Bond Yield Spread
Independent Variables	FE (1)	GMM (2)	RE (3)	POLS (4)	FE (5)	GMM (6)	RE (7)	POLS (8)
Environmental pillar score	0.001	0.000	0.000	−0.009 ***	−0.001	−0.011	0.001	−0.003 **
	(0.002)	(0.002)	(0.002)	(0.002)	(0.001)	(0.013)	(0.001)	(0.001)
Social pillar score	−0.006 ***	−0.006 *	−0.003 *	−0.006 **	−0.004 ***	−0.005 ***	−0.002	−0.004 ***
	(0.002)	(0.004)	(0.002)	(0.003)	(0.001)	(0.001)	(0.002)	(0.001)
Governance pillar score	−0.003 *	−0.012 **	−0.003 **	−0.006 **	−0.001	−0.000	0.001	−0.000
	(0.002)	(0.005)	(0.001)	(0.003)	(0.001)	(0.001)	(0.001)	(0.001)
ESG combined score	−0.003	−0.002	−0.003	−0.011 ***	−0.005 ***	−0.003 **	−0.001	−0.007 ***
	(0.002)	(0.003)	(0.002)	(0.004)	(0.002)	(0.002)	(0.002)	(0.002)

This table reports the results for the relationship between firm ESG and yield spreads for Sukuk and conventional bonds. In all models, the dependent variables are the Sukuk and bond yield spreads, and the independent variable is firm ESG. More comprehensive definitions of the variables can be found in Table 2. Year and country fixed effects are controlled in models (1), (3), (5), and (7). Numbers in brackets are the t-statistics based on the robust standard errors. Robust standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.

presents the results of the baseline regression analysis, which consistently shows a robust negative association between specific individual ESG dimensions and yield spreads across the models.

The full results of system GMM are presented in

Table 6. System GMM regressions on ESG performance–yield spread: Sukuk and conventional bond.

	Sukuk Yield Spread					Conventional Bond Yield Spread
Independent Variables	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)
Lag yield spread (LN)	0.970 ***	0.951 ***	0.977 ***	1.246 ***	0.853 ***	0.789 ***	1.370 ***	1.307 ***	0.794 ***	0.792 ***
	(0.221)	(0.179)	(0.241)	(0.242)	(0.139)	(0.168)	(0.467)	(0.347)	(0.178)	(0.161)
Environmental pillar score		0.000					−0.011
		(0.002)					(0.013)
Social pillar score			−0.006 *					−0.005 ***
			(0.004)					(0.001)
Governance pillar score				−0.012 **					−0.000
				(0.005)					(0.001)
ESG combined score					−0.002					−0.003 **
					(0.003)					(0.002)
Firm size (LN)	−0.111	−0.139	−0.181	−0.016	−0.145 *	0.115 **	0.634	0.132	0.118 **	0.112 **
	(0.287)	(0.261)	(0.156)	(0.132)	(0.083)	(0.051)	(0.867)	(0.105)	(0.059)	(0.049)
Leverage	0.158 **	0.166 **	0.212	0.022	0.103	−0.011	−0.091	−0.099	−0.011	−0.010
	(0.076)	(0.075)	(0.194)	(0.312)	(0.072)	(0.012)	(0.106)	(0.078)	(0.012)	(0.012)
Interest gearing	0.012 ***	0.012 ***	0.011 ***	0.018 ***	0.012 ***	0.038 **	0.463	0.266	0.039 **	0.044 ***
	(0.002)	(0.001)	(0.003)	(0.003)	(0.001)	(0.015)	(0.429)	(0.280)	(0.017)	(0.015)
Return on assets	−5.097 **	−5.097 **	−6.405 ***	−3.972 *	−3.488 ***	−4.307 ***	−7.799	−4.653 **	−4.347 ***	−4.306 ***
	(2.112)	(2.105)	(1.962)	(2.175)	(0.938)	(0.957)	(5.359)	(1.958)	(1.038)	(0.903)
Firm liquidity	0.071	0.066	0.028	0.098	0.016	−0.047	−0.298	−0.243 *	−0.049	−0.051 *
	(0.069)	(0.064)	(0.160)	(0.231)	(0.047)	(0.030)	(0.231)	(0.144)	(0.031)	(0.027)
Maturity	0.021	0.023	0.032 *	0.011	0.014 *	0.007	−0.017	0.011	0.007	0.007
	(0.026)	(0.028)	(0.016)	(0.018)	(0.009)	(0.007)	(0.071)	(0.010)	(0.007)	(0.007)
CDS	−0.001	−0.001	−0.005	−0.001	−0.000	0.001 ***	0.003	0.001	0.001 ***	0.001 ***
	(0.001)	(0.001)	(0.003)	(0.001)	(0.001)	(0.000)	(0.003)	(0.001)	(0.000)	(0.000)
Constant	2.438	3.120	4.615	−0.130	3.929	−1.344	−15.256	−0.743	−1.415	−1.137
	(7.176)	(6.369)	(4.662)	(4.199)	(2.412)	(1.639)	(18.534)	(1.676)	(1.844)	(1.568)
Observations	243	243	243	243	243	297	297	297	297	297
AR1 test prob	0.001	0.001	0.000	0.000	0.000	0.002	0.044	0.001	0.002	0.001
Hansen test prob	0.359	0.359	0.349	0.343	0.616	0.211	0.528	0.194	0.229	0.203
No. of group	84	84	84	84	84	77	77	77	77	77
No. of instrument	19	19	19	19	19	17	17	17	17	17

This table presents the results for one-step System GMM based on the relationship between firm ESG and yield spreads for Sukuk and conventional bonds. In all models, the dependent variables are the Sukuk and bond yield spreads, and the independent variable is firm ESG. More comprehensive definitions of the variables can be found on the Table 2. Numbers in brackets are the t-statistics based on the robust standard errors. Robust standard errors in parentheses *** p < 0.01, ** p < 0.05, * p < 0.1.

. The dynamic model indicates a significant negative relationship between Sukuk yield spreads and both social and governance measures, with significance observed at the 10% and 5% levels, respectively. For conventional bonds, social and aggregate ESG measures exhibit a significant negative association with yield spreads, with significance at the 1% and 5% levels, respectively. The confirmation provided by the System GMM approach is critical, as it addresses potential endogeneity from omitted variables and controls for unobserved heterogeneity, thereby enhancing the reliability of our analysis.

Other than system GMM, further tests are implemented through random effects model and pooled regression. The full results for these alternative specifications are presented in

Table 7. Random effect regressions on ESG performance–yield spread: Sukuk and conventional bond.

	Sukuk Yield Spread					Conventional Bond Yield Spread
Independent Variables	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)
Environmental pillar score		0.000					0.001
		(0.002)					(0.001)
Social pillar score			−0.003 *					−0.002
			(0.002)					(0.002)
Governance pillar score				−0.003 **					0.001
				(0.001)					(0.001)
ESG combined score					−0.003					−0.001
					(0.002)					(0.002)
Firm size (LN)	−0.184 ***	−0.186 ***	−0.177 ***	−0.216 ***	−0.193 ***	−0.218 ***	−0.226 ***	−0.225 ***	−0.221 ***	−0.217 ***
	(0.070)	(0.070)	(0.066)	(0.069)	(0.068)	(0.028)	(0.029)	(0.028)	(0.028)	(0.028)
Leverage	−0.331 ***	−0.323 ***	−0.328 ***	−0.339 ***	−0.331 ***	−0.037	−0.036	−0.035	−0.037	−0.041
	(0.088)	(0.090)	(0.083)	(0.085)	(0.087)	(0.043)	(0.044)	(0.043)	(0.046)	(0.044)
Interest gearing	0.006 ***	0.006 ***	0.007 ***	0.007 ***	0.007 ***	−0.021	−0.024	−0.020	−0.024	−0.022
	(0.001)	(0.001)	(0.001)	(0.001)	(0.002)	(0.014)	(0.015)	(0.015)	(0.015)	(0.015)
Return on assets	−0.301	−0.234	−0.573	−0.366	−0.420	0.636 ***	0.690 ***	0.622 ***	0.742 ***	0.658 ***
	(0.618)	(0.656)	(0.600)	(0.608)	(0.600)	(0.198)	(0.203)	(0.203)	(0.252)	(0.237)
Firm liquidity	−0.03	−0.022	−0.034	−0.043	−0.031	0.042	0.051	0.028	0.060	0.049
	(0.050)	(0.050)	(0.048)	(0.047)	(0.048)	(0.042)	(0.043)	(0.040)	(0.041)	(0.040)
Maturity	−0.02	−0.019	−0.022 *	−0.021 *	−0.022 *	−0.009	−0.009	−0.009	−0.010	−0.009
	(0.013)	(0.012)	(0.012)	(0.013)	(0.012)	(0.012)	(0.012)	(0.012)	(0.012)	(0.012)
CDS	0.033 ***	0.033 ***	0.032 ***	0.031 ***	0.032 ***	0.001 ***	0.001 ***	0.001 ***	0.001 ***	0.001 ***
	(0.005)	(0.005)	(0.005)	(0.005)	(0.005)	(0.000)	(0.000)	(0.000)	(0.000)	(0.000)
Constant	0	0.000	3.446 *	4.448 **	0.000	11.108 ***	11.245 ***	11.309 ***	11.096 ***	11.073 ***
	(0)	(0.000)	(1.852)	(1.916)	(0.000)	(0.639)	(0.674)	(0.632)	(0.640)	(0.632)
Observations	348	348	348	348	348	396	396	396	396	396
R-squared	0.6469	0.6505	0.6546	0.6559	0.6505	0.3307	0.333	0.3503	0.3435	0.3509
Time-specific effect	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes

This table reports the regression results using the random-effect model. The dependent variables are the Sukuk and bond yield spreads. In all models, the dependent variables are the Sukuk and bond yield spreads, and the independent variable is firm ESG. More comprehensive definitions of the variables can be found on the Table 2. Numbers in brackets are the t-statistics based on the robust standard errors. Year and country fixed effects are controlled in all models. Robust standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.

and

Table 8. Pooled OLS regressions on ESG performance–yield spread: Sukuk and conventional bond.

	Sukuk Yield Spread					Conventional Bond Yield Spread
Independent Variables	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)
Environmental pillar score		−0.009 ***					−0.003 **
		(0.002)					(0.001)
Social pillar score			−0.006 **					−0.004 ***
			(0.003)					(0.001)
Governance pillar score				−0.006 **					−0.000
				(0.003)					(0.001)
ESG combined score					−0.011 ***					−0.007 ***
					(0.004)					(0.002)
Firm size (LN)	−0.483 ***	−0.456 ***	−0.471 ***	−0.515 ***	−0.499 ***	−0.218 ***	−0.190 ***	−0.225 ***	−0.216 ***	−0.208 ***
	(0.050)	(0.047)	(0.049)	(0.048)	(0.048)	(0.022)	(0.025)	(0.022)	(0.022)	(0.021)
Leverage	0.245 ***	0.126 **	0.231 ***	0.146 **	0.174 ***	−0.039	−0.030	−0.043	−0.041	−0.047
	(0.050)	(0.060)	(0.050)	(0.068)	(0.056)	(0.032)	(0.032)	(0.033)	(0.034)	(0.032)
Interest gearing	0.008 ***	0.013 ***	0.010 ***	0.010 ***	0.012 ***	−0.030 *	−0.020	−0.025	−0.029 *	−0.017
	(0.001)	(0.001)	(0.001)	(0.002)	(0.002)	(0.016)	(0.016)	(0.016)	(0.017)	(0.016)
Return on assets	0.784	0.111	−0.005	0.638	−0.084	1.698 ***	1.577 ***	1.476 ***	1.678 ***	1.440 ***
	(0.844)	(0.726)	(0.758)	(0.810)	(0.746)	(0.328)	(0.326)	(0.335)	(0.333)	(0.334)
Firm liquidity	−0.057	−0.036	−0.091 *	−0.093 *	−0.096 **	0.095 **	0.123 ***	0.048	0.091 ***	0.053
	(0.050)	(0.052)	(0.047)	(0.048)	(0.048)	(0.037)	(0.041)	(0.035)	(0.035)	(0.035)
Maturity	−0.015	−0.022 **	−0.017	−0.019 *	−0.022 **	−0.016 ***	−0.016 ***	−0.015 ***	−0.015 ***	−0.014 ***
	(0.010)	(0.010)	(0.010)	(0.011)	(0.010)	(0.005)	(0.005)	(0.005)	(0.005)	(0.005)
CDS	0.002 **	0.001	0.001 *	0.002 ***	0.001 **	0.002 ***	0.002 ***	0.002 ***	0.002 ***	0.002 ***
	(0.001)	(0.001)	(0.001)	(0.001)	(0.001)	(0.000)	(0.000)	(0.000)	(0.000)	(0.000)
Constant	15.13 ***	15.158 ***	15.375 ***	16.343 ***	16.327 ***	9.976 ***	9.391 ***	10.417 ***	9.966 ***	10.111 ***
	(1.129)	(1.071)	(1.067)	(1.129)	(1.122)	(0.501)	(0.557)	(0.497)	(0.497)	(0.469)
Observations	348	348	348	348	348	396	396	396	396	396
R-squared	0.454	0.514	0.468	0.469	0.482	0.360	0.372	0.375	0.361	0.385

This table reports the regressions results using Pooled OLS model. In all models, the dependent variables are the Sukuk and bond yield spreads, and the independent variable is firm ESG. More comprehensive definitions of the variables can be found on the Table 2. Numbers in brackets are the t-statistics based on the robust standard errors. Robust standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.

, respectively. Remarkably, these results are consistent with our study’s overall findings, revealing a statistically substantial negative association of sustainability factors with yield spreads of both segments.

5.4. Yield Curve Impacts: Investment Horizon as Moderator over the Link of ESG–Sukuk Yield Spreads

The study examines further how the relationship between ESG performance and yield spreads varies according to different investment horizons: short-term (less than 3 years), lower medium-term (3–5 years), upper medium-term (5–8 years) and long-term (over 8 years).

Table 9. Yield curve impacts of firms’ ESG activities across Sukuk and conventional bonds.

	Sukuk Yield Spread				Conventional Bond Yield Spread
	Short	Lower Medium	Upper Medium	Long	Short	Lower Medium	Upper Medium	Long
Investment Horizon:	Below 3	3 to 5	5 to 8	over 8	Below 3	3 to 5	5 to 8	over 8
Environmental pillar score	−0.009 *	−0.015 ***	0.008 ***	0.005 *	−0.001	−0.005 **	−0.001	0.004 **
	(0.005)	(0.004)	(0.002)	(0.003)	(0.004)	(0.002)	(0.003)	(0.002)
Social pillar score	−0.001	−0.009 **	0.007 **	−0.001	−0.010 ***	−0.007 ***	0.007 ***	0.014 ***
	(0.007)	(0.004)	(0.003)	(0.003)	(0.003)	(0.002)	(0.002)	(0.002)
Governance pillar score	−0.025 **	−0.002	−0.005 ***	0.006 **	−0.008 ***	−0.006 **	0.004 **	0.007 ***
	(0.009)	(0.003)	(0.002)	(0.003)	(0.003)	(0.002)	(0.002)	(0.002)
ESG combined score	−0.008	−0.001	0.012 ***	0.003	−0.015 ***	−0.015 ***	0.008 ***	0.011 ***
	(0.015)	(0.007)	(0.004)	(0.004)	(0.004)	(0.003)	(0.003)	(0.002)
Firm characteristic	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Bond characteristic	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Macroeconomic variable	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Country-specific effect	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Time-specific effect	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes

This table presents the results based on the moderating impacts of investment horizon on the relationship between firm ESG and Sukuk and bond yield spreads. In all models, the dependent variables are the Sukuk and bond yield spreads, and the independent variable is firm ESG. More comprehensive definitions of the variables can be found on the Table 2. Numbers in brackets are the t-statistics based on the robust standard errors. Year and country fixed effects are controlled in all models. Robust standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.

presents a summary of the regression results. The findings reveal that the investment horizon moderates the ESG–yield spread relationship. Specifically, shorter investment horizons—encompassing both short- and lower medium-term horizons—are associated with a more pronounced reduction in yield spreads for firms with higher ESG performance, a pattern that holds for both Sukuk and conventional bonds, with some nuances. Notably, this outcome aligns with the study’s main findings, with coefficient signs remaining stable across models.

Conversely, longer investment horizons, i.e., upper medium-term and long-term, reveal a diverse impact of ESG factors on yield spreads. The analysis indicates significant positive coefficients for ESG dimensions across the longer-term horizons, except for the governance pillar in the Sukuk panel, which maintains a significant negative effect. This anomaly may be attributed to the unique pricing mechanisms in the Sukuk and conventional bond markets, which are highly sensitive to interest rate fluctuations. Investors adjust their maturity strategies based on their interest rate outlook and yield curve positioning. For instance, the barbell strategy—purchasing short-term bonds while selling long-term bonds—enables investors to benefit from a flattening yield curve amid rising interest rate expectations. Consequently, the inherent sensitivity of long-term bonds to interest rate risks can diminish the positive effects of robust ESG performance, resulting in a less pronounced reduction in long-term yield spreads. This phenomenon is further compounded by periods of heightened interest rate volatility, as witnessed during major policy adjustments by global central banks such as the U.S. Federal Reserve, which implemented 14 rate cuts (2008–2015 and 2019–2020) and 16 rate hikes (2015–2018 and 2022–2023) over the study period.

Another possible explanation may be linked to broader market apprehensions regarding the long-term sustainability and policy direction of companies or entire countries. In many developing regions—still striving to meet the ESG standards established by more developed economies—the ultimate trajectory of sustainable goals remains uncertain. This uncertainty may lead investors to prioritize short-term certainty over long-term progress, thereby driving up long-term yield spreads. Such findings underscore the complex and multifaceted relationship between ESG dimensions and yield spreads across different investment horizons. Given the inconsistent significance observed across the full investment horizon—particularly over the long term—the findings ultimately do not support the H2 hypothesis.

6. Summary and Discussion of Key Findings

Overall, our findings support and validate the premise that firms’ ESG performance exerts a lowering effect on Sukuk yield spreads. Specifically, Sukuk issuers that score highly on ESG metrics—particularly in the social and governance dimensions—are more likely to convince investors of their sustainable practices and align with investor values, as reflected in narrower yield spreads. This suggests that sustainability factors are increasingly integrated into investment decision-making, and robust sustainable efforts can reduce a firm’s yield spread, thereby lowering its funding costs. These results are consistent with prior research, further confirming the influence of sustainability on various components of firms’ cost of debt [10,18,47,92]. The negative association can be attributed to the observation that highly sustainable and socially responsible firms typically exhibit lower volatility in asset values and reduced perceived risk, resulting in a diminished risk premium and narrower yield spreads. Furthermore, firms that engage in practices to positively influence societal perceptions and bolster their legitimacy—through robust sustainable initiatives and transparent disclosures—are better positioned to secure the support and resources necessary to thrive in a market that increasingly values sustainability and accountability [58,106].

It is important to note that each ESG dimension exhibits a distinct relationship with Sukuk yield spreads. Specifically, the social and governance pillars exert a significant downward influence on yield spreads, thereby reducing financing costs in a manner that aligns with our hypothesis. Conversely, the environmental dimension shows no statistically significant relationship. Although this might seem counterintuitive, it highlights the inherent uncertainty in weighing the benefits against the costs of environmental practices. On one hand, poor environmental and resource management can erode stakeholder trust and confidence. On the other hand, even effective environmental management does not guarantee positive stakeholder returns, as the costs of implementation can lead to higher operational expenses and increased perceived risk on the firm’s balance sheet. Moreover, as explained by agency theory [107], if managers prioritize personal objectives over short-term profitability or stakeholder interests, investors may remain skeptical about the long-term benefits of environmental initiatives—especially in contexts where broader environmental policies are still evolving or uncertain.

As a secondary observation, awareness of environmental impacts tends to be less prevalent and develops later in emerging markets compared to other sustainability dimensions. In these regions, social and governance issues—such as poverty, living standards, and effective stakeholder governance—often take precedence as more immediate concerns. This outcome is consistent with previous studies conducted in emerging markets [79,108].

In the conventional bond analysis, the results mirror those observed for Sukuk, indicating that sustainable measures significantly influence yield spreads. However, a closer examination at the individual level reveals certain disparities. While the environmental and social pillars exhibit stable effects across both models, the governance pillar is not statistically significant for conventional bonds. Given Sukuk’s heightened governance emphasis, investor preferences—as underlined by investor taste theory—appear to play a more critical role in driving yield spread variations in the Sukuk market compared to conventional bonds. Furthermore, differences emerge in the control variables: Sukuk yield spreads tend to be more sensitive to firm behavioral characteristics related to debt management, such as leverage, interest gearing, and firm size, whereas conventional bond yield spreads are more strongly influenced by factors associated with resource efficiency—namely, return on assets and firm liquidity—and bond maturity.

An examination of the moderating effect of the investment horizon reveals a multifaceted influence of firms’ ESG practices on yield spreads. Across both Sukuk and conventional bonds, the study finds that ESG measures are positively associated with yield spreads over long-term horizons, while the relationship reverses for short-term horizons, showing a negative association. This divergent pattern illustrates how investors tailor their strategies by selecting segments of the yield curve that best match their expectations regarding interest rate outlook, economic conditions, and risk–return trade-off. Moreover, the heterogeneous impact of the investment horizon reflects the study period’s context of heightened interest rate volatility and underscores the need for further research to capture the effects of critical inflection points arising from rate changes.

By examining the differences between Sukuk and conventional bonds in relation to corporate ESG criteria, several conclusions emerge that contribute to the current literature. First, investors may gain greater confidence when firms’ ESG practices are assessed alongside traditional metrics of financial strength and other specific characteristics. Firms can enhance market perception by strategically emphasizing specific ESG dimensions that reflect their intrinsic value. However, compliance with ESG requirements may sometimes impose costs greater than benefits, thereby raising concerns over potential greenwashing. In such cases, firms might be better served by strengthening their core performance, such as improving profitability and generating higher shareholder returns, rather than relying sole on ESG initiatives.

7. Conclusions

In recent years, firms have been experiencing increased pressure in their approach around sustainability requirements. However, uncertainties abound as to the impact to their business and financial model posed by these requirements, posing challenges not only to firms but market players, including investors and policymakers. We examine how ESG factors affect firm yield spreads in the context of Sukuk and conventional bonds. Mainly, the findings confirm that higher ESG performance—particularly in the social and governance dimensions—correlates with narrower Sukuk yield spreads, using a comprehensive analysis of data comprising 744 bond-year observations. Such results affirm that investors increasingly incorporate sustainability criteria into their decision-making.

Building on our baseline results, we employ an advanced dynamic panel data model to mitigate potential endogeneity issues, complemented by a series of robustness tests to further strengthen our findings. These tests also examine the diverse effects across different investment horizons. Consistently, the robustness analyses corroborate our baseline findings, underscoring the pivotal role of ESG considerations in shaping firms’ yield spreads. These findings not only broaden the scope of sustainable finance literature but also provide critical insights into how ESG integration influences investor decisions within the Sukuk market. This research holds implications for corporate managers, investors, and policymakers. Firms aiming to lower their financing costs can leverage strong ESG credentials—particularly social and governance factors—to signal lower risk and earn favorable pricing in Sukuk and, to some extent, conventional bond markets. Policymakers can bolster these effects by fostering clear, consistent sustainability regulations and disclosure standards, thereby strengthening investor confidence and market liquidity. Similarly, policymakers could collaborate with rating agencies to refine credit assessment frameworks and bolster investor confidence in both Sukuk and conventional bond markets by integrating ESG information. Meanwhile, investors seeking to integrate ESG into their portfolios can employ differentiated strategies across investment horizons. In markets where environmental policies remain in flux, stakeholders should remain vigilant to potential costs of environmental projects and the risk of “greenwashing”. Nonetheless, evidence here suggests that an emphasis on social and governance factors can yield tangible financial benefits.

Overall, this study opens doors for further exploration in this evolving field. Future research could compare developed and emerging markets more systematically to capture the influence of broader regulatory environments and investor awareness. As demonstrated by a previous study [108], the geographical coverage can be a significant driver of ESG premium in the measurement of firms’ cost of debt. It may be beneficial to extend the study through the lens of comparing the developed markets as opposed to the emerging economies undertaken in this study. Only then, a more meaningful comparison and comprehensive conclusion could be drawn for the spectrum of this study.

Additionally, future research efforts that can leverage larger and more comprehensive datasets would be highly beneficial as the Islamic finance and ESG movements continue to grow in prominence. Larger, more granular datasets could also clarify how specific macroeconomic events or policy shifts affect Sukuk yield spreads over time. Additionally, applying advanced econometric models (e.g., real-time data analysis or high-frequency panel techniques) would provide deeper insights into how sudden shocks—such as interest rate hikes by global central banks—shape the interplay between ESG performance and bond pricing. Such approaches would enhance the understanding of both the short- and long-term dynamics underpinning Islamic finance instruments, allowing for more nuanced risk management strategies.

The aforementioned future research objectives underscore the need for a multifaceted methodology to examine Sukuk yield spreads. Integrating behavioral insights with advanced econometric modeling can provide a more comprehensive understanding of yield differentials across varying macroeconomic conditions, regulatory frameworks, and financial environments. Addressing these gaps will not only enrich scholarly debate but also offer valuable guidance to investors and policymakers seeking to optimize the growth of Sukuk markets. Overall, this study contributes to a growing body of literature on ESG and Islamic finance. As ESG considerations continue to rise in prominence, it becomes increasingly critical for firms to align with socially responsible and well-governed practices—not merely as an ethical imperative, but also as a means to secure competitive financing.