Green bond issuance and corporate ESG performance: the perspective of internal attention and external supervision

The study addresses whether and how issuing green bonds (GBI) affects corporate ESG performance in China. Motivated by the rapid growth of green finance and the resource requirements of ESG activities, the authors investigate firm-level outcomes of GBI beyond bond pricing. They posit that GBI can serve as a credible signal of environmental commitment and induce both internal and external pressures that improve ESG outcomes. The paper situates the research within the expansion of China’s green finance system since 2016 and highlights the need to unpack mechanisms—internal attention (executive environmental awareness) and external supervision (media monitoring)—through which GBI could influence ESG. The purpose is to provide evidence on the causal effect of GBI on ESG and the channels, and to inform policy and managerial practice in emerging markets.

The literature links green finance to environmental performance and ESG, but results on green bonds are mixed between a signal perspective (credible commitment improving environmental outcomes) and a greenwashing perspective (opportunistic issuance without substantive change). Drawing on stakeholder theory, the authors argue that ESG performance responds to stakeholder expectations and resource allocation tools like green bonds. They propose H1: GBI positively influences corporate ESG performance. Building on upper echelons theory, they argue that executive environmental awareness (internal attention) shapes strategic choices and ESG investments; legislation and green finance can enhance such awareness, motivating H2: GBI improves ESG through internal attention. From neo-institutional theory, firms seek legitimacy; increased disclosure and third-party verification tied to GBI heighten scrutiny by media and external monitors, reducing greenwashing risk and pressuring improvements, motivating H3: GBI improves ESG through external supervision (media coverage).

Data: A-share firms listed on the Shanghai and Shenzhen exchanges (SSE, SZSE) from 2012–2020. China’s green bond framework began in late 2015, so 2016 marks the post-treatment period. Seventy-one firms issued green bonds during 2016–2020; after exclusions (31 newly listed firms during sample period, 18 first-time issuers in 2019–2020 to ensure adequate pre/post windows, and 7 financial firms), the treatment group contains 15 listed firms. The control group comprises non-financial firms in the six industries where green bonds are concentrated (manufacturing; electric power; water conservancy; construction; mining; wholesale and retail). Firms with special treatment are excluded; continuous variables are winsorized at the 1st and 99th percentiles. Final sample: 830 firms and 6432 firm-year observations. Data sources: Financials from CSMAR; ESG scores from Bloomberg; media coverage from CNRDS. Variables: Independent variable GBI is the interaction GB×Post, where GB=1 for green bond issuers and 0 otherwise; Post=1 in and after the issuance year and 0 before. Dependent variable: LNESG is the natural log of Bloomberg’s overall ESG score; environmental, social, and governance component logs (LNE, LNS, LNG) are also analyzed. Mediators: Internal attention (IA) measured as executive environmental awareness—the frequency of environmental terms in annual reports divided by 100. External supervision (ES) measured by the log number of media topics mentioning the firm annually. Controls include Size (log assets), ROA, leverage (Lev), operating cash flow/TA (Cashflow), CEO-chair duality (Dual), largest shareholder ownership (Top), firm age (log years), state ownership (SOE), and regional Market_Index. Fixed effects for firm, year, and industry are included. Empirical strategy: A staggered difference-in-differences (DID) with firm, year, and industry fixed effects estimates the effect of GBI on LNESG. An event-study specification tests parallel trends using indicators for years relative to issuance (Before5 to After4). Mediation is assessed via two-step models: (1) regressing IA (or ES) on GBI and controls; (2) regressing LNESG on GBI, the mediator, and controls with fixed effects. Robustness: (i) Propensity score matching (1:4 nearest neighbor) followed by DID; (ii) placebo tests with randomized treatment assignment and policy timing (1000 simulations); (iii) industry-adjusted ESG (subtracting industry-year mean); (iv) alternative ESG measure (Huazheng ESG rating mapped to 1–9); (v) alternative fixed effects and clustering at the firm level. Extended analysis: Effects on E, S, G components; heterogeneity by firm size (relative to industry average), government subsidies (high vs low), and executives with environmental experience; firm value effects via Tobin’s Q variants and market-to-book (MB).

- Baseline DID: GBI significantly increases ESG performance. GB×Post coefficient ≈ 0.215 (t≈6.77) with firm, year, and industry fixed effects and full controls, supporting H1. - Parallel trends: Pre-trends coefficients (Before5–Before2) are insignificant; contemporaneous and post-issuance effects (Current, After1–After4) are positive and significant. - Robustness: - PSM-DID: GB×Post = 0.116, p<0.01. - Placebo: Simulated treatment yields null-centered estimates; p-values follow expected distribution, reinforcing causality. - Industry-adjusted ESG: GB×Post = 0.210, p<0.01. - Alternative ESG (Huazheng): GB×Post = 0.443, p<0.01. - Alternative FE/SE: Results remain positive and significant (e.g., 0.267, p<0.01). - Mechanisms (mediation): - Internal attention: GBI increases IA (α1=0.362, p<0.01); IA positively relates to ESG (η1=0.068, p<0.01). Mediation supports H2. - External supervision: GBI increases media coverage ES (α2=0.306, p<0.05); ES positively relates to ESG (η2=0.020, p<0.01). Mediation supports H3. - Heterogeneity: - Firm size: Significant positive effect for large firms; insignificant for small firms. - Government subsidies: Significant positive effect among high-subsidy firms; insignificant among low-subsidy firms. - Executive environmental experience: Significant positive effect when such executives are present; insignificant otherwise. - ESG components: Strongest effect on Environmental (β≈0.417, p<0.01), followed by Social (β≈0.225, p<0.01), then Governance (β≈0.039, p<0.01). - Firm value: Post-issuance associated with higher Tobin’s Q (0.293–0.394, p<0.10) and MB (0.357, p<0.10), indicating improved market valuation.

The findings show that issuing green bonds leads to measurable improvements in firms’ ESG performance, addressing concerns about greenwashing by demonstrating real effects consistent with the signal perspective. By identifying internal attention (executive environmental awareness) and external supervision (media scrutiny) as mechanisms, the study links green financial instruments to organizational behavior through upper echelons and neo-institutional lenses. The stronger environmental component effect aligns with the designated use-of-proceeds and third-party verification embedded in green bonds. Heterogeneous effects suggest that resource capacity, policy incentives, and managerial environmental expertise condition the ESG gains from GBI. The results reinforce the role of targeted green finance in advancing sustainability outcomes and provide policy-relevant evidence from an emerging market context.

Using a staggered DID on 830 Chinese listed firms (2012–2020), the study documents that green bond issuance significantly enhances overall ESG performance and the E, S, and G components, with the largest gains in environmental outcomes. Mediation analyses show that GBI operates through increased internal attention (executive environmental awareness) and heightened external supervision (media coverage). Effects are stronger for larger firms, firms receiving higher government subsidies, and firms with executives having environmental experience. GBI is also associated with improved firm valuation. Policy implications include strengthening green bond market institutions, expanding incentives/subsidies for issuers, and promoting ESG disclosure. Managerial implications stress enhancing environmental governance, recruiting environmentally experienced executives, and improving transparency and green project disclosure. Future research should validate generalizability beyond China and explore additional mechanisms linking GBI to ESG.

- External validity: The sample is limited to Chinese listed firms; results may differ in other emerging or developed markets. - Mechanism scope: Only two channels (internal attention and external supervision) are examined; other mechanisms may contribute. - Data access: Underlying datasets are not publicly available due to confidentiality, which may limit replication beyond author-provided access.