气候波动公共事业企业财务绩的效影响研究——基于双向固定效应模型的实证分析

Research on the Impact of Climate Fluctuations on the Financial Performance of Public Utility Enterprises—Empirical Analysis Based on the Bidirectional Fixed Effects Model

摘要: 在全球气候系统日益不稳定、异常天气事件频发的宏观背景下，中国作为典型的季风气候国家，正面临极端天气事件频发带来的严峻挑战。公共事业企业肩负着保障居民生活与维护社会稳定发展的重要责任，其经营稳定性极易受外部环境变化干扰，尤其是气候波动对其财务绩效构成了潜在威胁。本文基于收集的600组具有代表性的公共事业企业样本所构成的数据，通过计量经济学模型，实证检验并深入分析降水量异常与气温波动这两类关键气候变量对企业核心财务绩效指标——资产回报率(ROA)所产生的具体影响。研究发现：1) 降水异常对ROA有显著正向影响，结果稳健；2) 气候冲击仅影响当期绩效，无滞后效应；3) 影响存在异质性——西部地区降水量影响显著，东中部不显著；水务行业受降水影响(系数0.017)，电力行业受气温影响(系数0.019)，燃气行业则不敏感。4) 数字化转型显著强化了降水量对ROA的正向调节效应(交互项系数0.001，p < 0.05)，表明数字化能力是放大气候资源红利的关键赋能条件，但气温与数字化的交互项不显著。据此建议企业构建气候–财务联动预警机制，政府应加快推动气象数据与公共事业企业互联互通，建设统一的气候风险数据共享平台，并完善公共事业企业气候风险信息披露标准。

Abstract: Against the macroeconomic backdrop of an increasingly unstable global climate system and a rising frequency of anomalous weather events, China—as a typical monsoon-climate country—is facing severe challenges posed by the frequent occurrence of extreme weather events. Public utility enterprises bear the critical mission of safeguarding people’s livelihoods and maintaining social stability; consequently, their operational stability is highly susceptible to disturbances from changes in the external environment, particularly as climate fluctuations pose a potential threat to their financial performance. Based on data derived from 600 representative samples of public utility enterprises, this paper employs econometric models to empirically test and conduct an in-depth analysis of the specific impacts of two key climatic variables—precipitation anomalies and temperature fluctuations—on the core financial performance indicators of these enterprises: the Return on Assets (ROA). The study finds that: 1) Precipitation anomalies have a significant positive impact on ROA, and these results are robust; 2) Climate shocks only affect current-period performance and exhibit no lagged effects; 3) These impacts exhibit heterogeneity—precipitation levels have a significant effect in western regions but not in eastern or central regions; the water utilities sector is affected by precipitation (coefficient: 0.017), the power sector is affected by temperature (coefficient: 0.019), while the gas sector shows no sensitivity. 4) Digital transformation positively moderates the precipitation-ROA relationship (interaction coefficient 0.001, p < 0.05), indicating that digital capability amplifies climate dividends. Accordingly, the study recommends that enterprises establish a climate-finance linkage early-warning mechanism; the government should accelerate the interconnection of meteorological data with public utility enterprises, build a unified climate risk data-sharing platform, and refine the disclosure standards for climate risks among public utility enterprises.