A Study of the Factors Contributing to the Impact of Climate Risks on Corporate Performance in China’s Energy Sector
Abstract
:1. Introduction
2. Literature Review
3. Research Hypotheses
3.1. Climate Risk Perception and Corporate Performance
3.2. Climate Risk Perception, Financial Flexibility, and Corporate Performance
3.3. Climate Risk Perception, R&D Investment, and Corporate Performance
4. Research Methodology
4.1. Sample Selection and Data Sources
4.2. Definition of Variables and Modeling
4.2.1. Definition of Variables
- (1)
- Dependent variable
- (2)
- Independent variable
- (3)
- Control variables
- (4)
- Mediating variables
4.2.2. Descriptive Analysis
4.2.3. Model Specification
5. Empirical Results and Analysis
5.1. Benchmark Regression
5.2. Endogeneity Test
5.3. Robustness Test
5.3.1. Variables’ Replacements
5.3.2. Changing the Sample Cycle
5.4. Mechanism Analysis
5.4.1. Reduced Financial Flexibility
5.4.2. Increased R&D Intensity
5.4.3. Further Investigation
5.5. Moderating Effect Test
5.6. Heterogeneity Test
5.6.1. Heterogeneity Analysis of Ownership Structures
5.6.2. Heterogeneity Analysis of Contamination Levels
5.6.3. Heterogeneity Analysis Across Industries
5.6.4. Heterogeneity Analysis Across Carbon Trading Pilot Regions
6. Conclusions and Policy Suggestions
6.1. Conclusions
6.2. Policy Recommendations
6.3. Limitations and Future Research Directions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- World Meteorological Organization. State of the Global Climate 2024 (WMO-No. 1368); World Meteorological Organization: Geneva, Switzerland, 2025. [Google Scholar]
- Financial Stability Board. Final report: Recommendations of the Task Force on Climate-Related Financial Disclosures. Task Force Clim.-Relat. Financ. Discl. 2017, 2017, 35–39. [Google Scholar]
- Borozan, D.; Pirgaip, B. Climate policy uncertainty and firm-level carbon dioxide emissions: Assessing the impact in the US market. Bus. Strategy Environ. 2024, 33, 5920–5938. [Google Scholar] [CrossRef]
- Burke, M.; Hsiang, S.M.; Miguel, E. Global non-linear effect of temperature on economic production. Nature 2015, 527, 235–239. [Google Scholar] [CrossRef] [PubMed]
- Liu, Z.; Feng, J. Climate shocks and corporate default risk: Evidence from China. Energy 2025, 323, 135786. [Google Scholar] [CrossRef]
- Schaeffer, R.; Szklo, A.S.; de Lucena, A.F.P.; Borba, B.S.M.C.; Nogueira, L.P.P.; Fleming, F.P.; Troccoli, A.; Harrison, M.; Boulahya, M.S. Energy sector vulnerability to climate change: A review. Energy 2012, 38, 1–12. [Google Scholar] [CrossRef]
- Mugerman, Y.; Steinberg, N.; Wiener, Z. The exclamation mark of Cain: Risk salience and mutual fund flows. J. Bank. Financ. 2022, 134, 106332. [Google Scholar] [CrossRef]
- Zhang, X.; Bao, X. Sustainable transformation: The impact of climate risk perception on corporate operational resilience in China. Sustainability 2025, 17, 3387. [Google Scholar] [CrossRef]
- Zhang, Y.; He, M.; Liao, C.; Wang, L. Climate risk exposure and the cross-section of Chinese stock returns. Financ. Res. Lett. 2023, 55, 103987. [Google Scholar] [CrossRef]
- Kruttli, M.S.; Tran, B.R.; Watugala, S.W. Pricing Poseidon: Extreme weather uncertainty and firm return dynamics. J. Financ. 2025, 80, 783–832. [Google Scholar] [CrossRef]
- Addoum, J.M.; Ng, D.T.; Ortiz-Bobea, A. Temperature shocks and industry earnings news. J. Financ. Econ. 2023, 150, 1–45. [Google Scholar] [CrossRef]
- Hong, H.; Li, F.W.; Xu, J. Climate risks and market efficiency. J. Econom. 2019, 208, 265–281. [Google Scholar] [CrossRef]
- Li, X.; Luo, L.; Tang, Q. Climate risk and opportunity exposure and firm value: An international investigation. Bus. Strategy Environ. 2024, 33, 5540–5562. [Google Scholar] [CrossRef]
- Bolton, P.; Kacperczyk, M. Do investors care about carbon risk? J. Financ. Econ. 2021, 142, 517–549. [Google Scholar] [CrossRef]
- Bolton, P.; Kacperczyk, M. Global pricing of carbon-transition risk. J. Financ. 2023, 78, 1015–1050. [Google Scholar] [CrossRef]
- Gennaioli, N.; Shleifer, A.; Vishny, R. Neglected risks: The psychology of financial crises. Am. Econ. Rev. 2015, 105, 310–314. [Google Scholar] [CrossRef]
- Sautner, Z.; Van Lent, L.; Vilkov, G.; Zhang, R.; Zwinkels, R. Firm-level climate change exposure. J. Financ. 2023, 78, 1449–1498. [Google Scholar] [CrossRef]
- Wang, J.; Hu, X.; Zhong, A. Stock market reaction to mandatory ESG disclosure. Financ. Res. Lett. 2023, 53, 103402. [Google Scholar] [CrossRef]
- Chen, M.; Xiao, H.; Zhao, H.; Zhu, H. The power of attention: Government climate-risk attention and agricultural-land carbon emissions. Environ. Res. 2024, 251, 118661. [Google Scholar] [CrossRef]
- Krueger, P.; Sautner, Z.; Starks, L.T. The importance of climate risks for institutional investors. Rev. Financ. Stud. 2020, 33, 1067–1111. [Google Scholar] [CrossRef]
- Alok, S.; Kumar, N.; Wermers, R. Do fund managers misestimate climatic disaster risk? Rev. Financ. Stud. 2020, 33, 1146–1183. [Google Scholar] [CrossRef]
- Kling, G.; Volz, U.; Murinde, V.; Ayas, S. The impact of climate vulnerability on firms’ cost of capital and access to finance. World Dev. 2021, 137, 105131. [Google Scholar] [CrossRef]
- Battiston, S.; Mandel, A.; Monasterolo, I.; Schütze, F.; Visentin, G. A climate stress-test of the financial system. Nat. Clim. Change 2017, 7, 283–288. [Google Scholar] [CrossRef]
- Dell, M.; Jones, B.F.; Olken, B.A. Temperature shocks and economic growth: Evidence from the last half century. Am. Econ. J. Macroecon. 2012, 4, 66–95. [Google Scholar] [CrossRef]
- Kahn, M.E.; Mohaddes, K.; Ng, R.N.C.; Pesaran, M.H.; Raissi, M.; Yang, J.C. Long-term macroeconomic effects of climate change: A cross-country analysis. Energy Econ. 2021, 104, 105624. [Google Scholar] [CrossRef]
- Arian, A.; Naeem, M.A. Climate risk and corporate investment behavior in emerging economies. Emerg. Mark. Rev. 2025, 65, 101257. [Google Scholar] [CrossRef]
- Huang, H.H.; Kerstein, J.; Wang, C.; Wu, F.H. Firm climate risk, risk management, and bank loan financing. Strateg. Manag. J. 2022, 43, 2849–2880. [Google Scholar] [CrossRef]
- Khanra, S.; Dhir, A.; Kaur, P.; Barua, M.K. A resource-based view of green innovation as a strategic firm resource: Present status and future directions. Bus. Strategy Environ. 2022, 31, 1395–1413. [Google Scholar] [CrossRef]
- Serafeim, G. Public sentiment and the price of corporate sustainability. Financ. Anal. J. 2020, 76, 26–46. [Google Scholar] [CrossRef]
- Galbreath, J. Corporate governance practices that address climate change: An exploratory study. Bus. Strategy Environ. 2010, 19, 335–350. [Google Scholar] [CrossRef]
- Yin, L.; Tan, L.; Wu, J.; Gao, D. From risk to sustainable opportunity: Does climate risk perception lead firm ESG performance? J. Int. Financ. Manag. Account. 2025. [Google Scholar] [CrossRef]
- Halme, M.; Niskanen, J. Does corporate environmental protection increase or decrease shareholder value? The case of environmental investments. Bus. Strategy Environ. 2001, 10, 200–214. [Google Scholar] [CrossRef]
- Somanathan, E.; Somanathan, R.; Sudarshan, A.; Tewari, M. The impact of temperature on productivity and labor supply: Evidence from Indian manufacturing. J. Political Econ. 2021, 129, 1797–1827. [Google Scholar] [CrossRef]
- Dietz, S.; Bowen, A.; Dixon, C.; Gradwell, P. ‘Climate value at risk’ of global financial assets. Nat. Clim. Change 2016, 6, 676–679. [Google Scholar] [CrossRef]
- Kikstra, J.S.; Nicholls, Z.R.J.; Smith, C.J.; Riahi, K.; Kriegler, E.; van Vuuren, D.P. The IPCC Sixth Assessment Report WGIII climate assessment of mitigation pathways: From emissions to global temperatures. Geosci. Model Dev. 2022, 15, 9075–9109. [Google Scholar] [CrossRef]
- He, B.; Ma, C. Can the inclusiveness of foreign capital improve corporate environmental, social, and governance (ESG) performance? Evidence from China. Sustainability 2024, 16, 9626. [Google Scholar] [CrossRef]
- Zhou, R.; Lou, J.; He, B. Greening corporate environmental, social, and governance performance: The impact of China’s carbon emissions trading pilot policy on listed companies. Sustainability 2025, 17, 963. [Google Scholar] [CrossRef]
- Semieniuk, G.; Campiglio, E.; Mercure, J.F.; Volz, U.; Edwards, N.R. Low-carbon transition risks for finance. Wiley Interdiscip. Rev. Clim. Change 2021, 12, e678. [Google Scholar] [CrossRef]
- Naseer, M.M.; Guo, Y.; Zhu, X. The dynamics of corporate climate risk and market volatility: International evidence. North Am. J. Econ. Financ. 2025, 67, 102435. [Google Scholar] [CrossRef]
- Rao, S.; Narayan, P.K.; Sharma, S.S. When rain matters! Investments and value relevance. J. Corp. Financ. 2022, 72, 101827. [Google Scholar] [CrossRef]
- Ricci, E.C.; Banterle, A. Do major climate change-related public events have an impact on consumer choices? Renew. Sustain. Energy Rev. 2020, 126, 109793. [Google Scholar] [CrossRef]
- Hsiang, C.C.; Jen, C.H. Firm performance following actual share repurchases: Effects of investment crowding out and financial flexibility. Pac.-Basin Financ. J. 2022, 73, 101738. [Google Scholar] [CrossRef]
- Wang, Y.; Zhang, L.; Liu, J. Unravelling the Missing Link: Climate Risk, ESG Performance and Debt Capital Cost in China. Sustainability 2024, 16, 7137. [Google Scholar] [CrossRef]
- Tenggren, S.; Olsson, O.; Vulturius, G.; Carlsen, H.; Benzie, M. Climate risk in a globalized world: Empirical findings from supply chains in the Swedish manufacturing sector. J. Environ. Plan. Manag. 2020, 63, 1266–1282. [Google Scholar] [CrossRef]
- Zhang, Y.; Chen, X. Does ESG Performance Enhance Financial Flexibility? Evidence from Chinese Listed Companies. Sustainability 2022, 14, 11324. [Google Scholar] [CrossRef]
- Lv, C.; Shao, C.; Lee, C.C. Green technology innovation and financial development: Do environmental regulation and innovation output matter? Energy Econ. 2021, 98, 105237. [Google Scholar] [CrossRef]
- Delistavrou, A.; Tilikidou, I.; Papaioannou, E. Climate change risk perception and intentions to buy consumer packaged goods with chemicals containing recycled CO2. J. Clean. Prod. 2022, 382, 135215. [Google Scholar] [CrossRef]
- Fernando, Y.; Wah, W. The impact of eco-innovation drivers on environmental performance: Empirical results from the green technology sector in Malaysia. Sustain. Prod. Consum. 2017, 12, 27–43. [Google Scholar] [CrossRef]
- Li, Y.; Bosworth, D. R&D spillovers in a supply chain and productivity performance in British firms. J. Technol. Transf. 2020, 45, 177–204. [Google Scholar] [CrossRef]
- Bai, D.; Du, L.; Xu, Y.; Abbas, S. Climate policy uncertainty and corporate green innovation: Evidence from Chinese A-share listed industrial corporations. Energy Econ. 2023, 127, 107020. [Google Scholar] [CrossRef]
- Deng, M.; Fang, X.; Tian, Z.; Luo, W. The impact of environmental uncertainty on corporate innovation: Evidence from Chinese listed companies. Sustainability 2022, 14, 4902. [Google Scholar] [CrossRef]
- Loughran, T.; McDonald, B. Textual analysis in accounting and finance: A survey. J. Account. Res. 2016, 54, 1187–1230. [Google Scholar] [CrossRef]
- Hossain, A.T.; Masum, A.A. Does corporate social responsibility help mitigate firm-level climate change risk? Financ. Res. Lett. 2022, 47, 102791. [Google Scholar] [CrossRef]
- Bagh, T.; Hunjra, A.I.; Ntim, C.G.; Naseer, M.M. Capitalizing on risk: How corporate financial flexibility, investment efficiency, and institutional ownership shape risk-taking dynamics. Int. Rev. Econ. Financ. 2025, 99, 104068. [Google Scholar] [CrossRef]
- Fu, Y. Enterprises’ internationalization, R&D investment and enterprise performance. Financ. Res. Lett. 2024, 67, 105721. [Google Scholar] [CrossRef]
- Rosenbaum, P.R. An exact adaptive test with superior design sensitivity in an observational study of treatments for ovarian cancer. Ann. Appl. Stat. 2012, 6, 83–105. [Google Scholar] [CrossRef]
- Zhang, Z.; Feng, Y.; Zhou, H.; Chen, L.; Liu, Y. The Impact of Climate Policy Uncertainty on the ESG Performance of Enterprises. Systems 2024, 12, 495. [Google Scholar] [CrossRef]
- Naseer, M.M.; Khan, M.A.; Bagh, T.; Guo, Y.; Zhu, X. Firm climate change risk and financial flexibility: Drivers of ESG performance and firm value. Borsa Istanb. Rev. 2024, 24, 106–117. [Google Scholar] [CrossRef]
- Karlilar, S.; Tarzibashi, O.F.F. R&D investment and financial performance in EU countries: The role of shareholder protection and creditor rights in renewable energy firms. Environ. Sci. Pollut. Res. 2023, 30, 124170–124181. [Google Scholar] [CrossRef]
Climate Risk Keywords | |
---|---|
Lexicon | Energy saving, energy, clean, ecology, environment, transformation, solar energy, upgrading, recycling, utilization, nuclear power, wind power, natural gas, efficiency, fuel, efficiency, regeneration, emission reduction, environmental protection, green, low carbon, consumption reduction, fuel, water saving, photovoltaic, high efficiency, retrofit, fuel consumption, power consumption, energy consumption, wind power, photovoltaic, efficiency, intensification, disasters, earthquakes, typhoons, tsunamis, droughts and floods, extremes, harshness, waterlogging, high winds, dust, hurricanes, frost, floods, storms, mudslides, landslides, freezing, snow, droughts, floods, torrential rains, tornadoes, hail, floods, rain, snow, freezing, blizzards, freezing, drought, drought, heavy rains, flooding, severe cold, wind and sand, climate, weather, humidity, water temperatures, cooling, cold, temperature, rainfall, temperature, rainfall, rainy season, rainfall, precipitation, cloudy rain, rainy, extremely cold, winter, flood season, high humidity, water conditions, water level, light, water shortage, alpine, cold, cold wave, subsidence, groundwater, flood conditions, surface, water storage |
Variable Type | Variable Name | Variable Symbol | Definition | Expected Effect |
---|---|---|---|---|
Explained variable | corporate performance | ROE | The ratio of net income to average shareholders’ equity | |
Control variables | firm size | size | Logarithmic value of total enterprise assets | + |
fixed asset ratio | far | The ratio of net fixed assets to total assets | ||
short-term debt reliance | sbd | The ratio of short-term borrowings and current portion of long-term debt to total assets | ||
firm age | age | The natural logarithm of one plus years since listing | +/ | |
growth performance | growth | Percentage change in operating income relative to prior year | + | |
equity separation | top1 | The percentage shareholding of the largest shareholder | + | |
Mediating variables | financial flexibility | ff | The sum of cash flexibility and debt flexibility | + |
R&D investment | rd | The ratio of R&D investment to operating revenue |
VarName | Obs | Mean | SD | Min | Median | Max | sign Test |
---|---|---|---|---|---|---|---|
ROE | 800 | 0.0592 | 0.156 | −3.44 | 0.06 | 0.39 | p = 0.0155 |
ctrp | 800 | 0.5569 | 0.289 | 0.01 | 0.54 | 1.05 | p = 0.0736 |
size | 800 | 24.0287 | 1.508 | 20.47 | 23.86 | 28.64 | p = 0.0073 |
far | 800 | 0.4654 | 0.178 | 0.08 | 0.45 | 0.95 | p = 0.0642 |
sbd | 800 | 0.1150 | 0.081 | 0.00 | 0.10 | 0.45 | p = 0.0000 |
growth | 800 | 0.0752 | 0.177 | −0.31 | 0.05 | 2.79 | p = 0.0000 |
top1 | 800 | 45.5023 | 16.778 | 10.45 | 47.82 | 89.99 | p = 0.0001 |
age | 800 | 3.0348 | 0.267 | 2.20 | 3.09 | 3.40 | p = 0.0000 |
ff | 800 | 0.5728 | 0.217 | 0.09 | 0.56 | 1.50 | p = 0.0000 |
rd | 800 | 0.6375 | 1.004 | 0.00 | 0.13 | 6.31 | p = 0.0000 |
Variables | (1) | (2) | (3) |
---|---|---|---|
ROE | ROE | ROE | |
ctrp | −0.038 * | −0.129 *** | −0.104 ** |
(−1.893) | (−2.807) | (−2.103) | |
size | 0.007 * | 0.027 | 0.038 * |
(1.787) | (1.604) | (1.774) | |
far | 0.044 | 0.229 *** | 0.219 *** |
(1.391) | (3.153) | (3.006) | |
sbd | −0.365 *** | −0.381 *** | −0.393 *** |
(−5.325) | (−3.610) | (−3.651) | |
age | −0.031 | 0.000 | 0.000 |
(−1.530) | (.) | (.) | |
growth | 0.072 ** | 0.060 * | 0.058 * |
(2.307) | (1.880) | (1.757) | |
top1 | 0.000 | −0.000 | −0.000 |
(1.111) | (−0.003) | (−0.188) | |
_cons | −0.003 | −0.590 | −0.827 * |
(−0.025) | (−1.489) | (−1.676) | |
Year FE | NO | NO | YES |
Firm FE | NO | YES | YES |
N | 800 | 800 | 800 |
R2 | 0.063 | 0.041 | 0.055 |
Variables | (1) | (2) | (3) | (4) |
---|---|---|---|---|
First-Stage Regression | Second-Stage Regression | First-Stage Regression | Second-Stage Regression | |
ctrp | −0.379 * | −1.286 * | ||
(−1.892) | (−1.682) | |||
IV1 | 0.754 *** | |||
(6.917) | ||||
IV2 | −0.006 ** | |||
(−2.428) | ||||
controls | YES | YES | YES | YES |
_cons | −1.543 *** | −1.175 ** | −1.254 *** | −3.050 ** |
(−4.243) | (−2.096) | (−2.716) | (−2.306) | |
Year FE | YES | YES | YES | YES |
Firm FE | YES | YES | YES | YES |
N | 800 | 800 | 621 | 621 |
R2 | 0.408 | 0.352 |
Variables | Replacement Variable | Replacement Variable | ||||
---|---|---|---|---|---|---|
(1) | (2) | (3) | (4) | (5) | (6) | |
ROAs | ROAs | ROAs | EVA | EVA | EVA | |
ctrp | −0.009 * | −0.022 ** | −0.027 ** | −0.007 | −0.038 ** | −0.037 ** |
(−1.825) | (−2.092) | (−2.322) | (−1.016) | (−2.380) | (−2.193) | |
controls | YES | YES | YES | YES | YES | YES |
_cons | 0.033 | −0.085 | 0.015 | −0.043 | −0.234 * | −0.214 |
(1.167) | (−0.928) | (0.133) | (−1.043) | (−1.714) | (−1.260) | |
Year FE | NO | NO | YES | NO | NO | YES |
Firm FE | NO | YES | YES | NO | YES | YES |
N | 800 | 800 | 800 | 800 | 800 | 800 |
R2 | 0.124 | 0.045 | 0.055 | 0.104 | 0.050 | 0.063 |
Variables | (1) | (2) | (3) |
---|---|---|---|
ROE | ROE | ROE | |
ctrp | −0.009 | −0.056 ** | −0.059 ** |
(−0.713) | (−2.028) | (−1.993) | |
controls | YES | YES | YES |
_cons | −0.080 | −0.154 | −0.077 |
(−1.159) | (−0.677) | (−0.273) | |
Year FE | NO | NO | YES |
Firm FE | NO | YES | YES |
N | 560 | 560 | 560 |
R2 | 0.110 | 0.064 | 0.074 |
Variables | (1) | (2) | (3) |
---|---|---|---|
ff | ff | ROE | |
ctrp | −0.116 *** | −0.075 ** | |
(−3.352) | (−2.399) | ||
ff | Positive # | ||
controls | NO | YES | |
_cons | 0.599 *** | 3.221 *** | |
(32.144) | (10.251) | ||
Year FE | YES | YES | |
Firm FE | YES | YES | |
N | 800 | 800 | |
R2 | 0.027 | 0.234 |
Variables | (1) | (2) | (3) |
---|---|---|---|
rd | rd | ROE | |
ctrp | 0.709 *** | 0.649 *** | |
(3.719) | (3.337) | ||
rd | Negative # | ||
controls | NO | YES | |
_cons | 0.057 | −0.594 | |
(0.550) | (−0.305) | ||
Year FE | YES | YES | |
Firm FE | YES | YES | |
N | 800 | 800 | |
R2 | 0.252 | 0.262 |
Variables | (1) |
---|---|
ROE | |
crtp | −0.164 *** |
(−2.685) | |
mgmt | −2.234 *** |
(−4.555) | |
crtp × mgmt | 1.778 ** |
(2.047) | |
controls | YES |
_cons | −0.739 |
(−1.520) | |
N | 800 |
R2 | 0.089 |
Explained Variables | ROE | ROE | rd | rd |
---|---|---|---|---|
Sample | (1) | (2) | (3) | (4) |
SOEs | NSOEs | SOEs | NSOEs | |
ctrp | −0.113 ** | 0.028 | 0.627 ** | 0.625 |
(−2.118) | (0.260) | (3.058) | (1.154) | |
controls | YES | YES | YES | YES |
_cons | −0.892 | 0.159 | −0.665 | 2.838 |
(−1.548) | (0.225) | (−0.300) | (0.786) | |
Year FE | YES | YES | YES | YES |
Firm FE | YES | YES | YES | YES |
N | 724 | 76 | 724 | 76 |
R2 | 0.058 | 0.298 | 0.282 | 0.350 |
Variables | (1) | (2) |
---|---|---|
Non-Heavily Polluting Enterprises | Heavily Polluting Enterprises | |
crtp | 0.036 | −0.131 ** |
(0.454) | (−2.392) | |
controls | YES | YES |
Year FE | YES | YES |
Firm FE | YES | YES |
_cons | 0.905 | −0.956 * |
(0.540) | (−1.832) | |
N | 65 | 735 |
R2 | 0.408 | 0.060 |
Variables | (1) | (2) | (3) | (4) | (5) |
---|---|---|---|---|---|
Electric Power, Steam and Hot Water Production and Supply | Coal Mining and Dressing | Petroleum Processing, Coking, and Nuclear Fuel Processing Industries | Gas Production and Supply | Petroleum and Natural Gas Extraction | |
ctrp | −0.060 | −0.102 ** | −0.703 ** | 0.036 | −0.599 * |
(−0.822) | (−2.433) | (−2.346) | (0.454) | (−1.994) | |
controls | YES | YES | YES | YES | YES |
_cons | −1.031 | −0.740 | −0.988 | 0.905 | −11.548 |
(−1.425) | (−1.103) | (−0.938) | (0.540) | (−1.700) | |
Year FE | YES | YES | YES | YES | YES |
Firm FE | YES | YES | YES | YES | YES |
N | 455 | 168 | 82 | 65 | 30 |
R2 | 0.124 | 0.718 | 0.409 | 0.408 | 0.775 |
Variables | (1) | (2) |
---|---|---|
Treat = 0 | Treat = 1 | |
ROE | ROE | |
crtp | −0.119 *** | −0.084 |
(−2.658) | (−0.860) | |
controls | YES | YES |
_cons | −0.778 * | −1.693 |
(−1.785) | (−1.358) | |
N | 448 | 352 |
R2 | 0.113 | 0.105 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Song, Y.; Lu, L.; Liu, J.; Zhou, J.; Wang, X.; Li, F. A Study of the Factors Contributing to the Impact of Climate Risks on Corporate Performance in China’s Energy Sector. Sustainability 2025, 17, 5139. https://doi.org/10.3390/su17115139
Song Y, Lu L, Liu J, Zhou J, Wang X, Li F. A Study of the Factors Contributing to the Impact of Climate Risks on Corporate Performance in China’s Energy Sector. Sustainability. 2025; 17(11):5139. https://doi.org/10.3390/su17115139
Chicago/Turabian StyleSong, Yuping, Lu Lu, Jingxuan Liu, Jingyi Zhou, Xin Wang, and Fangfang Li. 2025. "A Study of the Factors Contributing to the Impact of Climate Risks on Corporate Performance in China’s Energy Sector" Sustainability 17, no. 11: 5139. https://doi.org/10.3390/su17115139
APA StyleSong, Y., Lu, L., Liu, J., Zhou, J., Wang, X., & Li, F. (2025). A Study of the Factors Contributing to the Impact of Climate Risks on Corporate Performance in China’s Energy Sector. Sustainability, 17(11), 5139. https://doi.org/10.3390/su17115139