Analysis of the Financing Structure of China’s Listed New Energy Companies under the Goal of Peak CO2 Emissions and Carbon Neutrality
Abstract
:1. Introduction
2. Related Literature Review
3. Methodology and Data
3.1. Subsection Panel Vector Autoregression
3.2. Data Descriptions
4. Empirical Analysis and Discussions
4.1. SYS-GMM PVAR
4.2. Orthogonal Impulse Response Function
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- World Meteorological Organization. The State of the Global Climate 2020; World Meteorological Organization: Geneva, Switzerland, 2020. [Google Scholar]
- BP. BP Statistical Review of World Energy (2020 Edition); BP: London, UK, 2020. [Google Scholar]
- Dogan, E.; Seker, F. The influence of real output, renewable and non-renewable energy, trade and financial development on carbon emissions in the top renewable energy countries. Renew. Sustain. Energy Rev. 2016, 60, 1074–1085. [Google Scholar] [CrossRef]
- UNEP. Global Trends in Renewable Energy Investment 2020; Frankfurt School—UNEP: Frankfurt, Germany, 2020. [Google Scholar]
- Gupta, D.; Das, A.; Garg, A. Financial support vis-à-vis share of wind generation: Is there an inflection point? Energy 2019, 181, 1064–1074. [Google Scholar] [CrossRef]
- Doh, S.; Kim, B. Government support for SME innovations in the regional industries: The case of government financial support program in South Korea. Res. Policy 2014, 43, 1557–1569. [Google Scholar] [CrossRef]
- Wu, X.Y.; Chen, Y.; Li, X.L.; Li, Z.K. R&D investment, government subsidies and corporate value of strategic emerging industries. Sci. Res. Manag. 2017, 038, 30–34. [Google Scholar]
- Zhu, Z.; Zhu, Z.; Xu, P.; Xue, D. Exploring the impact of government subsidy and R&D investment on financial competitiveness of China’s new energy listed companies: An empirical study. Energy Rep. 2019, 5, 919–925. [Google Scholar]
- Garrido, L.; Gomez, J.; Baeza, M.D.L.; Vassallo, J.M. Is EU financial support enhancing the economic performance of PPP projects? An empirical analysis on the case of spanish road infrastructure. Transp. Policy 2017, 56, 19–28. [Google Scholar] [CrossRef] [Green Version]
- Kaldellis, J. Critical evaluation of financial supporting schemes for wind-based projects: Case study Greece. Energy Policy 2011, 39, 2490–2500. [Google Scholar] [CrossRef]
- Guo, F.; Zou, B.; Zhang, X.; Bo, Q.; Li, K. Financial slack and firm performance of SMMEs in China: Moderating effects of government subsidies and market-supporting institutions. Int. J. Prod. Econ. 2019, 223, 107530. [Google Scholar] [CrossRef]
- Lee, E.; Walker, M.; Zeng, C. Do Chinese government subsidies affect firm value? Account. Organ. Soc. 2014, 39, 149–169. [Google Scholar] [CrossRef]
- Shao, X.F.; Zhong, Y.F.; Li, Y.M.; Altuntaş, M. Does environmental and renewable energy R&D help to achieve carbon neutrality target? A case of the US economy. J. Environ. Manag. 2021, 296, 113229. [Google Scholar]
- Cheng, G.; Zhao, C.J.; Iqbal, N.; Gülmez, Ö.; Işik, H.; Kirikkaleli, D. Does energy productivity and public-private investment in energy achieve carbon neutrality target of China? J. Environ. Manag. 2021, 298, 113464. [Google Scholar] [CrossRef]
- Xu, B.; Costa-Climent, R.; Wang, Y.; Xiao, Y. Financial support for micro and small enterprises: Economic benefit or social responsibility? J. Bus. Res. 2020, 115, 266–271, in press. [Google Scholar] [CrossRef]
- Zhang, J.Q.; Liu, Y. Impact of SEO behavior of A-share listed companies on value creation. J. Manag. Sci. China 2010, 13, 47–54. [Google Scholar]
- Cole, R.A.; Sokolyk, T. Debt financing, survival, and growth of start-up firms. J. Corp. Financ. 2018, 50, 609–625. [Google Scholar] [CrossRef]
- Davydov, D. Debt structure and corporate performance in emerging markets. Res. Int. Bus. Financ. 2016, 38, 299–311. [Google Scholar] [CrossRef]
- Campello, M. Debt financing: Does it boost or hurt firm performance in product markets? J. Financ. Econ. 2006, 82, 135–172. [Google Scholar] [CrossRef]
- Chu, Y.C.; Liu, J.P. A Study on the Impact of Debt Financing on Business Performance in Manufacturing. J. Quant. Tech. Econ. 2009, 9, 80–92. [Google Scholar]
- Zhang, Y.L.; Gong, Q.; Rong, Z. Technological innovation, equity financing & transformation of financial structure. Manag. World 2016, 11, 65–80. [Google Scholar]
- Sims, C.A. Macroeconomics and Reality. Econometrica 1980, 48. [Google Scholar] [CrossRef] [Green Version]
- Holtz-Eakin, D.; Newey, W.; Rosen, H.S. Estimating Vector Autoregressions with Panel Data. Econometrica 1988, 56, 1371. [Google Scholar] [CrossRef]
- Sigmund, M.; Ferstl, R. Panel vector autoregression in R with the package panelvar. Q. Rev. Econ. Financ. 2019, 80, 693–720. [Google Scholar] [CrossRef]
- Roodman, D. How to do xtabond2: An Introduction to Dierence and System GMM in Stata. Stata J. 2009, 9, 86–136. [Google Scholar] [CrossRef] [Green Version]
- Alahdal, W.; Alsamhi, M.H.; Tabash, M.I.; Farhan, N.H. The impact of corporate governance on financial performance of Indian and GCC listed firms: An empirical investigation. Res. Int. Bus. Financ. 2019, 51, 101083. [Google Scholar] [CrossRef]
- Tzouvanas, P.; Kizys, P.E.; Chatziantoniou, L.; Sagitova, R. Environmental and Financial Performance in the European Manufacturing Sector: An Analysis of Extreme Tail Dependency. Br. Account. Rev. 2019, 52, 100863. [Google Scholar] [CrossRef]
- Fan, L.; Pan, S.; Liu, G.; Zhou, P. Does energy efficiency affect financial performance? Evidence from Chinese energy-intensive firms. J. Clean. Prod. 2017, 151, 53–59. [Google Scholar] [CrossRef]
- Lewandowski, S. Corporate Carbon and Financial Performance: The Role of Emission Reductions. Bus. Strategy Environ. 2017, 26, 1196–1211. [Google Scholar] [CrossRef]
- Li, L.; Liu, Q.; Tang, D. Carbon Performance, Carbon Information Disclosure Quality and Cost of Equity Financing. Manag. Revew 2019, 31, 223–237. [Google Scholar]
Name | Symbol | Definition | Mean | St. Dev | Min | Max |
---|---|---|---|---|---|---|
Debt financing ratio | DFR | (short-term loans + long-term loans + bonds payable)/total assets | 0.2423 | 0.1628 | 0.0021 | 0.7570 |
Equity financing ratio | EFR | (paid-in capital + capital surplus)/total assets | 0.3370 | 0.1801 | 0.0695 | 1.2416 |
Return on Equity | ROE | Net income/average equity | 0.0556 | 0.1496 | −1.4822 | 0.4659 |
Return on Invested Capital | ROIC | Net operating profit after tax/invested capital | 0.0518 | 0.0782 | −0.4380 | 0.3192 |
Earning per share | EPS | Earings available for common shares/weighted average commom shares outstanding | 0.2958 | 0.5317 | −2.3694 | 2.9900 |
Operating income growth rate | OIGR | Increase in operating income/Total operating income in the last year | 0.1677 | 0.3500 | −0.6872 | 1.7969 |
Patent authorizations | Patent | Number of patent grants | 219.9313 | 428.4737 | 0 | 3258 |
Financial leverage | Leverage | Total liabilities/total assets | 0.5459 | 0.1517 | 0.0516 | 0.9523 |
Variables | ADF Test | PP Test |
---|---|---|
DFR | −5.7929 (0.01) | −70.534 (0.01) |
EFR | −4.9941 (0.01) | −79.528 (0.01) |
ROE | −5.6834 (0.01) | −198.09 (0.01) |
ROIC | −5.0659 (0.01) | −213.25 (0.01) |
EPS | −3.7515 (0.01) | −173.76 (0.01) |
OIGR | −6.5174 (0.01) | −288.05 (0.01) |
Patent | −2.1360 (0.05) | −34.934 (0.01) |
Leverage | −5.3615 (0.01) | −85.289 (0.01) |
Lag | BIC | AIC | HQIC | |
---|---|---|---|---|
Model 1 | 1 | −8454.74 | −3128.735 | −5557.16 |
2 | −5784.791 | −2137.741 | −3790.375 | |
3 | −5199.41 | −1977.747 | −3446.684 | |
Model 2 | 1 | −8521.351 | −3195.346 | −5623.77 |
2 | −5780.36 | −2133.31 | −3785.943 | |
3 | −5196.902 | −1975.239 | −3444.176 |
Variable | Eigenvalue | Modulus | |
---|---|---|---|
Model 1 | 1 | 1.011415 × 10−2 + 0i | 1.011415 × 10−2 |
2 | 4.512784 × 10−3 + 0i | 4.512784 × 10−3 | |
3 | 1.784088 × 10−4 + 2.230238 × 10−4i | 2.856034 × 10−4 | |
4 | 1.784088 × 10−4 − 2.230238 × 10−4i | 2.856034 × 10−4 | |
5 | 7.648161 × 10−6 + 0i | 7.648161 × 10−6 | |
Model 2 | 1 | 4.242394 × 10−2 + 0i | 4.242394 × 10−2 |
2 | 1.725966 × 10−3 + 0i | 1.725966 × 10−3 | |
3 | −1.112492 × 10−5 + 7.885312 × 10−4i | 7.886097 × 10−4 | |
4 | −1.112492 × 10−5 − 7.88531 2 × 10−4i | 7.886097 × 10−4 | |
5 | 2.346436 × 10−5 + 0i | 2.346436 × 10−5 |
Dependent Variables | |||||
---|---|---|---|---|---|
Model 1: Debt financing system | |||||
Independent variables | DFR | ROE | ROIC | EPS | OIGR |
lag1_DFR | 0.0172 *** | 0.0125 * | 0.0013 *** | 0.0083 ** | −0.0161 *** |
(0.0047) | (0.0055) | (0.0004) | (0.0027) | (0.0045) | |
lag1_ROE | 0.0021 *** | 0.0015 * | 0.0002 *** | 0.0011 ** | −0.0015 *** |
(0.0006) | (0.0007) | (0.0000) | (0.0004) | (0.0004) | |
lag1_ROIC | 0.0024 *** | 0.0017 * | 0.0002 *** | 0.0012 ** | −0.0019 *** |
(0.0007) | (0.0008) | (0.0001) | (0.0004) | (0.0005) | |
lag1_EPS | 0.0103 *** | 0.0076 * | 0.0010 *** | 0.0060 ** | −0.0069 *** |
(0.0028) | (0.0033) | (0.0003) | (0.0020) | (0.0020) | |
lag1_OIGR | 0.0134 *** | 0.0089 * | 0.0010 *** | 0.0072 ** | −0.0099 *** |
(0.0037) | (0.0039) | (0.0003) | (0.0024) | (0.0028) | |
lag2_DFR | 0.0174 *** | 0.0126 * | 0.0013 *** | 0.0081 ** | −0.0159 *** |
(0.0047) | (0.0055) | (0.0004) | (0.0027) | (0.0045) | |
Lag3_DFR | 0.0174 *** | 0.0126 * | 0.0013 *** | 0.0082 ** | −0.0156 *** |
(0.0047) | (0.0055) | (0.0004) | (0.0027) | (0.0044) | |
patent | 0.0001 * | 0.0000 | 0.0001 *** | 0.0004 *** | 0.0002 *** |
(0.0000) | (0.0000) | (0.0000) | (0.0001) | (0.0001) | |
leverage | 0.0356 *** | 0.0260 * | 0.0027 *** | 0.0167 ** | −0.0328 *** |
(0.0097) | (0.0113) | (0.0008) | (0.0055) | (0.0093) | |
const | 0.0636 *** | 0.0462 * | 0.0049 *** | 0.0299 ** | −0.0572 *** |
(0.0174) | (0.0201) | (0.0014) | (0.0100) | (0.0162) | |
Model 2: Equity financing system | |||||
Independent variables | EFR | ROE | ROIC | EPS | OIGR |
lag1_ EFR | 0.0398 *** | 0.0355 *** | −0.0061 *** | −0.0039 *** | 0.0026 *** |
(0.0032) | (0.0029) | (0.0005) | (0.0003) | (0.0002) | |
lag1_ROE | 0.0038 *** | 0.0034 *** | −0.0006 *** | −0.0010 *** | 0.0009 *** |
(0.0003) | (0.0003) | (0.0000) | (0.0001) | (0.0001) | |
lag1_ROIC | 0.0043 *** | 0.0039 *** | −0.0007 *** | −0.0008 *** | 0.0002 *** |
(0.0003) | (0.0003) | (0.0001) | (0.0001) | (0.0000) | |
lag1_EPS | 0.0185 *** | 0.0165 *** | −0.0029 *** | −0.0042 *** | 0.0021 *** |
(0.0015) | (0.0013) | (0.0002) | (0.0003) | (0.0002) | |
lag1_OIGR | 0.0233 *** | 0.0197 *** | −0.0035 *** | −0.0041 *** | 0.0023 *** |
(0.0019) | (0.0016) | (0.0003) | (0.0003) | (0.0002) | |
lag2_EFR | 0.0402 *** | 0.0355 *** | −0.0064 *** | −0.0040 *** | 0.0013 *** |
(0.0032) | (0.0029) | (0.0005) | (0.0003) | (0.0001) | |
Lag3_EFR | 0.0405 *** | 0.0364 *** | −0.0062 *** | −0.0039 *** | 0.0021 *** |
(0.0033) | (0.0029) | (0.0005) | (0.0003) | (0.0002) | |
patent | 0.0001 *** | −0.0001 *** | 0.0001 *** | 0.0007 *** | 0.0001 ** |
(0.0000) | (0.0000) | (0.0000) | (0.0001) | (0.0000) | |
leverage | 0.0636 *** | 0.0572 *** | −0.0096 *** | −0.0055 *** | 0.0028 *** |
(0.0051) | (0.0046) | (0.0008) | (0.0004) | (0.0002) | |
const | 0.1136 *** | 0.1016 *** | −0.0175 *** | −0.0103 *** | 0.0062 *** |
(0.0091) | (0.0082) | (0.0014) | (0.0008) | (0.0005) |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2021 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
Li, F.; Di, H. Analysis of the Financing Structure of China’s Listed New Energy Companies under the Goal of Peak CO2 Emissions and Carbon Neutrality. Energies 2021, 14, 5636. https://doi.org/10.3390/en14185636
Li F, Di H. Analysis of the Financing Structure of China’s Listed New Energy Companies under the Goal of Peak CO2 Emissions and Carbon Neutrality. Energies. 2021; 14(18):5636. https://doi.org/10.3390/en14185636
Chicago/Turabian StyleLi, Fuyou, and Hao Di. 2021. "Analysis of the Financing Structure of China’s Listed New Energy Companies under the Goal of Peak CO2 Emissions and Carbon Neutrality" Energies 14, no. 18: 5636. https://doi.org/10.3390/en14185636