| Literature DB >> 34800272 |
Linyun Zhang1, Feiming Huang1, Lu Lu2, Xinwen Ni3, Sajid Iqbal4.
Abstract
The aim of study is to estimate the role of energy financing for energy retrofit in COVID-19, with the intervening role of green bond financing. For this, Kalman technique is applied to infer the empirical findings. It is found that energy financing is significantly dependent on green bonds, and green bonds have a significant role in energy retrofit in E-7 economies specifically. It is further found that E-7 economies gained significant rise in energy efficiency financing green bonds financing, that has supportively extended energy retrofit - before and during COVID-19 crises. It is further found significant that the E-7 nations have to put alot of money into hydro and nuclear energy for energy retrofit, with low carbon emissions. In the light of COVID-19 crises, this study offers policy recommendations for effective energy management. However, such policy recommendations are expected to finely serve the financial intermediaries and national governments of E-7 economies to better optimize energy financing through green bond financing. The novelty of the study exists in topical framework and research directions, talking about the way forwards for energy efficiency financing - which is one of the latest issue of the recent times. Hence, this research provides some empirical verifications about energy financing in COVID-19 crises for energy retrofit, and shares some suggestions for stakeholders.Entities:
Keywords: Energy dependence; Energy efficiency; Energy transition; Green financing; Renewable energy
Mesh:
Substances:
Year: 2021 PMID: 34800272 PMCID: PMC8605453 DOI: 10.1007/s11356-021-17440-3
Source DB: PubMed Journal: Environ Sci Pollut Res Int ISSN: 0944-1344 Impact factor: 5.190
Descriptive statistics of energy redevelopment indictors
| Indicators | Mean | SD | Skewness | Variance |
|---|---|---|---|---|
| Energy storage system | − 0.00111 | 0.002643 | 0.009326 | 0.007341 |
| Energy frequency sensitivity mode | 0.000461 | 0.000518 | − 0.01203 | − 0.00242 |
| Energy supply fault ride through | − 0.00053 | 0.006871 | − 0.00869 | − 0.00046 |
| Fixed speed induction | 0.001554 | 0.000325 | 0.007323 | 0.009575 |
| High voltage ride through | 0.002429 | 0.003045 | − 0.00701 | − 0.00257 |
| Fully converted wind generator supply | − 0.00969 | 0.001737 | − 0.0021 | 0.002627 |
| Internet of things | − 0.0054 | − 0.00141 | − 0.00563 | 0.002266 |
| Photovoltaic | − 0.00352 | − 0.00418 | − 0.00397 | − 0.01935 |
| Low voltage through in thermal plants | 0.002684 | − 0.00087 | 0.010965 | 0.002643 |
| Point of common coupling | 0.005824 | − 0.00174 | − 0.01254 | 0.006516 |
| Rate of change of frequency | − 0.00058 | 0.001065 | − 0.00088 | 0.002241 |
| Transmission system score | − 0.0049 | − 0.00835 | 0.003816 | − 0.00298 |
| Rooter rated speed | − 0.00091 | − 0.00344 | − 0.00272 | 0.002967 |
| Nominal wind energy power | 0.002233 | − 0.00499 | − 0.00822 | 0.006324 |
| Real wind energy power | 0.005306 | − 0.01139 | − 0.01178 | − 0.00251 |
| Power system base | 0.004392 | − 0.0007 | − 0.00328 | − 0.01374 |
| Power generation kilowatts | − 0.00145 | − 0.00103 | 0.012416 | 0.009458 |
| Power generation Megawatts | − 0.00736 | − 0.00293 | − 0.00568 | − 0.00769 |
| Power generation in millisecond | 0.002476 | − 0.00324 | 0.003119 | − 0.02284 |
Kalman measure indicators
| Indicators | Coefficient | SE | Prob | |
|---|---|---|---|---|
| β1 | 0.7268 | 0.1719 | 0.0217 | 0.0175 |
| Β2 | 0.0415 | 0.4123 | 0.0732 | 0.1305 |
| Β3 | 0.0134 | 0.1144 | 0.0017 | 0.4033 |
| β4 | 0.0109 | 0.0178 | 0.0605 | 0.3256 |
| β5 | 0.0055 | 0.0776 | 0.0124 | 0.3271 |
| Β5 | 0.1774 | 0.6055 | 0.2705 | 0.0125 |
| β7 | 0.2403 | 0.0562 | 0.0764 | 0.0025 |
| β8 | 0.7383 | 0.2642 | 0.0441 | 0.0311 |
| β9 | 0.1278 | 0.1035 | 0.4617 | 0.0545 |
| β10 | 0.0809 | 0.1262 | 0.1689 | 0.0099 |
| β11 | 0.0742 | 0.1614 | 0.0642 | 0.0507 |
| β12 | 0.0585 | 0.0152 | 0.0775 | 0.0018 |
| β13 | 0.2887 | 0.2434 | 0.3615 | 0.0116 |
| β14 | 0.3117 | 0.1903 | 0.1006 | 0.1038 |
| β15 | 0.2119 | 0.0763 | 0.0657 | 0.2121 |
| β16 | 0.1141 | 0.0235 | 0.8769 | 0.2278 |
| β17 | 0.0882 | 0.5864 | 0.0811 | 0.3147 |
| β18 | 0.4448 | 0.1371 | 0.0044 | 0.0141 |
| β19 | 0.0212 | 0.9322 | 0.0381 | 0.1348 |
Estimates of Hansen parameter
| Stochastic trends | LC statistics | Deterministic trends | Significance | |
|---|---|---|---|---|
| COVID-19 lockdown | 0.220 | 0.286 | 0.222 | 0.000 |
| Energy redevelopment | 0.300 | 0.643 | 0.740 | 0.000 |
| Energy efficiency financing | 0.609 | 0.600 | 0.698 | 0.000 |
| Green bonds | 0.772 | 0.823 | 0.976 | 0.000 |
Energy redevelopment verification
| Study constructs | HVRT | Power factor | ||
|---|---|---|---|---|
| Leading | Lagging | |||
| COVID-19 lockdown | 0.332 | 0.337 | 0.313 | 0.351 |
| Energy redevelopment | 0.495 | 0.838 | 0.601 | 0.078 |
| Energy efficiency financing | 0.101 | 0.900 | 0.808 | 0.321 |
| Green bonds | 0.777 | 0.711 | 0.889 | 0.003 |
Multiple uncertainty levels — robustness test
| Example 1 | Example 2 | Example 3 | Example 4 | |
|---|---|---|---|---|
| COVID-19 lockdown | 0.673 | 0.893 | 0.776 | 0.091 |
| Energy redevelopment | 0.786 | 0.456 | 0.001 | 0.452 |
| Energy efficiency financing | 0.441 | 0.784 | 0.087 | 0.671 |
| Green bonds | 0.592 | 0.777 | 0.093 | 0.993 |