# Examining the Relationship between Rural and Urban Populations’ Access to Electricity and Economic Growth: A New Evidence

^{1}

^{2}

^{3}

^{*}

## Abstract

**:**

_{2}emissions; therefore, possible conservative strategies and policies are required from the Chinese government to use clean energy sources to fulfill its energy demand.

## 1. Introduction

## 2. Existing Literature

_{2}emissions on the environment [35,36].

## 3. Materials and Methods

#### 3.1. Econometric Model and Data Sources

#### 3.2. Granger Causality Technique under Vector Error Correction Model (VECM)

## 4. Empirical Outcomes and Discussion

#### 4.1. Descriptive Statistics and Variables Correlation

#### 4.2. Unit Root Testing amid Variables

#### 4.3. Bounds Test to Cointegration

#### 4.4. Symmetric (ARDL) Technique Outcomes

_{2}released per unit of power. Exponential increases in energy consumption and fast increases in pollutant emissions are predicted to have evident repercussions on the global environment: increasing global temperatures, instability in temperature and severe weather, and changes in ecosystems and habitats. All of these consequences offer growing problems for energy production and usage and have an increasing role in the design of future energy systems and energy policy [54,55]. Likewise, the demand for economic expansion leads to environmental deterioration, which is typically the outcome of development and industrialization in both emerging and developed economies. Economic development in every nation relies on many variables that might adversely affect the environment, such as unsustainable natural resource exploitation, environmental degradation, and climate change. In addition, the fast development in urbanization in many countries has hastened economic growth, resulting in greater energy consumption. Therefore, a crucial challenge confronting many nations is the carbon dioxide content of the atmosphere, which is growing considerably due to energy use and economic expansion. Fossil fuels, including coal, natural oil, and natural gas, are the primary source of energy, and they also lead to greater carbon dioxide emissions [56,57].

^{2}, adjusted R

^{2}, F-Stat., Akaike info criterion, and Durbin–Watson statistics are (0.864), (0.813), (17.017), (−1.835), and (2.112). Figure 4 illustrates the CUSUM and its squares plot with stable trends at the 5% significance level.

#### 4.5. Granger Causality Test under VECM Outcomes

## 5. Conclusions and Recommendations

_{2}. It is critical that the Chinese government adopts realistic and conservative plans and strategies in order to satisfy the country’s energy demands as efficiently as possible by utilizing renewable resources.

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## References

- Chen, Y.; Fang, Z. Industrial electricity consumption, human capital investment and economic growth in Chinese cities. Econ. Model.
**2018**, 69, 205–219. [Google Scholar] [CrossRef] - Shengfeng, X.; Sheng, X.M.; Tianxing, Z.; Xuelli, Z. The relationship between electricity consumption and economic growth in China. Phys. Procedia
**2012**, 24, 56–62. [Google Scholar] [CrossRef] [Green Version] - Zhang, C.; Zhou, K.; Yang, S.; Shao, Z. On electricity consumption and economic growth in China. Renew. Sustain. Energy Rev.
**2017**, 76, 353–368. [Google Scholar] [CrossRef] - Shiu, A.; Lam, P.-L. Electricity consumption and economic growth in China. Energy Policy
**2004**, 32, 47–54. [Google Scholar] [CrossRef] - Wang, S.S.; Zhou, D.Q.; Zhou, P.; Wang, Q.W. CO
_{2}emissions, energy consumption and economic growth in China: A panel data analysis. Energy Policy**2011**, 39, 4870–4875. [Google Scholar] [CrossRef] - Zaman, M.; Shaheen, F.; Haider, A.; Qamar, S. Examining relationship between electricity consumption and its major determinants in Pakistan. Int. J. Energy Econ. Policy
**2015**, 5, 998–1009. [Google Scholar] - Hirsh, R.F.; Koomey, J.G. Electricity consumption and economic growth: A new relationship with significant consequences? Electr. J.
**2015**, 28, 72–84. [Google Scholar] [CrossRef] - Wolde-Rufael, Y. Electricity consumption and economic growth: A time series experience for 17 African countries. Energy Policy
**2006**, 34, 1106–1114. [Google Scholar] [CrossRef] - Burke, P.; Stern, D.; Bruns, S.B. The impact of electricity on economic development: A macroeconomic perspective. Int. Rev. Environ. Resour. Econ.
**2018**, 12, 85–127. [Google Scholar] [CrossRef] - Chang, C.-C. A multivariate causality test of carbon dioxide emissions, energy consumption and economic growth in China. Appl. Energy
**2010**, 87, 3533–3537. [Google Scholar] [CrossRef] - Yuan, J.; Zhao, C.; Yu, S.; Hu, Z. Electricity consumption and economic growth in China: Cointegration and co-feature analysis. Energy Econ.
**2007**, 29, 1179–1191. [Google Scholar] [CrossRef] - Wang, Y.; Wang, Y.; Zhou, J.; Zhu, X.; Lu, G. Energy consumption and economic growth in China: A multivariate causality test. Energy Policy
**2011**, 39, 4399–4406. [Google Scholar] [CrossRef] - Zhang, C.; Su, B.; Zhou, K.; Yang, S. Analysis of electricity consumption in China (1990–2016) using index decomposition and decoupling approach. Jour. of Clea. Prod.
**2019**, 224–235. [Google Scholar] [CrossRef] - Lin, B.; Liu, C. Why is electricity consumption inconsistent with economic growth in China? Energy Policy
**2016**, 88, 310–316. [Google Scholar] [CrossRef] - Apergis, N.; Payne, J.E. Renewable and non-renewable electricity consumption–growth nexus: Evidence from emerging market economies. Appl. Energy
**2011**, 88, 5226–5230. [Google Scholar] [CrossRef] - Chen, S.-T.; Kuo, H.-I.; Chen, C.-C. The relationship between GDP and electricity consumption in 10 Asian countries. Energy Policy
**2007**, 35, 2611–2621. [Google Scholar] [CrossRef] - Džananović, E.; Dacić-Lepara, S. The relationship between GDP and electricity consumption in Southeast European countries. In Advanced Technologies, Systems and Applications; Springer: Cham, Switzerland, 2017; pp. 207–215. [Google Scholar] [CrossRef]
- Bildirici, M.; Bakirtas, T.; Kayıkçı, F. Economic growth and electricity consumption: Auto regressive distributed lag analysis. J. Energy S. Afr.
**2012**, 23, 29–45. [Google Scholar] [CrossRef] - Ferguson, R.; Wilkinson, W.; Hill, R. Electricity use and economic development. Energy Policy
**2000**, 28, 923–934. [Google Scholar] [CrossRef] - He, Y.; Guang, F.; Wang, M. The efficiency of electricity-use of China and its influencing factors. Energy
**2018**, 163, 258–269. [Google Scholar] [CrossRef] - Azam, A.; Rafiq, M.; Shafique, M.; Yuan, J. Renewable electricity generation and economic growth nexus in developing countries: An ARDL approach. Econ. Res. Ekon. Istraž.
**2021**, 34, 2423–2446. [Google Scholar] [CrossRef] - Chen, Y.; Wang, Z.; Zhong, Z. CO
_{2}emissions, economic growth, renewable and non-renewable energy production and foreign trade in China. Renew. Energy**2019**, 131, 208–216. [Google Scholar] [CrossRef] - Zafar, M.W.; Shahbaz, M.; Hou, F.; Sinha, A. From nonrenewable to renewable energy and its impact on economic growth: The role of research & development expenditures in Asia-Pacific Economic Cooperation countries. J. Clean. Prod.
**2019**, 212, 1166–1178. [Google Scholar] [CrossRef] - Mohapatra, G.; Giri, A.K. Examining the relationship between electricity consumption, economic growth, energy prices and technology development in India. Indian Econ. J.
**2020**, 68, 515–534. [Google Scholar] [CrossRef] - Kahouli, B. The causality link between energy electricity consumption, CO
_{2}emissions, R&D stocks and economic growth in Mediterranean countries (MCs). Energy**2018**, 145, 388–399. [Google Scholar] [CrossRef] - Smulders, S.; de Nooij, M. The impact of energy conservation on technology and economic growth. Resour. Energy Econ.
**2003**, 25, 59–79. [Google Scholar] [CrossRef] [Green Version] - Asghar, Z. Energy-GDP relationship: A causal analysis for the five countries of South Asia. Appl. Econom. Int. Dev.
**2008**, 8, 167–180. [Google Scholar] - Gertler, P.J.; Lee, K.; Mobarak, A.M. Electricity reliability and economic development in cities: A microeconomic perspective. J. Public Econ.
**2017**, 126, 64–73. [Google Scholar] - Allcott, H.; Collard-Wexler, A.; O’Connell, S.D. How do electricity shortages affect industry? Evidence from India. Am. Econ. Rev.
**2016**, 106, 587–624. [Google Scholar] [CrossRef] [Green Version] - Toman, M.T.; Jemelkova, B. Energy and economic development: An assessment of the state of knowledge. Energy J.
**2003**, 24, 93–112. [Google Scholar] [CrossRef] - Nakićenović, N. Freeing energy from carbon. Daedalus
**1996**, 125, 95–112. [Google Scholar] - Sharif, A.; Raza, S.A. Dynamic relationship between urbanization, energy consumption and environmental degradation in Pakistan: Evidence from structure break testing. J. Manag. Sci.
**2016**, 3, 3–23. [Google Scholar] [CrossRef] [Green Version] - Raza, S.A.; Jawaid, S.T.; Siddiqui, M.H. Electricity consumption and economic growth in South Asia. South Asia Econ. J.
**2016**, 17, 200–215. [Google Scholar] [CrossRef] - Ogundipe, A.A.; Akinyemi, O.; Ogundipe, M.O. Electricity consumption and economic development in Nigeria. Int. J. Energy Econ. Policy
**2016**, 6, 134–143. [Google Scholar] [CrossRef] [Green Version] - Aneja, R.; Banday, U.J.; Hasnat, T.; Koçoğlu, M. Renewable and non-renewable energy consumption and economic growth: Empirical evidence from panel error correction model. Jindal J. Bus. Res.
**2017**, 6, 76–85. [Google Scholar] [CrossRef] - Kahia, M.; Ben Aïssa, M.S.; Charfeddine, L. Impact of renewable and non-renewable energy consumption on economic growth: New evidence from the MENA Net Oil Exporting Countries (NOECs). Energy
**2016**, 116, 102–115. [Google Scholar] [CrossRef] - Afshar, O.; Saidur, R.; Hasanuzzaman, M.; Jameel, M. A review of thermodynamics and heat transfer in solar refrigeration system. Renew. Sustain. Energy Rev.
**2012**, 16, 5639–5648. [Google Scholar] [CrossRef] - Daut, M.A.M.; Hassan, M.Y.; Abdullah, H.; Rahman, H.A.; Abdullah, P.; Hussin, F. Building electrical energy consumption forecasting analysis using conventional and artificial intelligence methods: A review. Renew. Sustain. Energy Rev.
**2017**, 70, 1108–1118. [Google Scholar] [CrossRef] - Mohammadi, M.; Noorollahi, Y.; Mohammadi-Ivatloo, B.; Yousefi, H. Energy hub: From a model to a concept—A review. Renew. Sustain. Energy Rev.
**2017**, 80, 1512–1527. [Google Scholar] [CrossRef] - Sepehr, M.; Eghtedaei, R.; Toolabimoghadam, A.; Noorollahi, Y.; Mohammadi, M. Modeling the electrical energy consumption profile for residential buildings in Iran. Sustain. Cities Soc.
**2018**, 41, 481–489. [Google Scholar] [CrossRef] - Engle, R.F.; Granger, C.W.J. Co-integration and error correction: Representation, estimation, and testing. Econometrica J. Econom. Soc.
**1987**, 55, 251–276. [Google Scholar] [CrossRef] - Pesaran, M.H.; Shin, Y. An Autoregressive Distributed Lag Modelling Approach to Cointegration Analysis; University of Cambridge: Cambridge, UK, 1995. [Google Scholar]
- Johansen, S.; Juselius, K. Maximum likelihood estimation and inference on cointegration—With applications to the demand for money. Oxf. Bull. Econ. Stat.
**1990**, 52, 169–210. [Google Scholar] [CrossRef] - Pesaran, M.H.; Shin, Y.; Smith, R.J. Bounds testing approaches to the analysis of level relationships. J. Appl. Econom.
**2001**, 16, 289–326. [Google Scholar] [CrossRef] - Fuller, W.A. Distribution of the estimators for autoregressive time series with a unit root. J. Am. Stat. Assoc.
**1979**, 74, 427–431. [Google Scholar] - Phillips, P.C.; Perron, P. Testing for a unit root in time series regression. Biometrika
**1988**, 75, 335–346. [Google Scholar] [CrossRef] - Dwyer, G.P. The Johansen Tests for Cointegration. White Paper, 1–7. 2015. Available online: http://jerrydwyer.com/pdf/Clemson/Cointegration.pdf (accessed on 20 May 2022).
- Ashraf, Z.; Javid, A.Y.; Javid, M. Electricity consumption and economic growth: Evidence from Pakistan. Econ. Bus. Lett.
**2013**, 2, 21–32. [Google Scholar] [CrossRef] [Green Version] - Kim, Y.S. Electricity consumption and economic development: Are countries converging to a common trend? Energy Econ.
**2015**, 49, 192–202. [Google Scholar] [CrossRef] - Zhou, Y.; Liu, Y.; Wu, W.; Li, Y. Effects of rural–urban development transformation on energy consumption and CO 2 emissions: A regional analysis in China. Renew. Sustain. Energy Rev.
**2015**, 52, 863–875. [Google Scholar] [CrossRef] - Zhang, Y.-J.; Peng, Y.-L.; Ma, C.-Q.; Shen, B. Can environmental innovation facilitate carbon emissions reduction? Evidence from China. Energy Policy
**2017**, 100, 18–28. [Google Scholar] [CrossRef] - Dong, X.-Y.; Hao, Y. Would income inequality affect electricity consumption? Evidence from China. Energy
**2018**, 142, 215–227. [Google Scholar] [CrossRef] - Yoo, S.-H.; Lee, J.-S. Electricity consumption and economic growth: A cross-country analysis. Energy Policy
**2010**, 38, 622–625. [Google Scholar] [CrossRef] - Belaïd, F.; Zrelli, M.H. Renewable and non-renewable electricity consumption, environmental degradation and economic development: Evidence from Mediterranean countries. Energy Policy
**2019**, 133, 110929. [Google Scholar] [CrossRef] - Aydin, M. Renewable and non-renewable electricity consumption–economic growth nexus: Evidence from OECD countries. Renew. Energy
**2019**, 136, 599–606. [Google Scholar] [CrossRef] - Phimphanthavong, H. The impacts of economic growth on environmental conditions in Laos. Int. J. Bus. Manag. Econ. Res.
**2013**, 4, 766–774. [Google Scholar] - Osobajo, O.; Otitoju, A.; Otitoju, M.; Oke, A. The impact of energy consumption and economic growth on carbon dioxide emissions. Sustainability
**2020**, 12, 7965. [Google Scholar] [CrossRef] - Rehman, A.; Radulescu, M.; Ma, H.; Dagar, V.; Hussain, I.; Khan, M.K. The impact of globalization, energy use, and trade on ecological footprint in Pakistan: Does environmental sustainability exist? Energies
**2021**, 14, 5234. [Google Scholar] [CrossRef] - Sharif, A.; Raza, S.A.; Ozturk, I.; Afshan, S. The dynamic relationship of renewable and nonrenewable energy consumption with carbon emission: A global study with the application of heterogeneous panel estimations. Renew. Energy
**2019**, 133, 685–691. [Google Scholar] [CrossRef] - Saidi, K.; Rahman, M.M.; Amamri, M. The causal nexus between economic growth and energy consumption: New evidence from global panel of 53 countries. Sustain. Cities Soc.
**2017**, 33, 45–56. [Google Scholar] [CrossRef] - Wang, Y. The analysis of the impacts of energy consumption on environment and public health in China. Energy
**2010**, 35, 4473–4479. [Google Scholar] [CrossRef] - Muhammad, F.; Karim, R.; Muhammad, K.; Asghar, A. Population density, CO
_{2}emission and energy consumption in Pakistan: A multivariate analysis. Int. J. Energy Econ. Policy**2020**, 10, 250. [Google Scholar] [CrossRef]

LnECG | LnAEP | LnAERP | LnAEUP | LnENUS | |
---|---|---|---|---|---|

Mean | 2.220 | 4.574 | 4.559 | 4.603 | 7.146 |

Median | 2.235 | 4.577 | 4.559 | 4.603 | 7.082 |

Maximum | 2.655 | 4.605 | 4.605 | 4.605 | 7.743 |

Minimum | 1.362 | 4.524 | 4.496 | 4.597 | 6.602 |

Std. Dev. | 0.277 | 0.026 | 0.035 | 0.002 | 0.423 |

Skewness | −0.731 | −0.386 | −0.162 | −0.866 | 0.173 |

Kurtosis | 4.523 | 1.883 | 1.766 | 2.492 | 1.374 |

Jarque-Bera | 5.207 | 2.153 | 1.899 | 3.803 | 3.224 |

Probability | 0.073 | 0.340 | 0.386 | 0.149 | 0.199 |

LnECG | LnAEP | LnAERP | LnAEUP | LnENUS | |
---|---|---|---|---|---|

LnECG | (1.000) | −0.140 | −0.187 | −0.074 | −0.188 |

LnAEP | −0.140 | (1.000) | 0.993 | 0.958 | 0.953 |

LnAERP | −0.187 | 0.993 | (1.000) | 0.934 | 0.969 |

LnAEUP | −0.074 | 0.958 | 0.934 | (1.000) | 0.849 |

LnENUS | −0.188 | 0.953 | 0.969 | 0.849 | (1.000) |

DF-GLS Tests (at the Level) I (0) | |||||
---|---|---|---|---|---|

LnECG | LnAEP | LnAERP | LnAEUP | LnENUS | |

Probability values * with Test statistics | −1.998 (0.056) | −1.122 (0.273) | −0.786 (0.440) | −0.615 (0.544) | −1.753 (0.101) |

DF-GLS Tests at First Difference I (1) | |||||

Probability values * with Test statistics | −0.738 (0.008) | −0.392 (0.007) | −5.506 (0.000) | −6.998 (0.000) | −2.059 (0.050) |

P-P Test (at the Level) I (0) | |||||

Probability values * with Test statistics | −3.962 (0.005) | −4.039 (0.666) | −2.012 (0.279) | −4.361 (0.002) | −0.008 (0.949) |

P-P Test at First Difference I (1) | |||||

Probability values * with Test statistics | −8.359 (0.000) | −1.182 (0.004) | −5.386 (0.000) | −7.000 (0.000) | −2.786 (0.074) |

[F-Bounds Testing] | Founds no Levels Relationship at Null Hypothesis | |||
---|---|---|---|---|

[Critical Values] | [Lower Bound I (0)] | [Upper Bound I (1)] | ||

F-statistic value | [5.486] | [10%] | 2.2 | 3.09 |

[5%] | 2.56 | 3.49 | ||

[2.5%] | 2.88 | 3.87 | ||

[1%] | 3.29 | 4.37 |

Trace Test | ||||
---|---|---|---|---|

E-Value | T-Statistic | C-Values at (0.05) | Prob. Values ** | Hypo-No. of CE(s) |

0.814 | 103.962 | 69.818 | 0.000 | None * |

0.688 | 60.126 | 47.856 | 0.002 | At most 1 * |

0.526 | 29.780 | 29.797 | 0.050 | At most 2 |

0.225 | 10.322 | 15.494 | 0.256 | At most 3 |

0.132 | 3.694 | 3.841 | 0.054 | At most 4 |

Maximum Eigenvalue Test | ||||

E-Value | Max-EigenStatistic | C-Values at (0.05) | Prob. Values ** | Hypo-No. of CE(s) |

0.814 | 43.835 | 33.876 | 0.002 | None * |

0.688 | 30.345 | 27.584 | 0.021 | At most 1 * |

0.526 | 19.458 | 21.131 | 0.084 | At most 2 |

0.225 | 6.627 | 14.264 | 0.534 | At most 3 |

0.132 | 3.694 | 3.841 | 0.054 | At most 4 |

Short-Run Dynamics | ||||
---|---|---|---|---|

Variables | Coefficients | Standard Error | Test Statistic | p-Values |

C | −173.126 | 151.376 | −1.143 | 0.269 |

LnGDPG(−1) | −0.492 | 0.123 | −3.976 | 0.001 |

LnAEP | 8.038 | 10.985 | 0.731 | 0.004 |

LnAERP | −14.125 | 7.547 | −1.871 | 0.079 |

LnAEUP | 43.196 | 37.743 | 1.144 | 0.000 |

LnENUS(−1) | 0.409 | 0.310 | 1.317 | 0.007 |

D(ENUS) | 2.047 | 0.660 | 3.100 | 0.006 |

CointEq(−1) | −0.492 | 0.074 | −6.572 | 0.000 |

Long-run Dynamics | ||||

Variables | Coefficients | Standard Error | Test Statistic | p-Values |

LnAEP | 16.334 | 22.840 | 0.715 | 0.005 |

LnAERP | −28.704 | 14.646 | −1.959 | 0.077 |

LnAEUP | 87.776 | 77.554 | 1.131 | 0.000 |

LnENUS | 0.832 | 0.546 | 1.522 | 0.047 |

C | −351.800 | 316.662 | −1.110 | 0.283 |

Stability Tests | ||||

R^{2}Log likelihood Prob(F-statistic) Schwarz criterion D-Watson stat | 0.864 28.105 0.000 −1.489 2.112 | Adjusted R^{2}F-statistic AIC HQC | 0.813 17.017 −1.835 −1.748 |

Tests | F-Statistics | Prob. Values |
---|---|---|

[Serial Correlation LM Test of Breusch–Godfrey] | 0.367 | 0.698 |

[Harvey Heteroskedasticity Test] | 0.479 | 0.813 |

[CUSUM test] | Stable | |

[CUSUM of Squares test] | Stable |

Dependent Variables | Independent Variables | ||||
---|---|---|---|---|---|

ΔLnECG | ΔLnAEP | ΔLnAERP | ΔLnAEUP | ΔLnENUS | |

ΔLnECG | - | 2.674 | 5.774 ** | 0.000 | 0.719 ** |

ΔLnAEP | 1.255 | - | 5.094 ** | 1.410 | 2.047 |

ΔLnAERP | 0.593 | 6.586 | - | 0.936 | 1.399 |

ΔLnAEUP | 0.235 * | 1.781 | 3.071 | - | 1.740 |

ΔLnENUS | 0.898 | 2.489 | 2.374 * | 0.704 | - |

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |

© 2022 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

**MDPI and ACS Style**

Milin, I.A.; Mungiu Pupazan, M.C.; Rehman, A.; Chirtoc, I.E.; Ecobici, N.
Examining the Relationship between Rural and Urban Populations’ Access to Electricity and Economic Growth: A New Evidence. *Sustainability* **2022**, *14*, 8125.
https://doi.org/10.3390/su14138125

**AMA Style**

Milin IA, Mungiu Pupazan MC, Rehman A, Chirtoc IE, Ecobici N.
Examining the Relationship between Rural and Urban Populations’ Access to Electricity and Economic Growth: A New Evidence. *Sustainability*. 2022; 14(13):8125.
https://doi.org/10.3390/su14138125

**Chicago/Turabian Style**

Milin, Ioana Anda, Mariana Claudia Mungiu Pupazan, Abdul Rehman, Irina Elena Chirtoc, and Nicolae Ecobici.
2022. "Examining the Relationship between Rural and Urban Populations’ Access to Electricity and Economic Growth: A New Evidence" *Sustainability* 14, no. 13: 8125.
https://doi.org/10.3390/su14138125