Does renewable energy consumption add in economic growth? An application of auto-regressive distributed lag model in Pakistan

被引:266
|
作者
Shahbaz, Muhammad [1 ]
Loganathan, Nanthakumar [2 ]
Zeshan, Mohammad [3 ,4 ]
Zaman, Khalid [5 ]
机构
[1] COMSATS Inst Informat Technol, Dept Management Sci, Lahore, Pakistan
[2] Univ Sultan ZainalAbidin, Fac Econ & Management Sci, Kuala Terengganu 21300, Terengganu, Malaysia
[3] Inha Univ, Inchon, South Korea
[4] Pukyong Natl Univ, Pusan, South Korea
[5] COMSATS Inst Informat Technol, Dept Management Sci, Abbottabad, Pakistan
来源
关键词
Renewable energy; Economic growth; Pakistan; ELECTRICITY CONSUMPTION; CAUSAL RELATIONSHIP; REAL OUTPUT; NEXUS; COINTEGRATION; DYNAMICS; GDP;
D O I
10.1016/j.rser.2015.01.017
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The objective of the study is to examine the relationship between renewable energy consumption and economic growth by incorporating capital and labour as potential determinants of production function in case of Pakistan. This study used auto-regressive distributed lag (ARDL) model and rolling window approach (RWA) for cointegration in context of Pakistan. The study used quarterly data over the period of 1972Q1-2011Q4. The causality analysis applied through VECM Granger causality and innovative accounting approaches. The results reveal that all the variables in the study are cointegrated that shows the long run relationship between the variables. Furthermore, renewable energy consumption, capital and labour boost economic growth. The causality analysis shows the feedback effect between economic growth and renewable energy consumption. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:576 / 585
页数:10
相关论文
共 50 条
  • [1] Economic growth and electricity consumption: Auto regressive distributed lag analysis
    Bildirici, Melike E.
    Bakirtas, Tahsin
    Kayikci, Fazil
    JOURNAL OF ENERGY IN SOUTHERN AFRICA, 2012, 23 (04) : 29 - 45
  • [2] Fiscal federalism and economic development in Nigeria: An auto-regressive distributed lag approach
    Ewetan, Olabanji Olukayode
    Matthew, Oluwatoyin A.
    Babajide, Abiola A.
    Osabohien, Romanus
    Urhie, Ese
    COGENT SOCIAL SCIENCES, 2020, 6 (01):
  • [3] Energy consumption, real GDP, and financial development nexus in Italy: an application of an auto-regressive distributed lag bound testing approach
    Magazzino, C.
    ENERGY PRODUCTION AND MANAGEMENT IN THE 21ST CENTURY II: THE QUEST FOR SUSTAINABLE ENERGY, 2016, 205 : 21 - 32
  • [4] An empirical investigation between renewable energy consumption, globalization and human capital: A dynamic auto-regressive distributive lag simulation
    Ozcan, Burcu
    Danish
    Temiz, Mehmet
    RENEWABLE ENERGY, 2022, 193 : 195 - 203
  • [5] Renewable energy, technological innovation and the environment: A novel dynamic auto-regressive distributive lag simulation
    Danish
    Ulucak, Recep
    RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2021, 150
  • [6] Natural Disasters, Economic Growth, and Carbon Emissions: Empirical Analysis of Chinese Data Based on a Nonlinear Auto-Regressive Distributed Lag Model
    Cao, Ming
    Xu, Yiming
    Sun, Yuanhong
    Cang, Dingbang
    SUSTAINABILITY, 2023, 15 (21)
  • [7] Renewable energy, technological innovation and the environment: A novel dynamic auto-regressive distributive lag simulation
    Danish
    Ulucak, Recep
    Renewable and Sustainable Energy Reviews, 2021, 150
  • [8] Dynamics of material productivity and socioeconomic factors based on auto-regressive distributed lag model in China
    Wang, Tao
    Yu, Yadong
    Zhou, Wenji
    Liu, Bomin
    Chen, Dingjiang
    Zhu, Bing
    JOURNAL OF CLEANER PRODUCTION, 2016, 137 : 752 - 761
  • [9] China's energy consumption forecasting by GMDH based auto-regressive model
    Xie, Ling
    Xiao, Jin
    Hu, Yi
    Zhao, Hengjun
    Xiao, Yi
    JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY, 2017, 30 (06) : 1332 - 1349
  • [10] GMDH Based Auto-regressive Model for China's Energy Consumption Prediction
    Xiao, Jin
    Sun, Haiyan
    Hu, Yi
    Xiao, Yi
    2015 INTERNATIONAL CONFERENCE ON LOGISTICS, INFORMATICS AND SERVICE SCIENCES (LISS), 2015,