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The causal relationship among electricity consumption, economic growth and capital stock in Iran

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  • Salmanzadeh-Meydani, N.
  • Fatemi Ghomi, S.M.T.

Abstract

Due to the progress in industries, electricity consumption (EC) plays a vital role in economic growth (EG) as one of the important components of production. Furthermore, the influence of capital stock (CS) and labor is significant in EG. The main purpose of this paper is to examine causality and relationship among EG, EC, and CS, to forecast these variables and to propose related policy viewpoints for Iran. The empirical findings indicate the lack of short-run causality between pairwise variables. The results of standard Granger-causality (SGC) test demonstrate a bi-directional long-run causality between EC and EG and a uni-directional long-run causality from EC to CS. To forecast variables, the vector auto regression (VAR) model is estimated using logged variables. The Ariño and Franses approach is applied to transform time series data and forecast variables. The performance of the estimated VAR model is investigated and it clarified a highly accurate estimation with mean absolute percentage errors (MAPEs) of less than 4% for all variables. The results of the impulse response function (IRF) analysis indicate the dynamic behavior of long-run causalities. Therefore, to reduce EC and avoid negative impact on EG, Iran should adopt appropriate and affordable policies to raise efficiency optimization of EC. Finally, four policies including privatization, industrialization, supervision of banking resources and allocation of credits and liberalization of electricity prices are proposed.

Suggested Citation

  • Salmanzadeh-Meydani, N. & Fatemi Ghomi, S.M.T., 2019. "The causal relationship among electricity consumption, economic growth and capital stock in Iran," Journal of Policy Modeling, Elsevier, vol. 41(6), pages 1230-1256.
  • Handle: RePEc:eee:jpolmo:v:41:y:2019:i:6:p:1230-1256
    DOI: 10.1016/j.jpolmod.2019.05.003
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    3. Navid Salmanzadeh-Meydani & S. M. T. Fatemi Ghomi & Seyedhamidreza Shahabi Haghighi & Kannan Govindan, 2023. "A multivariate quantitative approach for sustainability performance assessment: An upstream oil and gas company," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(3), pages 2777-2807, March.
    4. Xu, Guangyue & Yang, Hualiu & Schwarz, Peter, 2022. "A strengthened relationship between electricity and economic growth in China: An empirical study with a structural equation model," Energy, Elsevier, vol. 241(C).
    5. Tayebeh Sadat Tabatabaei & Pedram Asef, 2021. "Evaluation of Energy Price Liberalization in Electricity Industry: A Data-Driven Study on Energy Economics," Energies, MDPI, vol. 14(22), pages 1-19, November.
    6. Esmaeili, Parisa & Rafei, Meysam, 2021. "Dynamics analysis of factors affecting electricity consumption fluctuations based on economic conditions: Application of SVAR and TVP-VAR models," Energy, Elsevier, vol. 226(C).
    7. Flavian Emmanuel Sapnken & Jean Gaston Tamba & Salome Essiane Ndjakomo & Francis Djanna Koffi, 2020. "Oil Products Consumption and Economic Growth in Cameroon Households: An Assessment Using ARDL Cointegration and Granger Causality Analysis," International Journal of Energy Economics and Policy, Econjournals, vol. 10(6), pages 510-523.
    8. Zolfaghari, Mehdi & Kabiri, Mahbobe & Saadatmanesh, Hamideh, 2020. "Impact of socio-economic infrastructure investments on income inequality in Iran," Journal of Policy Modeling, Elsevier, vol. 42(5), pages 1146-1168.

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    More about this item

    Keywords

    Causality; Economic growth; Capital stock; Vector auto autoregression regression model; Impulse response function analysis;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

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