Energy intensity convergence in Iranian provinces: evidence from energy carriers’ consumption intensity

Abstract

Investigating the energy intensity convergence in Iran, as a country with very high energy intensity in the world, is important in order to assess whether the government’s energy policies were effective to reduce energy intensity and its externality effects. This research investigated the convergence of total energy intensity and energy carriers’ consumption intensity in Iran and whether the energy intensity in the provinces with high energy intensity has been converged to the provinces with low energy intensity. To that end, the Markov chain method was used to investigate the convergence of total energy intensity and energy carriers’ consumption intensity in Iranian provinces from 2002 to 2016. The results indicated that there was club convergence in total energy, natural gas, electricity, and oil consumption intensity. Therefore, provinces with similar levels of energy intensity (e.g., high energy intensity and low energy intensity) converged to a unique steady state.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16

Data availability

The datasets generated and/or analyzed during the current study are available in https://pep.moe.gov.ir/.

Notes

  1. 1.

    The authors examined spatial Markov chain, but there were no spatial effects. Therefore, the results of spatial Markov chain did not report in the article. The results are available from the authors on request.

  2. 2.

    The authors examined the spatial Markov chain, but there were no spatial effects. Therefore, the results of spatial Markov chain were not reported in the article. The results are available from the authors on request.

  3. 3.

    The authors examined the spatial Markov chain, but there were no spatial effects. Therefore, the results of spatial Markov chain were not reported in the article. The results are available from the authors on request.

  4. 4.

    The authors examined the spatial Markov chain, but there were no spatial effects. Therefore, the results of the spatial Markov chain were not reported in the article. The results are available from the authors on request.

References

  1. Abid M, Alimi M (2019) Stochastic convergence in US disaggregated gas consumption at the sector level. J Nat Gas Sci Eng 61:357–368

    Article  Google Scholar 

  2. Aydin C, Esen Ö (2018) Does the level of energy intensity matter in the effect of energy consumption on the growth of transition economies? Evidence from dynamic panel threshold analysis. Energy Econ 69:185–195

    Article  Google Scholar 

  3. Bai C, Feng C, Du K, Wang Y, Gong Y (2020) Understanding spatial-temporal evolution of renewable energy technology innovation in China: evidence from convergence analysis. Energy Policy 143:111570

  4. Balcilar M, Emir F, & Roubaud D (2018) The Dynamics of Energy Intensity Convergence in the EU-28 Countries (No. 15-37)

  5. Barkhordari S, Fattahi M (2017) Reform of energy prices, energy intensity and technology: a case study of Iran (ARDL approach). Energy Strategy Rev 18:18–23

    Article  Google Scholar 

  6. Barro RJ (1991) Economic growth in a cross section of countries. Q J Econ 106(2):407–443

    Article  Google Scholar 

  7. Belzer DB, Bender SR, & Cort KA (2017) A comprehensive system of energy intensity indicators for the US: methods, data and key trends (No. PNNL-22267 Rev 2). Pacific Northwest National Lab.(PNNL), Richland (United States).

  8. Bhattacharya M, Inekwe JN, Sadorsky P, Saha A (2018) Convergence of energy productivity across Indian states and territories. Energy Econ 74:427–440

    Article  Google Scholar 

  9. Bhattacharya M, Inekwe JN, Sadorsky P (2020) Convergence of energy productivity in Australian states and territories: determinants and forecasts. Energy Econ 85:104538

    Article  Google Scholar 

  10. Bulut U, Durusu-Ciftci D (2018) Revisiting energy intensity convergence: new evidence from OECD countries. Environ Sci Pollut Res 25(13):12391–12397

    Article  Google Scholar 

  11. Burnett JW, Madariaga J (2017) The convergence of US state-level energy intensity. Energy Econ 62:357–370

    Article  Google Scholar 

  12. Canel C, Guris S, Guris B, Öktem B, Oktem R (2017) Convergence of energy intensity in OECD countries. Mod Econ 8(07):946–958

    Article  Google Scholar 

  13. Cheng Z, Liu J, Li L, Gu X (2020) Research on meta-frontier total-factor energy efficiency and its spatial convergence in Chinese provinces. Energy Econ 86:104702

    Article  Google Scholar 

  14. Conlen M (2019) Kernel Density Estimation. URL: https://mathisonian. github. io/kde/(visited on 05/11/2019)

  15. Dargahi H, Khameneh KB (2019) Energy intensity determinants in an energy-exporting developing economy: case of Iran. Energy 168:1031–1044

    Article  Google Scholar 

  16. Duro JA, Padilla E (2011) Inequality across countries in energy intensities: an analysis of the role of energy transformation and final energy consumption. Energy Econ 33(3):474–479

    Article  Google Scholar 

  17. Ezcurra R (2007) Distribution dynamics of energy intensities: a cross-country analysis. Energy Policy 35(10):5254–5259

    Article  Google Scholar 

  18. Fallahi F (2017) Stochastic convergence in per capita energy use in world. Energy Econ 65:228–239

    Article  Google Scholar 

  19. Farajzadeh Z, Nematollahi MA (2018) Energy intensity and its components in Iran: determinants and trends. Energy Econ 73:161–177

    Article  Google Scholar 

  20. Friedman M (1992) Do old fallacies ever die?. J Econ Lit 30(4):2129–2132

  21. Hajko V (2014) The energy intensity convergence in the transport sector. Procedia Econ Finance 12:199–205

    Article  Google Scholar 

  22. Hasanbeigi A, Hasanabadi A, Abdorrazaghi M (2012) Comparison analysis of energy intensity for five major sub-sectors of the textile industry in Iran. J Clean Prod 23(1):186–194

    Article  Google Scholar 

  23. Hatzigeorgiou E, Polatidis H, Haralambopoulos D (2011) CO2 emissions, GDP and energy intensity: a multivariate cointegration and causality analysis for Greece, 1977–2007. Appl Energy 88(4):1377–1385

    Article  Google Scholar 

  24. Hembram S, Maji S, Haldar SK (2019) Club convergence among the major Indian states during 1982–2014: does investment in human capital matter? South Asia Econ J 20(2):184–204

    Article  Google Scholar 

  25. Herrerias MJ (2012) World energy intensity convergence revisited: a weighted distribution dynamics approach. Energy Policy 49:383–399

    Article  Google Scholar 

  26. Herrerias MJ, Aller C, Ordóñez J (2017) Residential energy consumption: a convergence analysis across Chinese regions. Energy Econ 62:371–381

    Article  Google Scholar 

  27. Herrerias MJ, Liu G (2013) Electricity intensity across Chinese provinces: new evidence on convergence and threshold effects. Energy Econ 36:268–276

  28. Huang Z, Zhang H, Duan H (2019a) Nonlinear globalization threshold effect of energy intensity convergence in Belt and Road countries. J Clean Prod 237:117750

    Article  Google Scholar 

  29. Huang J, Zheng X, Wang A, Cai X (2019b) Convergence analysis of China’s energy intensity at the industrial sector level. Environ Sci Pollut Res 26(8):7730–7742

    Article  Google Scholar 

  30. Huang J, Zhang H, Peng W, Hu C (2020) Impact of energy technology and structural change on energy demand in China. Sci Total Environ 143345

  31. Huang J, Chen X, Cai X, Zou H (2021) Assessing the impact of energy-saving R&D on China’s energy consumption: Evidence from dynamic spatial panel model. Energy 218:119443

    Article  Google Scholar 

  32. Ibe O (2009) Markov processes for stochastic modeling, 2nd edn. Elsevier Academic Press

  33. Iranian parliament research center (2015a) Weekly energy evaluation. Office of energy, industry and mining Studies. Report number, 14214. https://rc.majlis.ir/fa/mrc_report/show/926206

  34. Iranian parliament research center (2015b) Ambiguity in energy intensity statistics and comparison Iran's energy statistics with other countries. Office of energy, industry and mining Studies. Report number, 14300. https://rc.majlis.ir/fa/mrc_report/show/931013

  35. Jiang L, Folmer H, Ji M, Zhou P (2018) Revisiting cross-province energy intensity convergence in China: a spatial panel analysis. Energy Policy 121:252–263

    Article  Google Scholar 

  36. Karimu A, Brännlund R, Lundgren T, Söderholm P (2017) Energy intensity and convergence in Swedish industry: a combined econometric and decomposition analysis. Energy Econ 62:347–356

    Article  Google Scholar 

  37. Kim YS (2015) Electricity consumption and economic development: are countries converging to a common trend? Energy Econ 49:192–202

    Article  Google Scholar 

  38. Kiran B (2013) Energy intensity convergence in OECD countries. Energy Explor Exploit 31(2):237–247

    Article  Google Scholar 

  39. Kounetas KE (2018) Energy consumption and CO2 emissions convergence in European Union member countries. A tonneau des Danaides? Energy Econ 69:111–127

    Article  Google Scholar 

  40. Le Gallo J (2004) Space-time analysis of GDP disparities among European regions: a Markov chains approach. Int Reg Sci Rev 27(2):138–163

    Article  Google Scholar 

  41. Le Pen Y, Sévi B (2010) On the non-convergence of energy intensities: evidence from a pair-wise econometric approach. Ecol Econ 69(3):641–650

    Article  Google Scholar 

  42. Li W, Zhao T, Wang Y, Zheng X, Yang J (2019) How does foreign direct investment influence energy intensity convergence in China? Evidence from prefecture-level data. J Clean Prod 219:57–65

    Article  Google Scholar 

  43. Liddle B (2010) Revisiting world energy intensity convergence for regional differences. Appl Energy 87(10):3218–3225

    Article  Google Scholar 

  44. Liddle B (2012) OECD energy intensity. Energy Efficiency 5(4):583–597

    Article  Google Scholar 

  45. Markandya A, Pedroso-Galinato S, Streimikiene D (2006) Energy intensity in transition economies: is there convergence towards the EU average? Energy Econ 28(1):121–145

    Article  Google Scholar 

  46. Martinez DM, Ebenhack BW, Wagner TP (2019) Energy efficiency: Concepts and calculations. Elsevier

  47. Mielnik O, Goldemberg J (2000) Converging to a common pattern of energy use in developing and industrialized countries. Energy Policy 28(8):503–508

    Article  Google Scholar 

  48. Mohammadi H, Ram R (2012) Cross-country convergence in energy and electricity consumption, 1971–2007. Energy Econ 34(6):1882–1887

    Article  Google Scholar 

  49. Monfort P (2008) Convergence of EU regions: Measures and evolution. European Commission, Regional Policy, Brussels

    Google Scholar 

  50. Mulder P, De Groot HL (2012) Structural change and convergence of energy intensity across OECD countries, 1970–2005. Energy Econ 34(6):1910–1921

    Article  Google Scholar 

  51. Mulder P, De Groot HL, Pfeiffer B (2014) Dynamics and determinants of energy intensity in the service sector: a cross-country analysis, 1980–2005. Ecol Econ 100:1–15

    Article  Google Scholar 

  52. Mussini M (2020) Inequality and convergence in energy intensity in the European Union. Appl Energy 261:114371

    Article  Google Scholar 

  53. Neven D, Gouyette C (1995) Regional convergence in the European Community. J Common Mark Stud 33:47–65

    Article  Google Scholar 

  54. Pan X, Liu Q, Peng X (2015) Spatial club convergence of regional energy efficiency in China. Ecol Indic 51:25–30

    Article  Google Scholar 

  55. Parker S, Liddle B (2017) Economy-wide and manufacturing energy productivity transition paths and club convergence for OECD and non-OECD countries. Energy Econ 62:338–346

    Article  Google Scholar 

  56. Payne JE, Vizek M, Lee J (2017) Stochastic convergence in per capita fossil fuel consumption in U.S. states. Energy Econ 62:382–395

    Article  Google Scholar 

  57. Pesaran MH (2007) A pair-wise approach to testing for output and growth convergence. J Econom 138(1):312–355

  58. Phillips PC, Sul D (2007) Transition modeling and econometric convergence tests. Econometrica 75(6):1771–1855

  59. Qi S, Peng H, Zhang X, Tan X (2019) Is energy efficiency of Belt and Road Initiative countries catching up or falling behind? Evidence from a panel quantile regression approach. Appl Energy 253:113581

    Article  Google Scholar 

  60. Quah D (1993) Empirical cross-section dynamics in economic growth. Eur Econ Rev 37:426–434

    Article  Google Scholar 

  61. Quah DT (1997) Empirics for growth and distribution: stratification, polarization, and convergence clubs. J Econ Growth 2(1):27–59

    Article  Google Scholar 

  62. Reboredo JC (2015) Renewable energy contribution to the energy supply: is there convergence across countries? Renew Sust Energ Rev 45:290–295

    Article  Google Scholar 

  63. Santiago R, Fuinhas JA, Marques AC (2020) An analysis of the energy intensity of Latin American and Caribbean countries: empirical evidence on the role of public and private capital stock. Energy 118925

  64. Shahbaz M, Solarin SA, Sbia R, Bibi S (2015) Does energy intensity contribute to CO2 emissions? A trivariate analysis in selected African countries. Ecol Indic 50:215–224

    Article  Google Scholar 

  65. Shaozhou Q, Li K (2011) The Convergence analysis on the economic growth and energy intensity gap between regional sectors. Chinese J Popul Resour Environ 9(3):33–46

  66. Shi X, Yu J, Cheong TS (2020) Convergence and distribution dynamics of energy consumption among China’s households. Energy Policy 142:111496

    Article  Google Scholar 

  67. Solarin SA (2019) Parametric and non-parametric convergence analysis of electricity intensity in developed and developing countries. Environ Sci Pollut Res 26(9):8552–8574

    Article  Google Scholar 

  68. Sun JW (2002) The decrease in the difference of energy intensities between OECD countries from 1971 to 1998. Energy Policy 30(8):631–635

    Article  Google Scholar 

  69. Wan J, Baylis K, Mulder P (2015) Trade-facilitated technology spillovers in energy productivity convergence processes across EU countries. Energy Econ 48:253–264

    Article  Google Scholar 

  70. Wang Y, Gong X (2020) Does financial development have a non-linear impact on energy consumption? Evidence from 30 provinces in China. Energy Econ 104845

  71. Wu J, Wu Y, Cheong TS, Yu Y (2018) Distribution dynamics of energy intensity in Chinese cities. Appl Energy 211:875–889

    Article  Google Scholar 

  72. Xin-gang Z, Fan L (2019) Spatial distribution characteristics and convergence of China's regional energy intensity: An industrial transfer perspective. J Clean Prod 233:903–917

    Article  Google Scholar 

  73. Xu H, Gao J, Yao A, Yao C (2018) The effect of the energy convergence and energy dissipation on the formation of severe knock. Appl Energy 228:1243–1254

    Article  Google Scholar 

  74. Yu H (2012) The influential factors of China's regional energy intensity and its spatial linkages: 1988–2007. Energy Policy 45:583–593

  75. Yu Y, Zhang Y, Song F (2015) World energy intensity revisited: a cluster analysis. Appl Econ Lett 22(14):1158–1169

    Article  Google Scholar 

  76. Zhang D, Broadstock DC (2016) Club convergence in the energy intensity of China. Energy J 37(3)

  77. Zhang W, Pan X, Yan Y, Pan X (2017) Convergence analysis of regional energy efficiency in china based on large-dimensional panel data model. J Clean Prod 142:801–808

    Article  Google Scholar 

  78. Zhang P, Wang X, Zhang N, Wang Y (2019) China’s energy intensity target allocation needs improvement! Lessons from the convergence analysis of energy intensity across Chinese Provinces. J Clean Prod 223:610–619

    Article  Google Scholar 

  79. Zhu J, Lin B (2020) Convergence analysis of city-level energy intensity in China. Energy Policy 139:111357

Download references

Author information

Affiliations

Authors

Contributions

Conceptualization (Rouhollah Shahnazi), data curation (Zahra Dehghan Shabani), formal analysis (Zahra Dehghan Shabani and Rouhollah Shahnazi), investigation (Rouhollah Shahnazi and Zahra Dehghan Shabani), methodology (Zahra Dehghan Shabani), project administration (Zahra Dehghan Shabani), resources (Zahra Dehghan Shabani and Rouhollah Shahnazi), software (Zahra Dehghan Shabani), supervision (Zahra Dehghan Shabani), validation (Rouhollah Shahnazi), Visualization (Rouhollah Shahnazi and Zahra Dehghan Shabani), writing—original draft (Rouhollah Shahnazi and Zahra Dehghan Shabani), writing—review and editing (Rouhollah Shahnazi and Zahra Dehghan Shabani).

Corresponding author

Correspondence to Zahra Dehghan Shabani.

Ethics declarations

Ethics approval and consent to participate

Not applicable

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Responsible editor: Ilhan Ozturk

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Dehghan Shabani, Z., Shahnazi, R. Energy intensity convergence in Iranian provinces: evidence from energy carriers’ consumption intensity. Environ Sci Pollut Res (2021). https://doi.org/10.1007/s11356-021-12450-7

Download citation

Keywords

  • Energy intensity
  • Convergence
  • Markov chain method
  • Iran