Volume 24, Issue 1 (Spring 2019)
JPBUD 2019, 24(1): 3-24 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Azizi Z. (2019). The Effect of Economic Complexity on Energy Consumption in the Industrial Sector. JPBUD. 24(1), 3-24. doi:10.29252/jpbud.24.1.3
URL: http://jpbud.ir/article-1-1799-en.html
URL: http://jpbud.ir/article-1-1799-en.html
Assistant Professor, Faculty of Social Sciences and Economics, Alzahra University, Tehran, Iran. , z.azizi@alzahra.ac.ir
Abstract: (3881 Views)
The relationship between technology and energy consumption is one of the most challenging issues in the field of energy policy. Various studies have investigated this relationship but did not come up with the same results. In this paper, using the economic
complexity index, this relationship is evaluated for energy consumption in the industrial sector of Iran for the period 1971-2016. The findings show that the increasing complexity of the economy has led to an increase in energy consumption in the industrial sector, which can be due to two reasons: first, the rebound effects of technology, and second, the transfer of production to the industrial sector due to the change in the structure of production towards technological goods. On the other hand, as regards the cross-effects, economic complexity has reduced the positive coefficient of income, which indicates that with higher technology, increase in production, will increase energy consumption to a lesser extent. Consequently, from this perspective, economic complexity can lead to positive results in energy consumption in the industrial sector.
complexity index, this relationship is evaluated for energy consumption in the industrial sector of Iran for the period 1971-2016. The findings show that the increasing complexity of the economy has led to an increase in energy consumption in the industrial sector, which can be due to two reasons: first, the rebound effects of technology, and second, the transfer of production to the industrial sector due to the change in the structure of production towards technological goods. On the other hand, as regards the cross-effects, economic complexity has reduced the positive coefficient of income, which indicates that with higher technology, increase in production, will increase energy consumption to a lesser extent. Consequently, from this perspective, economic complexity can lead to positive results in energy consumption in the industrial sector.
Keywords: Economic Complexity, Improvement of Technology, Energy Consumption, Rebound Effects, Industrial Sector.
Type of Study: Research |
Received: Jun 23 2019 | Accepted: Jan 10 2020 | ePublished: Jun 10 2020
Received: Jun 23 2019 | Accepted: Jan 10 2020 | ePublished: Jun 10 2020
References
1. Acs, Z. J., Anselin, L., & Varga, A. (2002). Patents and Innovation Counts as Measures of Regional Production of New Knowledge. Research Policy, 31(7), 1069-1085. [DOI:10.1016/S0048-7333(01)00184-6]
2. Ang, J. B. (2009). CO2 Emissions, Research and Technology Transfer in China. Ecological Economics, 68(10), 2658-2665. [DOI:10.1016/j.ecolecon.2009.05.002]
3. Basu, S., & Fernald, J. (2007). Information and Communications Technology as a General-Purpose Technology: Evidence from US Industry Data. German Economic Review, 8(2), 146-173. [DOI:10.1111/j.1468-0475.2007.00402.x]
4. Bayat, T., Kayhan, S., & Senturk, M. (2017). Is There Any Asymmetry in Causality between Economic Growth and Energy Consumption? Journal of Economic Cooperation & Development, 38(4), 77-93.
5. Bhattacharyya, S. C. (2011). Energy Economics: Concepts, Issues, Markets and Governance: Springer.
6. Can, M., & Gozgor, G. (2017). The Impact of Economic Complexity on Carbon Emissions: Evidence from France. Environmental Science and Pollution Research, 24(19), 16364-16370. [DOI:10.1007/s11356-017-9219-7]
7. Cohen, W. M., & Klepper, S. (1991). Firm Size versus Diversity in the Achievement of Technological in Z.J. Acs and D.B. Audretsch (eds) Innovation and Technological Change: An International Comparison, Ann Arbor, MI: University of Michigan Press, 183-203.
8. Crafts, N. (2003). Quantifying the Contribution of Technological Change to Economic Growth in Different Eras: A Review of the Evidence. Economic History Working Papers, 22350.
9. Dargahi, H., & Khameneh, K. B. (2019). Energy Intensity Determinants in an Energy-Exporting Developing Economy: Case of Iran. Energy, 168(1), 1031-1044. [DOI:10.1016/j.energy.2018.12.015]
10. Farid Ghaderi, S., Azadeh, M., & Mohammadzadeh, S. (2006). Electricity Demand Function for the Industries of Iran. Information Technology Journal, 5(3), 401-404. [DOI:10.3923/itj.2006.401.404]
11. Fei, Q., Rasiah, R., & Shen, L. J. (2014). The Clean Energy-Growth Nexus with CO2 Emissions and Technological Innovation in Norway and New Zealand. Energy & Environment, 25(8), 1323-1344. [DOI:10.1260/0958-305X.25.8.1323]
12. Griliches, Z. (1998). Patent Statistics as Economic Indicators: A Survey R&D and Productivity: The Econometric Evidence (287-343): University of Chicago Press.
13. Hausmann, R., Hidalgo, C. A., Bustos, S., Coscia, M., Simoes, A., & Yildirim, M. A. (2014). The Atlas of Economic Complexity: Mapping Paths to Prosperity: MIT Press. [DOI:10.7551/mitpress/9647.001.0001]
14. Hidalgo, C. A., & Hausmann, R. (2009). The Building Blocks of Economic Complexity. Proceedings of the National Academy of Sciences, 106(26), 10570-10575. [DOI:10.1073/pnas.0900943106]
15. Irandoust, M. (2016). The Renewable Energy-Growth Nexus with Carbon Emissions and Technological Innovation: Evidence from the Nordic countries. Ecological Indicators, 69 (1), 118-125. [DOI:10.1016/j.ecolind.2016.03.051]
16. Jacobsen, H. K. (2001). Technological Progress and Long-Term Energy Demand-A Survey of Recent Approaches and a Danish Case. Energy Policy, 29(2), 147-157. [DOI:10.1016/S0301-4215(00)00111-7]
17. Jevons, W. S. (1866). The Coal Question; An Inquiry Concerning the Progress of the Nation, and the Probable Exhaustion of our Coal-Mines. Fortnightly, 6(34), 505-507.
18. Jin, L., Duan, K., & Tang, X. (2018). What is the Relationship between Technological Innovation and Energy Consumption? Empirical Analysis Based on Provincial Panel Data from China. Sustainability, 10(1), 145-158. [DOI:10.3390/su10010145]
19. Kani, A., Abbaspour, M., & Abedi, Z. (2013). Estimation of Natural Gas Demand in Industry Sector of Iran: A Nonlinear Approach. International Journal of Economics and Finance, 5(9), 148-155. [DOI:10.5539/ijef.v5n9p148]
20. Keller, W. (2002). Geographic Localization of International Technology Diffusion. American Economic Review, 92(1), 120-142. [DOI:10.1257/000282802760015630]
21. Khan, A., & Ahmed, U. (2009). Energy Demand in Pakistan: A Disaggregate Analysis, Pakistan Institute of Development Economics, Islamabad.
22. Komen, M. H., Gerking, S., & Folmer, H. (1997). Income and Environmental R&D: Empirical Evidence from OECD Countries. Environment and Development Economics, 2(4), 505-515. [DOI:10.1017/S1355770X97000272]
23. Ladu, M. G., & Meleddu, M. (2014). Is There Any Relationship between Energy and TFP (Total Factor Productivity)? A Panel Cointegration Approach for Italian Regions. Energy, 75(1), 560-567. [DOI:10.1016/j.energy.2014.08.018]
24. Li, K., & Lin, B. (2014). The Nonlinear Impacts of Industrial Structure on China's Energy Intensity. Energy, 69(1), 258-265. [DOI:10.1016/j.energy.2014.02.106]
25. Lin, B., & Du, K. (2015). Measuring Energy Rebound Effect in the Chinese Economy: An Economic Accounting Approach. Energy Economics, 50(1), 96-104. [DOI:10.1016/j.eneco.2015.04.014]
26. Ma, H., Oxley, L., & Gibson, J. (2009). Substitution Possibilities and Determinants of Energy Intensity for China. Energy Policy, 37(5), 1793-1804. [DOI:10.1016/j.enpol.2009.01.017]
27. Neagu, O., & Teodoru, M. C. (2019). The Relationship between Economic Complexity, Energy Consumption Structure and Greenhouse Gas Emission: Heterogeneous Panel Evidence from the EU Countries. Sustainability, 11(2), 497-526. [DOI:10.3390/su11020497]
28. Sweet, C. M., & Maggio, D. S. E. (2015). Do Stronger Intellectual Property Rights Increase Innovation? World Development, 66(1), 665-677. [DOI:10.1016/j.worlddev.2014.08.025]
29. Tang, C. F., & Tan, E. C. (2013). Exploring the Nexus of Electricity Consumption, Economic Growth, Energy Prices and Technology Innovation in Malaysia. Applied Energy, 104(1), 297-305. [DOI:10.1016/j.apenergy.2012.10.061]
30. Weixian, W., & Fang, Y. (2010). Impact of Technology Advance on Carbon Dioxide Emission in China [J]. Statistical Research, 7(7), 36-44.
31. Yuan, C., Liu, S., & Wu, J. (2009). Research on Energy-Saving Effect of Technological Progress Based on Cobb-Douglas Production Function. Energy Policy, 37(8), 2842-2846. [DOI:10.1016/j.enpol.2009.04.025]
| Rights and permissions | |
.jpg) |
This work is licensed under a Creative Commons Attribution 4.0 International License. |
