Investigating the Effect of Energy Return on the Value Added of Agricultural Sector in Iran

Document Type : Research Paper

Authors

1 Graduate MSc., Department of Agricultural Economics, Faculty of Agriculture, Shahid Bahonar University, University of Kerman, Kerman, Iran

2 Professor, Department of Agricultural Economics, Faculty of Agriculture, Shahid Bahonar University, University of Kerman, Kerman, Iran

Abstract

Considering energy rebound effect, real energy savings are determined by the efficiency of resources. otherwise, creation an unrealistic place occur Economic analysis and planning. Therefore, the results of the policies applied are not desirable. In this paper, energy rebound effect of agricultural sectors was estimated in two models, with Divisia index and signification coefficient of fix effect Panel model, Cobb-Douglas function showed  positive effect energy consumption of agricultural sub-sectors on agriculture Value Added during 1996–2015, by least square method. The energy decomposition results of Divisia index method confirm energy intensity as the most effective factor in increasing energy consumption. energy  rebound effect in two models decreasing trend respectively with an average annual 19.38%  and 16.99% ,i.e., an average with 80.62%  and 83.01% saved expected energy savings. Given that effect energy intensity  the most important factor on increasing energy consumption in the agricultural sectors and after planning subsidies down trend energy rebound effect has decreased, therefore planning and policy making In efficiency and energy  rebound effect must do more attention.  

Keywords

References

  1. Ackerberg, D., Benkard, C. L., Berry, S., & Pakes, A. (2007). Econometric tools for analyzing market outcomes. Handbook of econometrics, 6, 4171-4276.‏
  2. Bakhshahyesh, M., & Yazdani, S. (2015). Estimation of energy demand function in agricultural sector of Iran. Iranian Journal of Agricultural Economics and Development Research, 46(2), 327-334. (in Persian)
  3. Berkhout, P. H., Muskens, J. C., & Velthuijsen, J. W. (2000). Defining the rebound effect. Journal of Energy policy, 28(6-7), 425-432.‏
  4. Deilami Nejad, R., & Ostad Hossein, R. (2010).The Relationship Between Energy Consumption and Output in the Economic Sectors in Iran. Journal of Economic Research and Policies. 18(55):3, 125-140. (in Persian)
  5. Esmaeili, A., & Fathi, F. (2012). Relationship between Energy Consumption, Income and Carbon Dioxides Emission in Iran. Iranian Journal of Agricultural Economics and Development Research, 43(2), 175-181. (in Persian)
  6. Ekhtiari Nikjeh, S. (2011). A Study to Evaluate the Rebound Effect for Motor Vehicle Travel. M. A Thesis On Energy Economics. Economics & Accounting-Department of Energy Economics. ISLAMIC AZAD UNIVERSITY of Tehran. (in Persian)
  7. Fazlzadeh, A., & Tajvidi, M. (2008).Energy Management in Iranian Industries: A Case Study: The causal relationship between the amount of electricity consumed and the value added of small industries (SSI), 10-49 employees. Quarterly Journal of Energy Economics Review. 5(19):147-162. (in Persian)
  8. Khoshkalam Khosroshahi, M. (2015). The recurrence effects of economic sectors and households as a result of improving the efficiency of gasoline consumption. Quarterly Journal of Economic Research and Policy. 20(74): 31-54. (in Persian)
  9. Lin, B., & Du, K. (2015). Measuring energy rebound effect in the Chinese economy: an economic accounting approach. Journal of Energy economics, 50, 96-104.‏

10. Manzour, D., Aghababa'I, M. A., & Haghighi, I. (2011).Analysis of the recurrence effects of improving the efficiency of electricity consumption in Iran: Computable general equilibrium pattern. Quarterly Journal of Energy Economics Review. 8(28):1-23. (in Persian)

11. Mundlak, Y. (1961). Empirical production function free of management bias. Journal of Farm Economics, 43(1), 44-56.‏

12. Shao, S., Huang, T., & Yang, L. (2014). Using latent variable approach to estimate China׳ s economy-wide energy rebound effect over 1954–2010. Journal of Energy Policy, 72, 235-248.‏

13. Wei, T. (2007). Impact of energy efficiency gains on output and energy use with Cobb–Douglas production function. Journal of Energy Policy, 35(4), 2023-2030.‏

14. Wei, T., & Liu, Y. (2016). Estimation of resource-specific technological change in a production function.‏ Journal of  Economic, 70(1): 65-94.

15. Yazdani, S,. Taheri Reikandeh, I,. Mohammadian, F,. Norouzi, H. (2018). Diversity of activity, Strategies to Promote Energy Productivity in Agriculture (Causality analytical approaches Toda - Yamamoto and Bounds test). Iranian Journal of Agricultural Economics and Development Research, 48(4), 547-556. (in Persian)

16. Zhang, Y. J., Peng, H. R., & Su, B. (2017). Energy rebound effect in China's Industry: An aggregate and disaggregate analysis. Journal of Energy Economics, 61, 199-208.‏

17. Zibaei, M. H., & Akhoond-Ali, A. M. (2017). The Rebound Effect or Jevons Paradox: A Concept for More Proper Understanding of the Consequences of Improvements in Water Productivity. Journal of JWSS-Isfahan University of Technology, 20(78), 157-170. (in Persian)

Iranian Journal of Agricultural Economics and Development Research
Volume 49, Issue 4
November 2018
Pages 651-659

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