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Investigation on the Impact of an Energy Desubsidization Shock on the General Price Index Via a Nonlinear Inflation Model: Case of Iran

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  • Asghar Shahmoradi

    (Faculty of Economics, University of Tehran, Tehran, Iran)

  • Hamed Shakouri

    (Department of Industrial Engineering, University of Tehran, Tehran, Iran)

Abstract

For decades, energy prices have been controlled by the government in Iran. This policy had a long lasting impact on almost all economic variables in Iran. To date, under tremendous pressure to adequately meet the huge domestic demands for energy inputs, the government has decided to reduce/eliminate the energy subsidies. Thus, its impact on the consumer price index is unavoidable. This paper investigates the dynamics of that impact via a dynamic nonlinear inflation model. It is shown that an increasing shock in fuel price has less increasing effect on the general price index, compared to the steady state effect of a continuously increasing signal. Based on this fact, it is deduced that other factors, e.g. the Money Supply Growth and the Goods Market Gap, has much more impact on the inflation. Therefore, unsubsidizing energy price, particularly fuel, will empower the government to save more money and avoid expansionary monetary policies. The currency not used for subsidizing fuel price can help to decrease the money supply growth, and contribute subsidence of extremely growing inflation due to the money gap.

Suggested Citation

  • Asghar Shahmoradi & Hamed Shakouri, 2010. "Investigation on the Impact of an Energy Desubsidization Shock on the General Price Index Via a Nonlinear Inflation Model: Case of Iran," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 15(3), pages 33-51, fall.
  • Handle: RePEc:eut:journl:v:15:y:2010:i:3:p:33
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    References listed on IDEAS

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    1. Durevall, Dick & Ndung'u, Njuguna S., 1998. "A Dynamic Model of Inflation for Kenya 1974 - 1996," Working Papers in Economics 7, University of Gothenburg, Department of Economics.
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    Cited by:

    1. Seyed Azad Nabavi & Alireza Aslani & Martha A. Zaidan & Majid Zandi & Sahar Mohammadi & Naser Hossein Motlagh, 2020. "Machine Learning Modeling for Energy Consumption of Residential and Commercial Sectors," Energies, MDPI, vol. 13(19), pages 1-22, October.

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