Journal of Economic Modeling Research

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The characterization of memory effects in crude oil markets is an interesting issue that has attracted the attention of researchers from different disciplines, from econophysics to more classical economics. The importance of the problem relies in the fact that the departure from uncorrelated behavior would imply the presence of not-random effects which, in principle, can be exploited for arbitrage. This paper tries to contribute into the issue by estimating the memory effects by means of different parametric, semi-parametric, and non-parametric methods. In the other words, this paper provides analysis on the memory of the oil markets measured via the fractional integration parameter (d) by estimating it with various methods such as the MLE, NLS, GPH, Whittle, Lo, Hurst Exponent and Wavelet. To achieve this goal, we use the daily time series for WTI and Brent spot crude oil prices as well as 3-month futures, and further divide them into yearly subsections to obtain the historical series of memories. Results of the whittle and wavelet estimations, which are better suitted for this analysis, show no evidence of a long memory process. However, the oil price time series exhibits a nonstationary mean-reverting behaviour. Note that in this paper the behaviour of memory is our concern instead of the memory value itself. The results of memory changes trend shows that memory of international oil markets does not have an important trend change. In the other words, in our study period the efficiency of the market does not have an important decline or increase.

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This paper tries to model the electricity demand in Iran’s industrial sector which captures economic factors and also non-economic exogenous factors. The structural time series model (STSM) approach is employed which allows using economic theory and time series flexibility. In this approach the role of UEDT (Underlying Energy Demand Trend) including technological improvement and structural changes is modeled, therefore the income and price elasticity are estimated more accurately. The results show that the UEDT has the stochastic nature. And UEDT has a great impact on industrial energy demand during 1975-2012. So, the electricity has not been used efficiently in this sector. In the short run the estimation of the income and price elasticity are 0.42 and 0.11 respectively. The value of the cross-price elasticity of electricity demand is estimated about 0.06. It shows that natural gas substitute electricity in industrial sector, however it is small.

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Exchange rate is one of the key indicators affecting macroeconomic performance, and inflation is one of the most important indicators which represents the macroeconomic performance. The aim of this paper is to identify the relation between these two important economic variables. By using the model of structural time series and Kalman Filter algorithm the effect of exchange rate gap (the difference between official exchange rate and parallel market exchange rate) on inflation in Iran has been investigated during 1961- 2012. The results of this paper indicate that exchange rate gap has a significant positive impact on inflation in Iran, so that 1 percent increase in exchange rate gap lead to 3 percent increase in inflation in Iran.  These results have approved the single currency policy to control inflation in the country.

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In this study, we estimate the demand for natural gas in the subsection manufacture of basic metals of Iran using structural time series model (STSM) over the period of time 1981-2013. Such model contains unobservable elements which have been transported to state space model with the use of kalman filter and is estimated by implementing maximum likelihood approach. Also, because the Targeting of Subsidies Plan was approved by the Iranian parliament at the end of 2010, so we evaluate the role of this plan on energy demand of industrial subsectors. Finding of the research is that, first of all the nature of the trend is smooth one. Secondly, it is changing on a nonlinear basis. The estimated demand function shows that price elasticity for natural gas in the long and short run, correspondingly, are (-0.30) and (-0.79) and production elasticities of natural gas in the short and long run, correspondingly, are (0.17) and (0.38). Furthermore, Cross elasticity for electricity and gasoline in the long and short run, correspondingly, are substitute and complementary goods. In addition, the result of evaluating effect of the Targeting of Subsidies Plan show that estimated natural gas demand functions can explain the impact of this policy.