Iranian Economic Review (10266542)25(3)pp. 397-417
Iran has faced oil and banking sanctions since 2012. Following the sanctions and instability of the exchange rates, the Rial has sharply lost its value. Rising economic unrest has widened the gap between the official exchange rate and parallel market rate. However, the depreciation of Iran’s Rial does not show a uniform trend, and the decline path has been complicated. We know that sanctions against Iran have created new expectations, concerns, and attention. Google Trends has provided an analytic tool for measuring and monitoring people’s expectations based on their Internet search data. This study attempted to analyze and model the exchange rate trends in Iran using sanctions-related expectations extracted from Google Trends. The Google search index (GSI) of the sanctions demonstrated the agent’s expectations. Monthly data and the autoregressive distributed lag (ARDL) method were used for estimation. The results indicated a significant and positive impact of GSI on the unofficial exchange rate (UER) and just a positive impact on the real unofficial exchange rate (RUER). We can conclude that the effects of sanctions appear partly through changes in people’s expectations that can be extracted using GSI. Moreover, the difference in inflation showed a significant positive effect on the market exchange rate in Iran. Thus, an improvement in the expectations through reducing the international tensions and a perspective shift can strengthen the Rial exchange rate. Moreover, the policymaker can control the volatility and depreciation of the exchange rates in Iran by restricting the M2 growth through an appropriate long-run monetary policy. © University of Tehran.
International Journal Of Energy Economics And Policy (21464553)9(5)pp. 433-441
Regional energy planning under uncertainty is an important concept in energy-economy models which makes the planning outcomes closer to reality and enables the decision maker to select the best decision. Reliability of local energy supply and the possibility of long-term access to resources and emissions reduction is an essential step. In this study, an urban energy demand which is supplied by electricity network is investigated with an optimal combination of alternative energy resources such as solar, wind and natural gas during the next 10 years. The optimal combination of fossil energy as well as renewable energies are determined by goal stochastic programming model. Isfahan province in Iran has been selected as a case study. Empirical results indicate that due to the importance of investment and operation costs, the dominant share of energy supply will belong to natural gas, while the shares of solar and wind energies remain constant in the next decade. In sum, the share of solar and wind energies increases by 8% in 10 years and therefore, it is not necessary to increase electricity supply by the network in order to meet annual increasing demand. CO2 and NOx emissions will decrease significantly. © 2019, Econjournals. All rights reserved.
Applied Econometrics and International Development (15784487)15(1)pp. 143-160
This case study estimated an electricity demand function for industrial sector of Iran by applying the structural time series technique to quarterly data for 2000q1-2011q4. In addition to identifying the size and significance of the price and output elasticities, this technique also uncovers UEDT. It is found that the estimated long-run and short-run industrial output elasticities are respectively, 0.85 and 0.36 and the estimated long-run and short-run industrial energy price elasticities are -0.47 and -0.27, respectively. The results suggest that the nature of the trend is not linear and deterministic but stochastic in form. The UEDT for the electricity usage of the industrial sector shows an upward slope.
