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Showing 3 results for Ardl Model

Rahim Dallali Esfahani, Said Samadi, Mohammad Mahdi Mojahedi, Amir Jabbari, Reza Samadi Boroujeni,
Volume 3, Issue 7 (3-2012)
Abstract

    This paper examines the effects of different variables on inflation in the monetary economics using endogenous growth models. So, different aspects of inflation formation were analyzed based on micro-foundations. We investigated the role of imported inflation, fiat money, expectations, monetary base and capital accumulation on inflation using an endogenous growth model. An ARDL approach was utilized to estimate the model for Iranian economy during 1979 -2008. The estimation results show that imported inflation affects the inflation through the exchange rate channel. Also, expectations, capital return and monetary base play an outstanding role in Iranian economy.

 


Mohammad Sarrafi Zanjani, Nader Mehregan,
Volume 9, Issue 33 (10-2018)
Abstract

Studying currency shocks impact on the stock market could be beneficial regarding to exchange rate fluctuations caused by various exchange policies in recent years. Therefore symmetrical or asymmetrical impacts of negative and positive dollar shockwaves in the market on indexes of chemical and basic metals industry are under investigation by weekly data collected since 2006 up to 2016 as these two industries have the most non-oil exports of Iran. First existence of long-term equilibrium relationship was examined by Pesaran Bound test and confirmed. Afterwards in addition to admitting asymmetric effect of positive and negative foreign exchange shocks on the indexes using WALD test, based on the results of the main model of the research which is the Nonlinear Autoregressive Distributed Lag (NARDL), effects of increasing in dollar rate on both indexes are positive and meaningful and the effect of its decreasing is meaningless. In addition the extracted coefficients indicates deeper effects of free dollar rate on the chemical index in comparison with index of the basic metals. OPEC crude oil, which is the control variable considered in this article has a direct and significant effects on both indicators on the short and long term.

Mr Hossein Hafezi, Mr Siab Mamipour,
Volume 13, Issue 49 (12-2022)
Abstract

Climate change has emerged as a significant global challenge, with its impact increasing rapidly in recent decades. The consumption of fossil fuels, which leads to the emission of greenhouse gases like CO2, is a major contributor to climate change. Iran, ranked as the sixth most polluted country in the world, emitted a staggering 745 million tons of CO2 in 2020. Notably, the power plants sector in Iran accounts for roughly 30% of its total carbon emissions. As a result, the main objective of this paper is to engage in long-term planning for electricity supply and demand in Iran, aiming to reduce carbon emissions in line with the country's obligations under the Paris Agreement. To achieve this goal, we utilized the MESSAGE model to design an electricity generation system that takes into account the potential of renewable sources from 2021 to 2050. Additionally, the ARDL model was employed to estimate electricity demand under various scenarios, including subsidy reforms. These predictions were then incorporated into the long-term planning process for Iran's electricity supply system. The findings of the ARDL model highlight that the subsidy reform strategy leads to a 10% decrease in electricity demand throughout the planning period, indicating effective control over the demand side. On the other hand, the MESSAGE model's findings reveal that Iran's ability to fulfill its responsibilities under the Paris Agreement heavily relies on the utilization of renewable potentials across different regions in power supply planning. While carbon dioxide emissions in Iran's electrical sector are not expected to be reduced in the near future (2020 to 2030). However, in the long term (2040 to 2050), significant reductions in CO2 emissions can be achieved. According to the findings, if the electricity system in Iran is designed in accordance with a chosen scenario that incorporates green technologies and subsidy reforms, the share of renewable technologies can increase from 6% in 2020 to 15%, 50%, and 78% in 2030, 2040, and 2050, respectively. Consequently, carbon emissions in the power generation sector can be reduced by 20% and 54% in 2040 and 2050, respectively, compared to 2020 levels.


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