structural vector auto regression model

The purpose of this article is to investigate the effects of monetary policy through monetary transmission channels (interest channel, exchange rate channel, credit channel and expectations channel) in the short and long term during the period 1386Q1-1396Q4. For this purpose, using the structural vector autoregression model of the effects Monetary policy was examined through channels. The experimental results obtained by estimating the relationships between variables using the SVAR approach based on statistical data show that in the short and long term, the exchange rate channel is the most effective channel in the transmission of monetary policy, so that the variable of expectations has both the most effect in the short term and long-term on this channel, after the exchange rate channel, there are expectations channel, and after that, credits and interest rate channel, which have the greatest impact in the short and long term, respectively.Finally, by examining the relative importance of monetary transfer channels to each other, it can be pointed out that with the passage of time, the influence of the channels will change, so that with price shocks, the expectations channel has the greatest impact in the short term, and the medium term of the effective money and the interest rate channel is effective in the long term.

Given the economic dependence of OPEC member countries, including Iran, on crude oil prices and export earnings, and considering the fact that one of the factors affecting crude oil prices is OPEC decisions, in this study, we investigate the impact of OPEC Summit Statements (increase, decrease and stabilization of production levels) focused on Iran's oil export earnings. Therefore, from the monthly data for the period 2018-1986 in the form of three quantities: West Texas crude oil prices are below $ 40 (Q-reg1), between $ 40 and $ 70 (Q-reg2) and above $ 70 (Q-). reg3) and Structural Vector Autoregressive Model (SVAR) were used in the quantile method. The results of the estimation of the instantaneous reaction functions (IRF) in the quintiles showed that the impact of Iranian oil export earnings on oil prices increased from $ 40 to $ 40 and then $ 70. Decreases. On the other hand, in quintiles of crude oil prices below $ 40, between $ 40 and $ 70 and above $ 70, first the shock caused by the statement declines, then the shock caused by the statement increases and finally, the shock caused by the level stability statement OPEC production affects Iran's oil export earnings. Also, as crude oil prices rise, the impact of these statements on Iran's oil earnings is diminished.

Basically, quantitative specification of sanction effects on economic sectors has undeniable importance to increase the buffering of nations’ economy against their negative effectsThis study examines the impacts of economic sanctions shocks through four indicators: (a) crude oil export revenue shock, (b) non-oil export shock, (c) raw material import shock, capital and intermediate goods, and exchange rate shocks on the construction sector in Iran. For this purpose, the research data were collected from the Central Bank of the Islamic Republic of Iran during the period 1996-1996. Also, structural vector autoregressive model (SVAR) and impulse resonse function (IRF) were used to analyze the data. Results showed that economic sanctions diminished the value added of the construction sector. However, the impact of the economic sanctions indicators examined on this section varies. Among the four indicators of economic sanctions under consideration, respectively: (a) exchange rate shocks; (b) raw material import shocks; intermediate goods and capital; (c) non-oil export shocks; and (d) oil export earnings shocks have the greatest negative impact on the value added of the construction sector.

Crude oil commercial stocks are one of the main components of the oil market, and its fluctuations are important in the analysis of the oil market. The purpose of this study is to investigate the unprecedented accumulation of crude oil commercial stocks according to structural shocks and convenience yield, since the onset of crude oil prices decline. In this study, the effect of structural shocks on fluctuations of crude oil commercial stocks was analyzed in the form of a structural vector auto regression model (SVAR) over the period from 2006 to 2016. Also, for the first time, convenience yield is calculated using the inverse problem method. This paper has two innovations. First, it is the first time that convenience yield is calculated in the oil market using the inverse problem method. Second, for the first time, the dynamics of crude oil commercial stocks are analyzed expanding Killian’s SVAR Model (2009).The results show that from late 2014 onwards, mostly crude oil supply shocks and crude oil inventory demand shocks have contributed to oil commercial accumulation. Also results show that WTI futures term structure (spread) has been in contango based on the negative net convenience yield since October 2014 and has led to accumulating more crude oil commercial stocks with speculative purposes.