This paper aims to identify the main determinants contributing to business cycles in Iran in short and long run. The paper tries to underpin the impulse response function of output to AGGREGATE supply and DEMAND shocks. We use annual data from 1959 to 2006 to decompose the cycles from trend, implementing band pass frequency method with the approach of Baxter and King. Then we use Engel and Granger causality test to determine the causality relation between AGGREGATE DEMAND cycles and real GDP, with and without oil. To determine the structural shocks threatening the Iranian economy, we use a Structural VAR with the restrictions imposed in Blanchard and Quah's study. The result of our study indicates that oil revenues are one of the most important factors contributing to business cycles in Iran.The results also suggest that the speed of adjustment of AGGREGATE output to structural AGGREGATE supply and DEMAND shocks varies depending on whether the shock originates from the supply or DEMAND side. The shocks last for four to five years if it originates from the supply side and lasts for six to seven years if it originates from the DEMAND side. In other words shocks originating from the DEMAND side last longer compared with the supply shocks. The structural variance decomposition of forecast errors suggests that most of changes in AGGREGATE output can be attributed to supply structural shocks, whereas most of changes in prices can be attributed to structural AGGREGATE DEMAND shocks.

Development of technology has made possible the invention of innovative and modern methods to solve partially the problems caused by traffic congestion, through decreasing the need for physical transportation; one such method being telecommuting. Although, research has been conducted to model employees’ and employers’ attitude towards telecommuting at micro level of a city, few predictions have been reported regarding its AGGREGATE DEMAND at the level of a city, generally because of the complexity and multi-dimensionality of the subject. In this paper, an approach for the estimation of potential telecommuting DEMAND is proposed and applied for the city of Tehran, using a 3-level generalization process to compensate for the incompleteness of the unattainable vast and expensive data. In the first level of the proposed approach, the matrix of average potential telecommuting DEMAND for 36 job categories defined by different organizational positions and 6 different organizational units, is derived from a 670-sized sample. In the second level, the data of 14 percent of the government employees are collected, in the third level, the geographic distribution of all governmental employees with telecommuting potential is determined. Result of this research regarding potential telecommuting DEMAND for the city of Tehran show that 53,898 out of 148,551 government employees are able to participate in telecommuting programs on a daily basis, removing 53,898 peak hour work trips on a daily basis. Although based on rather strong assumptions, forced by the limitation of data, the approach is implemented for Tehran.