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Considering multifaceted nature of "information", it has been introduced into different terminologies by the different researchers during the last three decades. In this article, we attempt to examine empirically the measurement of a sub-set of "information", namely “Primary information sectors (PIS)”, which requires the following factors: definition and conceptualization, methodology, Process of estimation, and data requirements. Based on the 99 sectors of input-output table derived from a 2002 version as well as the availability of the results from the 2002 manufacturing Census of the country; the size, importance, and scope of the PIS of Iran have been worked out. The results indicate that the shares of PIS in gross output, value added and final demand are 8, 10.2, and 8.6 percent respectively. However, these percents are relatively less than those shares found in the selected developed and developing countries over the 1960s, 1970s, 1980s, and 1990s.

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The 2006 census reveals that more than 50% of employed population in Iran is not involved in the production of food, clothing, housing and other tangible goods. Apart from the serious reservation of industrialization in Iran, this can be considered as one of the indications of a new phase shift known as “service economy”. To analyze such a post-industrialization economy, it requires new concepts and classifications which, to our knowledge, have been ignored by researchers mainly in Iran. The main objective of this paper is to measure and identify the domain of the fourth sector and its structural analysis in the framework of input-output and semi-social accounting matrix models. Using 2001 input-output data, the overall results show that the fourth sector appears to be oriented as a consumption goods sector compared to the other sectors. Consequently, the consumption-induced effect ploys a significant role in rising production, income and employment.

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The statistical data of Tehran Province shows that the ratios of output and employment of service sector to total provincial output and employment are 57 and 63 percent in 2001, respectively. The aim of this article is to quantitatively explain the structure of service –based economy of province, using Input-Output Model and intersectional linkages by Eigen Vector method. So, the main question in this research is that can the usage of Eigen vector method rather than traditional methods like Chenery-Watanabe and Rasmussen methods evaluate more precisely the importance of provincial economic sectors on the basis of intermediate viability in the production process?     For this purpose, first the Input-Output Table of “Tehran Province” for 2001 was estimated by AFLQ method, and then the importance of provincial economic sectors was measured in terms of forward and backward linkages by Chenery-Watanabe, Rasmussen and Eigen vector methods.     The results show that Eigen Vector Method can explain the importance of economic sectors of province on the basis of intermediate viability in the production process, in such a way that four key sectors are of dominant shares in industrial activities which their average share of demand out of total output is 45.5 percent, but ratios for 71 economic and service sectors are 76 percent and 84 percent, respectively. In general, results show that the nature of service sector in Tehran province is different from the services in modern economies. The main reason is that the service sector in Tehran is the consuming rather than producing sector.

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The implementation of any economic policy that has expansionary effects requires relatively stable economic conditions. Under such conditions it is expected that potential predictable effects of such policy implementation on welfare of households, especially low income households could be evaluated. The economic context of poverty in the Iranian economy and the ineffectiveness of supportive institutions in particular circumstances make the effects of economic policies on low-income households widespread. In some cases, these effects are so broad that policy-makers are forced to leave or select the opposite course of that policy. Under these conditions, analyzes that illustrate the effectiveness path of policy help the policy-maker to have a clearer picture of the probable consequences of a policy. The main aim of this article is to analyze quantitatively the effects of the recent subsidy targeting policy on the welfare index (cost of living index) in different deciles of urban and rural households using social accounting matrix (SAM) approach. For this purpose two updated social accounting matrices for the years 2009 and 2011 have been used. Both matrices include 40 economic sectors. Comparing the cost of living index, we find that welfare vulnerability of households has decreased in general, however the magnitude of welfare reduction differs between rural and urban households among income deciles. Our findings reveal that the cost of living index of rural households is more than the corresponding urban households. The vulnerability in the natural gas distribution sector has tripled in urban areas in 2011and in rural areas it is nearly four times higher than 2009 level. We also find that every 100-unit increase in cost of electricity will potentially increase welfare index of urban and rural household by 34 and 46 units, respectively. From the distribution viewpoint, the welfare loss is lower for high-income deciles. In addition, our findings show that the degree of vulnerability in middle income groups in majority of sectors is less than the other income groups. The structural path of changes shows that subsidy targeting has created wide complexity and entanglement in the path of the effectiveness of fuel price changes on price indices, especially on the household living cost index. Accordingly, before implementing subsidy targeting scheme, the increase in fuel prices was influencing the household cost index in five ways, while after targeting the increase in fuel prices affected it through the twenty different paths. 

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