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Showing 3 results for Factor Analysis
Assessment of International Sanctions on Iranian Macroeconomic Variables
Dr Alireza Garshasbi, Mr Mojtaba Yusefi,
Volume 7, Issue 25 (10-2016)
Abstract
Legal and economic dimensions of sanctions, and also its diversity make it difficult to evaluate the contribution of the sanctions on macroeconomic variables; besides quantification of sanction by itself is a major problem. As the first step in this study, we try to offer a new index for representing the sanction in economic modeling. For this purpose by applying the exploratory factor analysis approach, we try to measure the mentioned index and produce the time series for the period of 1978-2010; here twelve variables which are mainly affected by the sanctions included in related process. Then, applying three-stage least squares (3SLS) method for a small macroeconomic model, the contribution of the sanctions on major economic variables such as economic growth, trade, investment and employment are evaluated. According to the findings of this study, the direct effects of sanctions are only significant in growth and term of trade equations. It seems also that there is a direct relationship between severity of the sanctions and its impact on major economic variables.
Comparative Analysis of the Economic Factors and Technical Factors in Improving Energy Efficiency in the Iranian Household Sector
Mahdi Sadeghi, Mahdi Khoshkhooy,
Volume 8, Issue 27 (3-2017)
Abstract

Today one of the basic conditions for economic development in one country, is the high performance of energy sources used in different sections of the country economy. When the efficiency is raised, one of essential requirements is benefit from technologies and equipments with higher technical and performance specifications, and removing economic barriers or improving economic policies, in order to achieve as higher efficiency as possible in energy consumption. Considering that close to half of the our country energy consumption accounted for households and this sector is the largest consumer of energy in the country, and considering the importance of the issue of energy consumption, in this study we decided to analyze and scrutiny the phenomenon of energy efficiency in the household sector, and to achieve accurate and scientific analysis in this area based on expert opinion data, using structural equations modeling technique in LISREL. Based on the result of the model, economic policies (price and none price) has relatively more importance than the technical and technological solutions to the problem of improving energy efficiency in the household sector, as well as important and effective indices of each of these factors are extracted and identified. According to it, "levy a tax on energy consumption" among economic policies, and indicators of "e-government infrastructure development", "development of smart counters and Equipments WARNING energy consumption in homes" and "development of vernacular architecture patterns adapted to climatic conditions in different regions of the country" in connection with Technical foctors, have the greatest impact on energy efficiency in the mentioned sector. However, if the relationship identified for both the economic policies and technical-technological factors with the dependent variable "performance" was not acceptable very good, this matter can indicate this fact that there are other variables and factors that are influencing and can have a great role to play. Among these factors it can be addressed the socio-cultural factors and insights and norms of society which can be a help to aggravate the problem of inefficiency in energy use.


Using Clustering and Factor Analysis in Cross Section Analysis Based on Economic-Environment Factors
Vahid Majed, Hossein Mirshojaeian Hosseini , Samira Riazi ِdoust,
Volume 10, Issue 35 (3-2019)
Abstract
Homogeneity of groups in studies those use cross section and multi-level data is important. Most studies in economics especially panel data analysis need some kinds of homogeneity to ensure validity of results. This paper represents the methods known as clustering and homogenization of groups in cross section studies based on enviro-economics components. For this, a sample of 92 countries which produce the most greenhouse gases including CO2, clustered based on 18 criteria. Those criteria reduced to five primary components using factor analysis. Clustering of countries done by HCPC (Hierarchical Clustering on Principal Component) method. All 92 countries were clustered in 7 different groups. For each group properties of countries indicates the homogeneity of each cluster. In cross section analysis with many sections, especially analysis based on panel data, clustering, increases assurance of expected homogeneity and validity of result.

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