Spatial Analysis of the Affecting Factors on Housing Prices in Tehran Metropolis

Among the different areas of Tehran, the distinctive and colorful role of several thriving and high-income areas in the north with high volume of construction and sales, the role of price drivers as the first hypothesis of the present study and factors affecting the level of demand and supply. This research is applied in terms of purpose and descriptive-analytical in terms of method. In this research, using spatial statistics technique in Arc GIS environment, the subject was analyzed and studied. To extract the data used in this section from the statistics and information of the Statistics Center of the country and studies of detailed plans of regions (urban land use) as well as reports of the Central Bank of the Islamic Republic of Iran, General Directorate of Economic Statistics (2006-2017), economic and social situation report. The results of the study of construction activities in urban areas of Tehran and the results of statistics on the cost and income of urban households and the authors' calculations and its conversion into cross-sectional data have been used. According to the results of Moran test, the existence of spatial effects on the difference in housing prices in the 22 districts of Tehran metropolis with three factors of distance, degree of concentration and topographic factor is confirmed at a high level of significance. According to the results of the spatial autocorrelation coefficient, the price fluctuation shock in one area has spread to other areas of Tehran metropolis. In other words, in spatial autocorrelation coefficient, among 521556 residential land use units in the neighborhoods and areas of Tehran metropolis, its price fluctuation and amplitude is strongly a function of the topography and stereotype of Balashahr-Paeinshahr in the popular literature of urban economics. So that among the 374 neighborhoods surveyed in the 22 regions of regions 1, 3, 2, 6, 5 and 4, the highest housing prices and regions 12, 15, 18, 11 and 16 have the lowest range of fluctuations and the lowest housing prices in the decade. Experimented 85-95.