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Few studies have recently supported the preposition that housing price changes in one location can be affected not only by its history but also by housing price changes in other locations (Ripple effect). There are many reasons why housing price changes in some areas may lead housing price movements in the other areas. The possible causes include structural differences and economic interdependence between areas, migration as well as informational factors. This paper examines spatial effects of house price dynamics within Tehran. The first hypothese is that house prices have started rising first in the north and then spread out over the rest of the city. The second hypothesis is that there is a strong price relationship between contiguous districts. Spatial autoregressive (SAR) and vector error-correction (VEC) models are emplyed to estimate the empirical models using quarterly panel data of Tehran housing markets over the period 1991 to 2006. The results confirms that there is a positive spatial interrelationship among districts. Moreover, the findings indicate the evidence of leading role of the district 1 in the northern half of the city while district 2 seems to have a more prominent effect on the center and the west. Furtheremore, the price interdependence of contiguous districts in the north is seen to be more significant and stronger than the south.

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The purpose of this paper is to examine the relationship between bank loan rate and housing prices in Iran. For this purpose, some VAR models have been applied, using the following variables: real loan rate, money supply (including the high powered money and the liquidity), GDP, housing services index, and the number of licenses for new houses. The results show that a reduction in the loan interest rate will increase the demand for housing sector because of reduction in cost of borrowing from banking system in order to invest in this sector. In other word, the research findings have implied a negative relationship between bank loan interest rates and housing prices. The results have also revealed that financial repression in the form of bank loan rates control policy induces more investment in housing sector and results into resource depletion of banking system.

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In spite of a lot of studies in field of housing, housing supply has been less addressed. One of main reasons is complexity of housing supply field. In this study we use Capozza and Helsley urban growth model which assume housing supply as a function of variations in both housing price and construction expenses. The model is estimated with General Method of Moments (GMM) using seasonal data of Iran for 1996:2-2008:1. Results show that effect of housing price variations on housing supply is positive, however the effect of building material expenses and construction opportunity cost (stock exchange index) are both negative on it, but coefficient of stock exchange index is statistically insignificant. In addition, housing price variations and building material expenses with two period lags are effective on housing supply which indicate role of expectations. Also results show that variations in the other markets such as building materials market play important role in housing supply. It is proposed that because of high sensitivity in increasing of housing price, policies of housing supply to be followed by this market.