Naser Khiabani; shaghayegh shajari
Abstract
Housing price swings have always been under the spotlight for policy-makers and academics. Financial accelerator mechanism (developed by Bernanke and Gertler, 1999) can provide some explanation to these fluctuations. With focusing on the concept of financial accelerator, this paper sheds light on the ...
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Housing price swings have always been under the spotlight for policy-makers and academics. Financial accelerator mechanism (developed by Bernanke and Gertler, 1999) can provide some explanation to these fluctuations. With focusing on the concept of financial accelerator, this paper sheds light on the long- and short-run correlation of housing prices and credit in Iran. We applied a Structural Vector Error Correction Model (SVECM) to housing and credit market over period 1988q2-2015q1. Our findings confirm the existence of a cointegrated relationship between credit and housing prices. In a long-run perspective, the causation goes from credit to housing prices. However, in the short-run we find an existence of contemporaneous bi-directional dependence between housing prices and credit. In general, we find the evidence of housing collateral effect in housing and credit markets in Iran. However, this role is small and limited compared to the same role in countries with developed financial and mortgage markets.
Seyed Mohammadreza Seyed Nourani
Volume 14, Issue 52 , April 2014, , Pages 68-49
Abstract
Abstract In this paper we have examined housing bubble and speculation in urban areas of Iran. For this purpose, we have designed a suitable model to identify factors determining housing prices in Iran and then, we have used GMM method to estimate the model for quarterly data ...
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Abstract In this paper we have examined housing bubble and speculation in urban areas of Iran. For this purpose, we have designed a suitable model to identify factors determining housing prices in Iran and then, we have used GMM method to estimate the model for quarterly data in the period of 1996:2 to 2011:1. The results show that several variables including prices in previous periods, the rate of return in other markets (taking adjusted consumer price index as a proxy) , housing supply (for which, we have used the number of construction permits as proxy), population growth and housing costs has had statistically significant impact on house prices in Iran. Contrary to our expectations, the coefficient of national income (GDP) variable has not been statistically significant. Taking prices of previous year as Proxy of speculation demand, while taking return in other markets, housing supply, changes in population and housing costs as proxy for consumption demand, we found that the share of speculating demand for housing has been 6.8 times higher than demand for consumption during the period under study. When we extend our sample up to 2012 and defining house price bubble as deviation of short term price from its long term trends, the result shows that in the three last quarters of year 2012, price bubble in housing of Iran was 17/8, 26/3 and 56/6 percent respectively for these quarters, which we can interpret them as the impact of psychological expectations and short term fluctuations.
Heshmatolah Asgari; Isaac Almasi
Volume 11, Issue 41 , July 2011, , Pages 201-224
Abstract
Fluctuations of the housing prices during the past 15 years in the country and
provincial level, has been remarkable. In this paper, factors affecting housing price
level (long term) and its fluctuations (short term) in the provinces during the period
1370-1385(1991-2006) has been studied. For this ...
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Fluctuations of the housing prices during the past 15 years in the country and
provincial level, has been remarkable. In this paper, factors affecting housing price
level (long term) and its fluctuations (short term) in the provinces during the period
1370-1385(1991-2006) has been studied. For this purpose we used method of
panel data. The analysis shows that in short-term, factors of the housing price
fluctuations are: stock market price index, the general price level in the previous
period, the price of land, construction costs, oil prices, the amount of private sector
investment, household spending and interest rate on loan. Also in the long term,
factors of the housing price fluctuations are: housing prices in the previous period,
the number of households, stock market price index, household spending, the gold
prices, land and housing prices and so on. Other results in this paper show that in
determining housing prices and its variations the land price, the general price level
of the previous priod, interest rate on loan and oil prices had the greatest effect,
respectively.
