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This paper examines the effects of a mortgage interest rate subsidy on booms and busts in the housing market by analyzing the Housing Mortgage program in Mongolia. We find that the most recent housing boom in Mongolia occurred from the second quarter (Q2) of 2012 to first quarter (Q1) of 2014, and that the subsequent housing bust lasted 4 years. Both house-specific factors and macroeconomic variables had a significant influence on housing price dynamics. Mortgage interest rate semielasticity and real household income elasticity were estimated as −3 and 1.4, respectively. Dynamic analysis of the estimated vector error correction models suggests that the country’s policy intervention in the mortgage market—introducing an interest rate subsidy on mortgage loans for residential properties of up to 80 square meters—drove the recent housing boom in Mongolia.

In this paper, we propose a two-country, two sector monetary union DSGE model with housing. One of the countries is calibrated to represent the Spanish economy while the other one is the rest of the European monetary union. First, we illustrate how looser credit conditions coming from the Euro area, together with increases in housing demand, lead to an increase in house prices and credit in Spain. Then, we analyze to what extent, macroprudential policies could have avoided the excess in credit that triggered the financial crisis in Spain. We find that a countercyclical loan-to-value (LTV) rule that mainly responds to house prices would have mitigated the credit boom in Spain. These results can also be applied to other countries facing similar problems in the housing sector and thinking about implementing macroprudential policies.

The latest global financial tsunami and its follow-up global economic recession has uncovered the crucial impact of housing markets on financial and economic systems. The Chinese stock market experienced a marked fall during the global financial tsunami and China’s economy has also slowed down by about 2%–3% when measured in GDP. Nevertheless, the housing markets in diverse Chinese cities seemed to continue the almost nonstop mania for more than 10 years. However, the structure and dynamics of the Chinese housing market are less studied. Here, we perform an extensive study of the Chinese housing market by analyzing 10 representative key cities based on both linear and nonlinear econophysical and econometric methods. We identify a common collective driving force which accounts for 96.5% of the house price growth, indicating very high systemic risk in the Chinese housing market. The 10 key cities can be categorized into clubs and the house prices of the cities in the same club exhibit an evident convergence. These findings from different methods are basically consistent with each other. The identified city clubs are also consistent with the conventional classification of city tiers. The house prices of the first-tier cities grow the fastest and those of the third- and fourth-tier cities rise the slowest, which illustrates the possible presence of a ripple effect in the diffusion of house prices among different cities.

The often volatile behavior of the Hong Kong housing construction activity is analysed using an annual econometric model for 1975 through 1999. Theory suggests that an increase in house prices leads to a rise in the housing stock, whereas an increase in interest rates leads to a decrease in the housing stock. However, the DiPasquale and Wheaton (1996) model does not seem to work for Hong Kong. Therefore, this study develops and uses an alternative model to show that the long-run equilibrium housing construction is constrained by total space absorption.

This paper investigates whether real house price appreciations can be attributed to the surge in real capital inflows into Singapore. We proxy capital flows by using the amount of Foreign Direct Investments (FDI) to real estate capturing the foreign purchases of property in Singapore which we deflate by the private residential property price index. Notwithstanding the absence of a cointegrating relationship, our results support the hypothesis that lagged short term fluctuations in capital inflows are positively associated with the growth rates of house prices over the last decade. We also provide evidence that macroprudential measures implemented by Singapore reduced the impact of capital inflows on house price appreciation by more than half, suggesting the effectiveness of such market cooling measures in weakening the credit growth channel.

How can we detect real estate bubbles? In this paper, we propose making use of information on the cross-sectional dispersion of real estate prices. During bubble periods, prices tend to go up considerably for some properties, but less so for others, so that price inequality across properties increases. In other words, a key characteristic of real estate bubbles is not the rapid price hike itself but a rise in price dispersion. Given this, the purpose of this paper is to examine whether developments in the dispersion in real estate prices can be used to detect bubbles in property markets as they arise, using data from Japan and the U.S. First, we show that the land price distribution in Tokyo had a power-law tail during the bubble period in the late 1980s, while it was very close to a lognormal before and after the bubble period. Second, in the U.S. data we find that the tail of the house price distribution tends to be heavier in those states which experienced a housing bubble. We also provide evidence suggesting that the power-law tail observed during bubble periods arises due to the lack of price arbitrage across regions.