Speculative bubbles or market fundamentals? An investigation of US regional housing markets

This paper investigates the existence of speculative bubbles in the US national and 21 regional housing markets over three decades (1978–2015). A new method for real-time monitoring exuberance in housing markets is proposed. By taking changes in the macroeconomic conditions (such as interest rate, per-capita income, employment, and population growth) into consideration, the new method provides better control for housing market fundamentals and thereby it is expected to significantly reduce the chance of false positive identification. Compared with the method of Phillips et al. (2015a, 2015b), the new approach finds a dramatic reduction in the number of speculative housing markets and shorter bubble episodes in the US. It locates only one bubble episode in the early-to-mid 2000s over the whole sample period in the national housing market. At the regional level, it identifies two periods of speculation: late 1980s and early-to-mid 2000s. The early-to-mid 2000s bubble episode lasts longer and involves 16 metropolitan statistical areas.     

Patterns of growth in Chinese cities: Implications of the land lease

A special feature of China’s housing market is land use rights in the form of land leasehold contracts granted by the government. We consider an equilibrium model in which a representative developer may choose to redevelop existing centrally located housing or to develop new housing at the periphery of the city. We show that as the city grows, the land leasehold system results in the city center being developed less intensely and more land being used on the outskirts of the city when compared to a fee simple environment. Thus, cities in China are likely to be relatively more spread out, with city centers relatively older than would be the case with “fee simple” ownership. Our model suggests that excess residential land use is about 6 percent. In addition, compared with the ownership case, housing supply will grow more quickly in the near future, but more slowly later on during the transition of the Chinese economy. Parallel to the supply growth pattern, equilibrium price grows relative slowly in the near future, but more quickly later on. While we focus on residential uses, we believe our model can be applied to other land uses.     

Do housing prices promote total factor productivity? Evidence from spatial panel data models in explaining the mediating role of population density

The issue of what to promote in total factor productivity (TFP) in urban areas has been widely discussed in academia and housing prices and population density are confirmed to be two of the most essential driving factors. However, research into the interaction of housing prices and population density with TFP has been neglected, with no previous studies taking spatial factors into consideration, which may bias the results. From this perspective, using spatial panel data models and employing instrumental variables to solve the endogenous problem, this study examines the impact of housing prices on TFP through the mediating effect of population density for 283 Chinese cities during the period 2000–2013, and confirms that the mediating effect accounts for 18.70 % of the total effect. The results show the positive and significant association of housing prices with TFP and the inverted U-shape of population density. The underlying logic is that housing prices change population density by attracting people with high purchasing power and discouraging those unable to afford housing, whereas increased density helps to promote productivity since the settled inhabitants always have highly developed work skills and are well educated. The influencing mechanism of housing prices on TFP through population density is analyzed, namely the spillover effect. We find that the spillover effect exists in the eastern and central regions, as well as first, second, and third tier cities, while for western regions and fifth tier cities, population mobility and increased in housing prices slows their economic development. There is no evidence of any spillover effect in fourth tier cities. A discussion and suggested policy implications are also provided.     

What caused the rise of Airbnb? An examination of key macroeconomic factors

The social and economic implications of the Airbnb phenomenon have been the subject of much research. Yet, the academic literature on Airbnb is nascent. Specifically, the issue of whether major macroeconomic conditions affect the supply of Airbnb has not been investigated. To address this gap, we propose a conceptual model that explains the determinants of Airbnb supply and examine the extent to which major macroeconomic factors affect the supply of Airbnb. Specifically, we analyze the effects of hotel room rates (ADR), hotel demand, tourism demand, house prices, gross domestic product (GDP), wages and unemployment on the supply of Airbnb in 50 U.S. states. Results show that increases in hotel ADR, house prices, and GDP have contributed to an increase in the supply of Airbnb, whereas increases in unemployment rates and wages have adverse effects on Airbnb supply. Theoretical and policy implications are discussed within realms of macroeconomic theory.     

The effect of economic policy uncertainty on China’s housing market

This study examines the relationship between economic policy uncertainty (EPU) and housing price at the macro-level in China as a developing country. The empirical evidence indicates that EPU has a leading effect on China’s housing market. In general, the housing market is prosperous when economic policy is stable and there is a positive relationship between housing price variation and EPU, which means housing market risk grows under unstable economic policies in this developing economy. Moreover, economic policy variation affects low-amplitude changes in housing prices. A variation of policy uncertainty enhances the risk premium of the housing market. By contrast, the level of EPU influences high-amplitude changes in housing prices, which reflects the trend of EPU dominating China's housing market.     

Time-varying inter-urban housing price spillovers in China: Causes and consequences

The spatial spillovers of housing prices across regions are well documented by a large body of previous studies. This paper tries to investigate the dynamic (time-varying) evolution of spatial interactions and their underlying driving factors intensively. Using a recently developed Generalized Autoregressive Score (GAS) model, this paper examines the time-varying spatial spillovers of housing prices in 70 major and median cities of China from 2006 to 2019. We find that the GAS model can well capture the impact of time-varying critical events of Chinese real estate market on the whole. However, different regions display heterogeneous variation patterns over time. Further investigation shows that inter-regional labor mobility and trades are two major channels, accounting for 1.25% and 2.58% of the monthly standard deviations of spatial spillover effects from one city to another, respectively. We also characterize and distinguish between three time-varying patterns of spatial spillovers within different regions of China. Our results shed lights on the understanding of spatial spillovers across regional real estate markets across different city network structures within China.     

Ex-post incentive compatible and individually rational assignments in housing markets with interdependent values

This paper presents a model for housing markets with interdependent values. We introduce private information on the quality of a house (i.e., high or low), which is known only to the initial owner. Interdependency means that the ex-post preference of an agent depends on the private information of the other agents with regard to the quality of houses. We prove that on a domain satisfying a richness condition, the no-trade rule is the only rule that satisfies ex-post incentive compatibility and ex-post individual rationality.     

Random mechanisms for house allocation with existing tenants

We study the house allocation problem with existing tenants: $n$ houses (stand for “indivisible objects”) are to be allocated to $n$ agents; each agent needs exactly one house and has strict preferences; $k$ houses are initially unowned; $k$ agents initially do not own houses; the remaining $n-k$ agents (the so-called “existing tenants”) initially own the remaining $n-k$ houses (each owns one). In this setting, we consider various randomized allocation rules under which voluntary participation of existing tenants is assured and the randomization procedure either treats agents equally or discriminates against some (or all) of the existing tenants. We obtain two equivalence results, which generalize the equivalence results in Abdulkadiroğlu and Sönmez (1999) and Sönmez and Ünver (2005).     

Was the expansion of housing credit in Japan good or bad?

This paper shows, using data from the Family Income and Expenditure Survey, that housing credit has become increasingly available over time in Japan, especially since 2000, and that this has made it easier for Japanese households to purchase housing and enabled them to do so at an earlier age. However, it also shows that the greater availability of housing credit has increased households’ housing loan repayment burden, which has resulted in their cutting back on their other consumption expenditures and created the potential for retirement insecurity. Another concern is that the increasing availability of housing credit has been accompanied by a pronounced shift from fixed-rate to variable-rate housing loans. This is cause for concern given the low level of financial literacy that prevails among the Japanese population and the likelihood that interest rates on variable-rate housing loans will be raised sooner or later as monetary policy is tightened.     

Tacit collusion in housing markets: the case of Santiago,Chile

In this article, using a detailed micro-database from Santiago, Chile, the potential existence of tacit collusion in housing markets is investigated. In order to perform the test, Santiago’s housing market is split into four different submarkets using hedonic price analysis and household’s socioeconomics characteristics. Then, using a GMM panel data model, regressions are run for each submarket, correlating industry’s markups with the aggregate level of activity. The main finding is that low and middle income submarkets present higher average markups and a pro-cyclical behaviour. This finding is consistent with a market where participants do not face capacity constraints and behave strategically to sustain tacit collusion during increasing demand periods.