This paper is about investigating how different bank liquidity creation activities affect housing markets. Using data of 401 metropolitan statistical areas/metropolitan statistical area divisions (MSAs/MSADs) of the U.S. between 1990 and 2018, we show that not all bank liquidity creation activities boost the housing markets. In particular, unlike asset- side and off-balance sheet liquidity creations, funding-side liquidity creation dampens housing markets. The relationships between liquidity creation activities and housing markets are stronger in regions with inelastic house supply, but flip when banks face external liquidity shocks. We also find that housing markets dominated by large banks are more sensitive to off-balance sheet liquidity creation activities. Finally, as expected, asset-side and off-balance sheet liquidity creations boost housing markets by driving house prices away from fundamental values. Our results offer a more thorough explanation of how bank liquidity creation fuels the momentum of housing markets.

We document a speculation channel through which house market booms negatively affect entrepreneurship. To address endogeneity concerns, we exploit plausibly exogenous variation in house prices generated by staggered and unintended policy spillovers in China. We find house market speculation triggered by house booms crowds out entrepreneurship. Reduced labor supply, reduced capital supply, and heightened entry costs do not appear to explain our main findings. The negative effect exhibits in the OECD countries as well. Our paper complements the well-documented collateral channel by offering novel evidence on a previously under-explored adverse consequence of house market booms – their hindrance to entrepreneurship.

Using the regression discontinuity design, a quasi-experiment approach, this paper establishes a causal relationship between the down payment requirement and house prices by exploiting a unique institutional background in Shanghai. In the unique setting, the required minimal down payment ratio jumps at the Inner Ring, a circular elevated highway, from 50% to 70% for a large group of buyers. With transaction level data from the largest real estate broker in Shanghai, we find that a lower required down payment ratio increases the apartment price by 138.8 thousand RMB, around 3.71% of the average transaction price.

This study contributes to the understanding of the relationship between Chinese local government debt and house prices by proposing the land channel as a novel explanatory framework. We construct a three-sector equilibrium model and demonstrate that local government debt positively affects house prices through both direct and indirect effects, with the indirect effect operating through the land market. However, the land use efficiency mitigates the positive effect of government debt on land and house prices within indirect effect. These propositions are empirically confirmed using a panel dataset of 260 cities in China from 2011 to 2019.

We examine the roles of bank ownership and CEO political faction membership in facilitating or hindering the implementation of central bank policy in China. Specifically, we examine the response of China’s commercial banks to People’s Bank of China (PBC) guidelines intended to decrease mortgage lending and to slow down the rise in residential property prices. We find that both bank ownership and faction membership matter. Central government-owned banks whose CEOs are members of the specialist finance faction within the Chinese Communist Party (CCP) respond most strongly to PBC guidance, whereas provincial or city government-owned banks whose CEOs are members of a generalist faction respond least strongly. The implementation of PBC policy has real effects: in those cities where central government-owned banks with specialist CEOs constitute a larger percentage of total bank branches, house prices grew more slowly, as did the number of residential real estate transactions and the number of new listings. Where in contrast provincial and city government-owned banks with generalist CEOs dominate, the number of transactions grew faster; the rate of house price appreciation and the number of listings were however unaffected. We conclude that China’s different levels of government and the CCP’s different factions enjoy some discretion in responding to PBC guidance and that they exploit the discretion they are afforded to vary the strength of their response.

This paper studies the effect of housing wealth shocks on workplace shirking. We use the type and actual time stamps of credit card transactions to detect non-work-related behavior during work hours. After positive shocks to house prices, affected homeowners experienced a fast and persistent increase (by 19% per month) in their propensity to use work hours to attend to personal needs. The post-shock response is more pronounced among homeowners with a greater wealth increase, with poorer career potential, or for occupations with higher monitoring costs. Our estimate implies an elasticity of shirking propensity with respect to house price of 3.8.

There are many similarities between the US, the UK and the Chinese housing markets, including the movements of interest rates and house prices. Some Chinese banks, especially the Bank of China, have been exposed to the US mortgage securitization market. These have triggered a serious concern as to whether the US credit crunch and housing market crisis may be replicated in China. This paper shows that there are some significant differences between China and the West, especially the US and the UK. Compared with the US and other western industrialized economies, the booming house market in China has been supported by fast economic growth, rapid urbanization and high domestic savings. In addition, Chinese banks are less exposed to mortgage defaults than their western counterparts because house buyers are mainly urban and high income residents who are required to have high down payments. These Sino-Western economic and social differences suggest that the US credit crunch and housing market crisis may have some negative impacts on Chinese commercial banks and the overall economy but are unlikely to cause a similar financial and housing crisis in China despite the current struggling Chinese stock markets and a slowdown of house price growth.

Using loan-level data, we analyze the quality of subprime mortgage loans by adjusting their performance for differences in borrower characteristics, loan characteristics, and house price appreciation since origination. We find that the quality of loans deteriorated for six consecutive years before the crisis and that securitizers were, to some extent, aware of it. We provide evidence that the rise and fall of the subprime mortgage market follows a classic lending boom-bust scenario, in which unsustainable growth leads to the collapse of the market. Problems could have been detected long before the crisis, but they were masked by high house price appreciation between 2003 and 2005.

We conduct a within-county analysis using detailed zip code level data to document new findings regarding the origins of the biggest financial crisis since the Great Depression. The recent sharp increase in mortgage defaults is significantly amplified in subprime zip codes that experience an unprecedented relative growth in mortgage credit from 2002 to 2005. This expansion in mortgage credit to subprime zip codes occurs despite sharply declining relative (and in some cases absolute) income growth in these neighborhoods. In fact, 2002 to 2005 is the only period in the last 18 years when income and mortgage credit growth are negatively correlated. We show that the expansion in mortgage credit to subprime zip codes and its dissociation from income growth is closely correlated with the increase in securitization of subprime mortgages. Finally, we show that all of our key findings hold in markets with very elastic housing supply that have low house price growth during the credit expansion years. Overall, our findings favor a supply-based explanation for credit expansion over income-based or house price expectations-based hypotheses.

The pairs (or repeat) transactions index model is the most widely used method for constructing housing market index and for estimating individual house prices. However, this model is unable to provide price level information on the housing market and encounters several statistical problems when individual houses have more than two transactions. In order to overcome the shortcomings of pairs transactions model, we propose a multi transactions model with the panel data approach to estimate market index and to predict house prices. The empirical results based on 5,000 houses in Howard County Maryland demonstrate that the proposed multi transactions model: (1) can provide price level information on the housing market; (2) produces market index with smaller standard errors; (3) is more robust in terms of difference between the sub-sample estimate and full sample estimate; (4) has smaller index revision volatilities; and (5) performs better in the out-of-sample test on the prediction of individual house prices. Thus, the multi transactions model is recommended for constructing housing market index and assessing individual house prices.