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In 2016, the city of Shanghai increased the minimum down payment rate requirement for purchasing various types of properties. We study the treatment effect of this major policy change on Shanghai’s housing market by employing panel data from March 2009 to December 2021. Since the observed data are either in the form of no treatment or under the treatment but before and after the outbreak of COVID-19, we use the panel data approach suggested by Hsiao et al. (J Appl Econ, 27(5):705–740, 2012) to estimate the treatment effects and a time-series approach to disentangle the treatment effects and the effects of the pandemic. The results suggest that the average treatment effect on the housing price index of Shanghai over 36 months after the treatment is -8.17%. For time periods after the outbreak of the pandemic, we find no significant impact of the pandemic on the real estate price indices between 2020 and 2021.

Motivated by the observation that the down payment policy in China is government-controlled and pro-cyclical based on the housing market, I construct a heterogeneous DSGE model to study the relationship between China’s down payment policy, property tax, and economic fluctuations. The results indicate that an increasing down payment ratio suppresses the speculative belief and decreases household’s housing demand. This in turn pulls housing prices down and smoothes the economic fluctuations. By way of counterfactual exercises, I also find that the down payment policy and the property tax can be substitutes for each other. If there is an active down payment policy, the implementation of property tax shall be prudently deliberated by the Chinese government.

We study the relationship between homebuyers’ beliefs about future house price changes and their mortgage leverage choices. Whether more pessimistic homebuyers choose higher or lower leverage depends on their willingness and ability to reduce the size of their housing market investments. When households primarily maximize the levered return of their property investments, more pessimistic homebuyers reduce their leverage to purchase smaller houses. On the other hand, when considerations such as family size pin down the desired property size, pessimistic homebuyers reduce their financial exposure to the housing market by making smaller downpayments to buy similarly-sized homes. To determine which scenario better describes the data, we investigate the cross-sectional relationship between house price beliefs and mortgage leverage choices in the U.S. housing market. We use plausibly exogenous variation in house price beliefs to show that more pessimistic homebuyers make smaller downpayments and choose higher leverage, in particular in states where default costs are relatively low, as well as during periods when house prices are expected to fall on average. Our results highlight the important role of heterogeneous beliefs in explaining households’ financial decisions.

I propose a life-cycle model where a finitely lived risk-averse household finances its housing investment by opting to provide a down payment. Given that the household may default, risk-neutral lenders efficiently charge a default premium to hedge against expected losses. This has two major consequences. First, the higher the house price volatility, the higher the down payment the household provides to decrease the volatility of the equity share in the house. Second, in the presence of borrowing constraints, higher risk of unemployment persistence and/or a substantial drop in labor income decreases the leveraged position the household takes on.

We construct housing price indices for 120 major cities in China in 2003–2013 based on sequential sales of new homes within the same housing developments. By using these indices and detailed information on mortgage borrowers across these cities, we find enormous housing price appreciation during the decade, which was accompanied by equally impressive growth in household income, except in a few first-tier cities. While bottom-income mortgage borrowers endured severe financial burdens by using price-to-income ratios over eight to buy homes, their participation in the housing market remained steady and their mortgage loans were protected by down payments commonly in excess of 35%. As such, the housing market is unlikely to trigger an imminent financial crisis in China, even though it may crash with a sudden stop in the Chinese economy and act as an amplifier of the initial shock.

President-elect Joe Biden on Dec. 16 called the roughly $900 billion coronavirus aid bill taking shape in Congress a \"downpayment\" toward a bigger stimulus next year.

This paper uses an assignment model to understand the cross section of house prices within a metro area. Movers' demand for housing is derived from a life-cycle problem with credit market frictions. Equilibrium house prices adjust to assign houses that differ by quality to movers who differ by age, income, and wealth. To quantify the model, we measure distributions of house prices, house qualities, and mover characteristics from micro-data on San Diego County during the 2000s boom. The main result is that cheaper credit for poor households was a major driver of prices, especially at the low end of the market.

How much of the foreclosure crisis can be explained by the large number of high-leverage mortgages originated during the housing boom? In our model, heterogeneous households select from mortgages with different down payments and choose whether to default given income and housing shocks. The use of low–down payment loans is initially limited by payment-to-income requirements but becomes unrestricted during the boom. The model approximates key housing and mortgage market facts before and after the crisis. A counterfactual experiment suggests that the increased number of high-leverage loans originated prior to the crisis can explain over 60 percent of the rise in foreclosure rates.

This paper studies how the durability of assets affects financing. We show that more durable assets require larger down payments making them harder to finance, because durability affects the price of assets and hence the overall financing need more than their collateral value. Durability affects technology adoption, the choice between new and used capital, and the rent versus buy decision. Constrained firms invest in less durable assets and buy used assets. More durable assets are more likely to be rented. Economies with weak legal enforcement invest more in less durable, otherwise dominated assets and are net importers of used assets.