Housing Market Spillovers

The housing market has been argued as the main driving force of the 2008-2009 financial crisis. In U.S., the past decade initially saw a rapid growth in housing prices and residential investment, followed by the collapse of housing market and frozen credit market. This led many economists to raise the issue that housing market is not only a passive reaction of other economic and financial activities but the causing factor of business fluctuations. Therefore, we wish to expand this study further by undertaking empirical research, firstly by modelling housing market either in a dynamic stochastic general equilibrium (DSGE) framework or a reduced form VAR model. Secondly, we will examine the sources and consequences of housing market

The earlier literature attempts to incorporate the housing market are Iacoviello (2005) and Iacoviello and Neri (2010). Building a dynamic stochastic general equilibrium (DSGE) model, they found that housing market spillovers cannot be ignored. Over the business cycle, housing demand andhousing technology shocks explain one-quarter each of the volatility of housing market. Similar versions of this model have been used in different central banks and economic organisations, such as Riksbank (Sellin and Walentin, 2015), European Commission (Roeger and in ’t Veld, 2009), Bank of Canada (Christensen, et al., 2009), and IMF (Kannan, Rabanal and Scott, 2009).

Proposed Methods

The method can be two directions. If we focus on the reduced form model, we need to build a VAR model based on the DSGE framework of Iacoviello (2005). The impulse response functions can explain the housing market responses after a shock. The variance decomposition allows us to see how much each shock contributes to the volatility of the housing market. If we need to build a DSGE framework, we can use Bayesian estimation method. All the analysis will be based on these estimation results.