We use a time-varying parameter dynamic factor model with stochastic volatility estimated using Bayesian methods to disentangle the relative importance of the common component in Federal Housing Finance Agency house price movements from state-specific shocks, over the quarterly period of 1975Q2 to 2017Q4. We find that the contribution of the national factor in explaining fluctuations in house prices is critical. We then use a Bayesian change-point vector autoregressive model that allows for different regimes throughout the sample period, to study the impact of aggregate supply, aggregate demand, (conventional) monetary policy, and term-spread shocks, identified based on sign restrictions on the national component of house price movements. While monetary policy and other shocks are found to be quite dominant early on, we find evidence that the national factor has been detached from the identified macroeconomic shocks since 2014, thus suggesting that a “national bubble” might be brewing again in the US housing market.

In this paper we empirically examine the sources of the volatility of the foreign exchange risk premia. Using a nonlinear structural Vector Autoregression (VAR) model based on no-arbitrage condition to identify various macroeconomic shocks and the foreign exchange risk premia, we find that more than 80% of the volatilities of the currency risk premia can be accounted for by the standard macroeconomic shocks that drive output and inflation. By explicitly modelling the currency risk premia in the VAR system, we also offer a potential reconciliation for the seemingly contradicting observations from the previous VAR analysis of the exchange rate “overshooting” behavior under exogenous monetary innovations.