This paper studies the dynamic relationship between public and private commercial real estate market in the U.S. To do so, we propose a correlatedcunobserved component model with a common trend and Markov-Switching heteroscedasticity. This model addresses the dichotomy in the relationship between these two markets in the short-run and the long-run by allowing for a common long-run trend and correlated short-run cycles. To take into account the non-linearity in the commercial real estate dynamics, we also allow Markov regime-switching in shocks to the trend and the cycles.
Consistent with the findings of the literature, we find almost one-for-one comovement in these two markets in the long-run. However, our results suggest significant difference in the correlation of the cycles in low
volatility and high volatility regimes. We find high degree of correlation between private and public commercial real estate cycles only in the high volatility regime. This explains the low correlation in the return of these two markets as has been widely reported in the literature. Moreover, we also find that the past movements in public commercial real estate cycle predict future movement in private commercial real estate cycles reflecting the
forward-looking nature of the public commercial real estate market