Policy Impact Analysis of Housing Policies Using Housing Cycles

In Korea, there is a big difference in the rise and fall of apartment prices by region, so it is expected that there will be differences in regional economic indexes. So, to capture the housing market conditions, we developed the housing cycle by using the factor-augmented vector autoregressive model (FAVAR). In addition, we estimated the impacts of the Korean government’s housing policies on the housing cycle. The first is a net policy effect model, and the second is a comprehensive model with macroeconomic variables and regional variables. To estimate the effects of the policies, we considered financial, tax, and housing transaction policies. In the net policy effect model, we found that all policies, including an increase in the DTI (debt to income) ratio, the LTV (loan to value) limit, an acquisition tax reduction, a transfer tax deregulation, deregulation of the housing subscription policy, and a housing purchase right transfer, impacted the housing cycles at the period t − 1. This is why the Korean government announced policy enforcement in advance a month ago before policy implementation. In the comprehensive model, we found that the policies had statistically significant effects on housing cycles at the period t − 1, and we also found that the regional variables had an influence on the housing cycle. Therefore, the Korean government should consider the regional characteristics and time lag when it attempts to intervene in the housing market.