A Framework to Monitor the Effects of External Shocks on Housing Markets

We develop a framework to holistically test for and monitor the impact of different types of events affecting a country's housing market, yet originating from housing-external sources. We classify events along three dimensions leading to testable hypotheses: prices versus quantities, supply versus demand, and immediate versus gradually evolving. These dimensions translate into guidance about which data type, statistical measure and testing strategy should be used. To perform such test suitable statistical models are needed which we implement as a hierarchical hedonic price model and a complementary count model. These models are amended by regime and contextual variables as suggested by our classification strategy. We apply this framework to the Austrian real estate market together with three disruptive events triggered by the COVID-19 pandemic, a policy tightening mortgage lending standards, as well as the cost-of-living crisis that came along with increased financing costs. The tests yield the expected results and, by that, some housing market puzzles are resolved. Deviating from the prior classification exercise means that some developments would have been undetected. Further, adopting our framework consistently when performing empirical research on residential real estate would lead to better comparable research results and, by that, would allow researchers to draw meta-conclusions from the bulk of studies available across time and space.