This study provides fresh implications for the puzzle of the recent housing boom-bust cycle in the United States. It extracts housing factors from housing price and volume time series at state and regional levels under a dynamic factor model, which considers three varieties of structural instability in local housing markets. The findings suggest that state-level housing price cycles are more unstable than housing volume cycles, and the probability of rejecting stability for the Northeast is the highest among four regional housing markets. In general, the housing market forecasts based on 1988–2012 full-sample factors and time-varying coefficients across pre- and post-1999 subperiods are superior to alternatives. The factor-based forecast results provide new evidence for a nationwide housing crisis in 2007–2008, and thus suggest possible effectiveness of monetary policies in stabilizing recent housing boom-bust cycles.
Computational Economics – Springer Journals
Published: May 31, 2018
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera