Everyone wants to know the future. Home sellers and buyers want to predict home prices. Home sellers want to know the best time to sell. Home buyers want to know if they’re getting a good price. And apparently there may be a fairly reliable predictor to home prices, however it’s not what you think it is.
Several empirical studies have attempted to provide a methodology for predicting the housing market. Of course, there is the familiar forecasting of real estate through divorce and premarital agreements. Back in 2013, the American Academy of Matrimonial Lawyers (AAML.org) issued a press release citing the increase of prenuptial agreements as sign of the improving economy. The increase in prenuptial agreements meant that people felt there was value in their assets. And this was meant to be a good sign for the housing market.
Of course, there was also a spike in divorces that year, leading some to believe this also to be a good sign that people felt better about the economy because of their willingness to begin anew. But as University of Maryland sociologist Philip N. Cohen pointed out in his November 2015 blog post (Divorce rate plunge continues; familyinequality.wordpress.com) the increased divorce activity of 2013 was just a recession-related “bump” and in actuality, the divorce rate decreased in 2014.
Then there was predicting housing through internet search data, which sounds more like fortune-telling than research, to be honest. However, Beracha and Wintoki (Forecasting Residential Real Estate Price Changes from Online Search Activity; The Journal of Real Estate Research 35.3 (2013): 283-312.) concluded that, indeed, you can gauge regional housing trends through specific keyword search volume. Given this method, I used Google Trends to look up the keyword “home for sale” for the Washington, DC metro region – and it is bound to become a hot market in the next six months (maybe a Presidential election has something to do with that?).
But a better indicator of where home prices will go may be the availability of credit. Most would argue that mortgage lending is a matter of housing demand. However, a working paper by Manuel Adelino, Antoinette Schoar, and Felipe Severino (Credit Supply and House Prices: Evidence from Mortgage Market Segmentation; February 19, 2014) concluded that “easy credit supply leads to an increase in house prices.” They contend that higher conforming loan limits and low interest rates benefit home sellers in the form of higher sale prices.
Adelino, Schoar, and Severino’s premise can be witnessed in hindsight as the pre-recession housing boom seemed to be fueled on easy credit. As credit became increasingly available, real estate appreciation took off. Likewise, housing stabilized and home values appreciated post-recession as home-lending requirements loosened.
Of course, many associate easy credit policies with recessions, and even the Great Depression. However, it’s not necessarily the easy credit that precipitates the recession – but rather it’s the tightening of credit. Stephen Gandel (Time to Panic About a Recession; fortune.com; March 8,2016) said it succinctly, “Tightening credit doesn’t always lead to a recession. But every recession starts with that.”
One may infer from Adelino, Schoar, and Severino’s research that a home seller can gauge their home sale price based on the lending environment. Lower interest rates and loose credit points to a higher sale price. However, tightening credit policies may point to flat or even lower home prices.
Dan Krell is a Realtor® with RE/MAX All Pro in Rockville, MD. You can access more information at www.DanKrell.com.