Big data is everywhere. The ability to tap into vast quantities of information is influencing virtually every facet of business, and the real estate industry is no exception.
What does big data offer? First, up-to-date and reliable information on local and global real estate markets, which can reframe strategic decision-making. Second, the creation of new data sets that may effectively predict housing booms and busts.
Consider the global financial crisis of 2007-2008, triggered in part by the U.S. real estate bubble. If industry experts and governments had been able to access and leverage data more effectively, they could have made more accurate assessments of the market situation.
As noted by Prof. Carles Vergara of IESE’s Financial Management Department, “The intelligent use of big data is critical for real estate professionals and developers, as well as financial institutions and policymakers.”
Deeper market insights
One of the most prominent players in the real estate sector has been the online database company, Zillow. The company aggregates key information for users, generating revenue through advertising on its website. Zillow has transformed the industry, helping customers make more informed investment decisions, while serving as a channel for agents to market houses.
The list of relevant information categories now available online is long: property features, crime rate indexes, education levels, air pollution and quality of life standards, among others. All can be culled and analyzed to make more effective real estate investment decisions.
For instance, communities with a high quality of life typically offer affordable housing, employment opportunities, good schools and outstanding public services. These elements are now being measured and reported online. Having a more granular view of these factors can help city planners more effectively map out residential, commercial and industrial growth.
Predicting future crashes
Big data can also help predict the next housing crash.
A lot of effort has gone into explaining what causes housing prices to rise, and consequently bubbles to occur. Theories include irrational optimism, widespread perceptions of price appreciation or the erroneous belief in the efficient markets hypothesis.
In fact, big data may hold the key to predicting when an asset bubble is on the horizon.
In a recent study, Vergara and Pedro Saffi from the University of Cambridge proved this. They collated lending data from the stock markets with detailed property data gleaned from Real Estate Investment Trusts (REITs). Their analysis showed that the amount of investors’ REIT short-selling activity in the stock markets is a reliable indicator of a housing crash.
The 2008 global financial crisis, sparked in part by the real estate bubble burst, had far-reaching effects, including a sharp fall in global trade and investment. This was followed by a long period of slow growth in countries burdened by debt. While it’s still difficult to detect a housing bubble, this may become easier with big data.
Keeping the real estate industry healthy is vital, since it has a major impact on the economy as a whole. Big data can contribute to this goal, helping inform decision-making and anticipate future crises.
If you want to learn more about global real estate, such as how to better analyze the sector from an international perspective and how to master the common elements of successful property operations, IESE’s “International Real Estate” program will take place October 23-25, 2018, in IESE’s Barcelona campus.