The Impact of High-Quality Innovation on Home Prices
The high cost of housing may have more than just supply and demand as driving factors.
Academic researchers have determined that the price of housing is higher in metropolitan areas that generate a significant amount of high-quality innovation. “We based our research on the theory that the quality of innovation centered in specific metropolitan areas support a higher rate of wealth and income growth which allow for higher house price appreciation,” said Yaoyi Xi, professor of finance at the Fowler College of Business at San Diego State University.
Xi was one of four researchers who studied how the number of high-quality innovations within a specific metropolitan area impacted the region’s housing costs. Xi, Eli Beracha of Florida International University, ZhaoZhao He of the University of New Hampshire, and M. Babajide Wintoki of the University of Kansas published their findings in the July 10, 2021 edition of The Journal of Real Estate Finance and Economics.
Yaoyi Xi is a finance professor at SDSU’s Fowler College of Business
The researchers defined a “high-quality innovation” by the number of citations each patent receives. For example, if a patent application for a new innovation cites data from a previously patented innovation, the previously patented innovation earns a citation.
Since there was very little previous research done to determine the correlation between innovation and real estate value, Xi and the other professors obtained a database listing all patents granted by the United States Patent and Trademark Office between 1926 and 2010 and the citations affiliated with those patents. In addition, they obtained a second database listing each “inventor” or patent applicants to determine their metropolitan area of residence.
After analyzing the databases, the researchers determined the five metropolitan areas with the greatest number of patents (Silicon Valley, Minneapolis-St. Paul, San Diego, Austin, Atlanta) and those with the fewest (Hot Springs, Arkansas; El Paso, Texas; Enid, Oklahoma; Hinesville, Georgia, Yuma, Arizona). They also noted that the five regions with the greatest number of patents had some of the highest priced housing markets in the nation.
The researchers next used information about the areas’ home prices, education levels, unemployment figures, and area/land constraints to develop a formula that incorporated these variables into their calculations. They wanted to determine if these factors may be additional influences on the correlation between housing prices and quality innovation.
After the final evaluation of the data, the researchers noted four possible indicators as to why the number of high-quality innovations may predict regional housing costs:
- Higher quality innovation attracts talented employees and entrepreneurs to the area, leading to increased job creation and recruiting.
- Wealthy investors supply additional capital to stimulation innovation. In the process, this encourages regional growth and infrastructure development.
- Home prices appreciate as a result of increased household wealth, driving up pricing as the demand for investment property increases.
- “Ample evidence” indicates that high-quality innovation is carried out by individuals with high levels of formal education who drive the demand for high-quality schools and other amenities. This usually results in higher residential property prices.
In their final analysis, the researchers found that when there was a significant number of high-quality innovations, home values increased substantially. This is particularly true during robust economic conditions and when there are constraints on the area that may inhibit physical growth. Further analysis indicated that this was not a bi-directional phenomenon — the cost of housing did not seem to have an impact on the number of high-quality innovations that were patented.
“Our findings suggest that high-quality innovation spurs job creation and is an effective predictor in the value of real estate within a specified metropolitan area,” said Xi. “Ours is the first study to establish this direct correlation and has implications for investors and the housing market dynamics.”
