Should You Ignore the Weather When Buying a New House or Car?
An NBER working paper (full PDF here) by Meghan R. Busse, Devin G. Pope, Jaren C. Pope, and Jorge Silva-Risso explores the role of projection bias when choosing a new car or house. It turns out that weather conditions are a huge factor when consumers are debating big purchases like houses or cars. The abstract:
Projection bias is the tendency to overpredict the degree to which one’s future tastes will resemble one’s current tastes. We test for evidence of projection bias in two of the largest and most important consumer markets – the car and housing markets. Using data for more than forty million vehicle transactions and four million housing purchases, we explore the impact of the weather on purchasing decisions. We find that the choice to purchase a convertible, a 4-wheel drive, or a vehicle that is black in color is highly dependent on the weather at the time of purchase in a way that is inconsistent with classical utility theory. Similarly, we find that the hedonic value that a swimming pool and that central air add to a house is higher when the house goes under contract in the summertime compared to the wintertime.
The researchers found that a 20-degree increase in temperature will result in an 8.5 percent increase in the share of convertible cars sold, even in the spring or fall season. This effect does not take place if the weather is already hot. While hot weather means more convertibles, snow gives cars with 4-wheel drive a boost: about 2 percentage points during snow storms with 10 inches of snow. As the authors write:
Our findings are significant for several reasons. First, the car and housing markets in and of themselves are large and important. Identifying, and potentially correcting, systematic errors in these markets can have valuable welfare implications. Perhaps more importantly, our results suggest that projection bias may be prevalent in other important decisions (getting married, choosing a job, etc.) that are similarly distinguished by having large stakes, state-dependent utility, and low-frequency decision-making.
Related: having a job interview on a rainy day can hurt your chances.