Barometric Models

Of course, the speculative run-up in housing prices, after peaking in 2006, culminated in unprecedented price declines over the next two years of 30 to 50 percent. Why did so many home buyers, homeowners, lenders, and financial institutions believe that housing prices could go nowhere but up? Simple psychology accounts for a large part of the answer. Such beliefs are supported by a strong (often unconscious) bias toward overoptimism. According to surveys taken over the last 20 years, homeowners report that they expect housing prices to increase in the future by some 10 percent per year. These predictions have been very stable—before and during the price run-up and even after housing prices plunged. Moreover, individuals selectively cling to reasons—more qualified buyers, high demand in growing cities, the scarcity of land and housing in the most desirable locations—that support these beliefs, while overlooking or dismissing disconfirming evidence. To sum up, the way to overcome these psychological biases is to keep firmly in mind the 50-year “big picture” of house price movements.

Barometric models search for patterns among different variables over time. Consider a firm that produces oil drilling equipment. Management naturally would like to forecast demand for its product. It turns out that the seismic crew count, an index of the number of teams surveying possible drilling sites, gives a good indication as to changes in future demand for drilling equipment. For this reason, we call the seismic crew a leading indicator of the demand for drilling equipment.

Economists have identified many well-known leading indicators. The number of building permits lead the number of housing starts. Stock market indices (such as the Dow Jones Industrial Average) indicate future increases and decreases in economic activity (expansions or recessions). Such indicators, however, are not without certain problems.

1.Leading indicators are not always accurate. According to one humorous economic saying, declines in the stock market have predicted 14 of the last 8 recessions. 2.The amount of time between the change in the leading indicator and the change in the forecasted series varies. Leading indicators may say a change is coming, but they often cannot say exactly when. 3.The change in the leading indicator rarely gives much information about the size of the change in the forecasted series.

Frequently, leading indicators are averaged to form a composite leading indicator. This helps eliminate some of the randomness and makes the indicator