A monthly budget is somewhat predictable and likely includes payments for housing, food, transit, utilities, and other regular expenses. But atypical costs—such as car and home repairs and medical emergencies—can throw off people’s budgets in a big way. In a 2013 report by personal finance app HelloWallet, such costs were the most common reason Americans tapped into retirement savings for early withdrawals, leading to an annual $7 billion in 401(k) penalties.
But people’s spending predictions can be greatly improved to include atypical outlays, according to research by Texas A&M’s Ray Charles “Chuck” Howard, University of British Columbia’s David J. Hardisty, Chicago Booth’s Abigail Sussman, and University of St. Andrews’s Marcel F. Lukas.
In North America, at least 63 percent of smartphone users have at least one financial or budgeting app installed. Yet while people budget for regularly occurring items, unexpected or unusual costs lead many to turn to payday loans, credit cards, and their retirement accounts for ready cash. This can greatly damage their finances, and some people get stuck in a debt trap.
To learn more about spending predictions, the researchers conducted 10 experiments involving more than 6,000 people in three countries. In one, they surveyed close to 200 members of a Canadian credit union, asking them to predict their weekly spending over five weeks. At the end of each week, they asked the participants how much they actually spent. In the first month, the researchers find, the participants underestimated spending by $100 a week.
When the fifth week rolled around, the researchers changed tactics to see if they could improve the participants’ accuracy. They split the participants randomly into two groups. Those in the first were told to estimate their spending in the same way as in the previous four weeks, but the second group was asked to consider three reasons why their spending for the following week might be different from usual.
Over a series of five weeks, participants in an experiment who were asked to predict their weekly expenses regularly underestimated their spending. But when then prompted to consider the possibility of atypical expenses, they came closer to predicting their actual expenses.
At the end of the final week, the people in the first group underestimated their spending just as before. Those in the second group, however, considered one-off expenses they might face, such as a longer-than-typical car trip, a birthday gift for a relative, or new work clothes. Their estimates came within $7 of what they actually spent.
The researchers also asked the participants about their confidence in their predictions, their savings goals, and their general optimism, theorizing that these could affect the estimates. However, they find no correlation between predictions and any of those things, providing further support to the notion that being prompted to consider atypical expenses led to participants’ improved spending forecasts.
Subsequent experiments reinforced this finding. The researchers observed more accurate predictions even when more than 1,700 participants in the United Kingdom were asked to consider just one different expense that might occur. Those who considered this predicted their spending within about 2 percent of the actual outlays, while a control group’s estimates undershot by 32 percent.
And when participants were asked to predict either three or 10 potentially different one-off expenses, those who considered 10 items went on to make the most accurate spending predictions—demonstrating that the more items considered, the more effective the practice.
Financial-literacy organizations might benefit from adding the unusual-expenses prompt to their repertoire, the researchers suggest, noting that companies in the fintech sector developing budgeting apps could leverage the findings to help users set more realistic budgets.
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