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A new study has found human feelings can accurately be expressed numerically and have more predictive power for how we behave than formal studies of socioeconomic factors like household income and employment status.

The study co-author Andrew Oswald, a professor of economics and behavioral science gathered information from nearly 700,000 people, who were asked annually over a three-decade period how they felt on a numerical scale about their job, spouse, health and home. Using the data collected, researchers constructed statistical models to show how people felt and the actions they took as a result of their reported feelings. The study found that ratings of life satisfaction had a direct linear (线性的) relationship to actions people subsequently take. Participants who rated their job satisfaction as a 2 out of 7 had a 25% probability of quitting their job. Those who rated a 6 out of 7 had only a 10 percent probability of quitting. The same was true across other measures like marriage, health and housing.

Previous research has also shown data about feelings predict human outcomes, but not in such a linear fashion; the degree of satisfaction served as a good predictor of future actions. Additionally, economists have previously been critical of feelings data because they considered them unscientific and unreliable. But this study shows socioeconomic factors have a lesser probability of predicting human behavior than data on feelings.

Though the study shows numbers can quantify feelings, researchers are still a bit confused as to why estimates of seemingly subjective feelings can be such good predictors of future actions. According to Oswald, a number of factors could be at play. Humans are very experienced in comparative thinking and are able to scale their own life satisfaction against that of their neighbors. We’re also accustomed to using measuring devices for other aspects of life like temperature, distance and weight, so it shouldn’t be too surprising that we’re able to measure our feelings in a similarly accurate way. Another study co-author Caspar Kaiser says that it may also be because we communicate our feelings and do it in a scaled fashion every day. This could be why it comes out in the data more accurately than in objective markers.

Ori Heffetz, an economics professor who was not involved in the study, says that this research shows feelings data shouldn’t be underestimated even if they’re more difficult to study. “Scientists who ignore this do so at their own risk,” he says.

Looking ahead, Kaiser hopes this same data can be studied in lower-income countries so that it can be applied universally to places with varied levels of economic development. But more than anything else he’s interested in studying why feelings work so well.