The Growing Importance of Decision-Making on the Job

Machines increasingly replace people in routine job tasks. The remaining tasks require workers to make open-ended decisions and to have “soft” skills such as problem-solving, critical thinking and adaptability. This paper documents growing demand for decision-making and explores the consequences for life-cycle earnings. Career earnings growth in the U.S. more than doubled between 1960 and 2017, and the age of peak earnings increased from the late 30s to the mid-50s. I show that a substantial share of this shift is explained by increased employment in decision-intensive occupations, which have longer and more gradual periods of earnings growth. To understand these patterns, I develop a model that nests decision-making in a standard human capital framework. Workers predict the output of uncertain, context-dependent actions. Experience reduces prediction error, improving a worker’s ability to adapt using data from similar decisions they have made in the past. Experience takes longer to accumulate in high variance, non-routine jobs. I test the predictions of the model using data from the three waves of the NLS. Life-cycle wage growth in decision-intensive occupations has increased over time, and it has increased relatively more for highly-skilled workers.