MACHINE LEARNING’S IMPACT ON OCCUPATIONAL WAGE: AN ANALYSIS OF AN OCCUPATIONS SUITABILITY FOR MACHINE LEARNING AND

Abstract

Does an occupation's SML value impact an occupations wage growth in any significant way? This paper builds off of the SML metric established by previous literature and uses standard time series linear regressions to determine whether there is a causal relationship between an occupations suitability for machine learning and its wage growth. Using the SML metric previously established along with data from the U.S. Bureau of Labor Statistics we look at the wages of 964 occupations over 18 years as well as each occupation's corresponding SML value. We use this data to predict whether the growth in occupational wages is statistically significantly impacted by that occupations SML value. This paper's results indicate that there is a causal relationship between the variables with a high degree of certainty.