>As well as looking at income, we rated skills on satisfaction, risk of automation, and breadth of applicability. Translation: We cooked up data by adding our

>As well as looking at income, we rated skills on satisfaction, risk of automation, and breadth of applicability. Translation: We cooked up data by adding our biases, but since we teamed up with a "data science fellow", thus our findings must scientific! This is worse than the average feel good pop pscyhology that appears in NYtimes. Reminds me of this good bit from an EJMR post: "Any approach that claims to recover the distribution of individual utility parameters from aggregate data based on arbitrary distributional and functional form assumptions is dubious at best,"