Technology Spatial Sorting and Job Polarization
Abstract Job polarization and wage inequality have increased substantially in the last four decades, being largely attributed to technological change. But there are two competing drivers: Skill Biased Technological Change (SBTC) leading to a rising college premium; and automation, leading to the replacement of routine occupations and the "hollowing out" of the income distribution. Using a novel data set on Information Technology (IT) adoption, we exploit geographical variation and the sorting patterns of differentially skilled workers to infer the main driver of job and wage polarization. We find strong evidence that there is more automation in big cities; big cities also have a disproportionate decrease in the share of routine cognitive jobs (clerical workers and low level white collar workers) We propose an economic mechanism where the substitutability of routine workers by IT leads to higher IT adoption in large cities than in small cities. Wages and productivity are higher in large cities, whereas technology prices are constant across cities. This technology also generates thick tails in the skill distribution in large cities.