We show that differential IT investment across cities is a key driver of job and wage polarization since the 1980s. Using a novel dataset, we establish two stylized facts: IT investment is highest in firms in large cities; the decline in routine cognitive occupations is most prevalent in large cities. We propose a mechanism where the substitution of routine workers by IT leads to higher IT adoption in large cities due to higher cost of living and wages. We estimate a spatial equilibrium model to trace out the effects of IT on the labor market between 1990 and 2015. We find that the fall in IT prices explains 28% of the reallocation of employment away from routine cognitive towards non-routine cognitive jobs. The decline in IT prices can also explain 50% of the rising wage gap between routine and non-routine cognitive jobs. Moreover, our estimates show that the impact of IT is uneven across space. Expensive locations have seen a stronger displacement of routine cognitive jobs and a larger widening of the wage gap between routine and non-routine cognitive jobs.

Over the last two decades labor market dynamism, measured by flows of workers between employers, declined substantially in the US. During the same period employment polarized into low and high skill jobs. This paper shows that the two trends are linked. First, I provide a framework to study employment and worker flows, where skill intensity of jobs and workers’ skills are complements. I analyze within this framework the effects of routine-biased technological change and the increasing supply of college graduates on labor market flows. When routine-biased technological change displaces mid-skill jobs, it lowers the opportunity to move up to better jobs for low-skilled workers. Similarly, high skilled workers have less opportunity to take stepping stone jobs and are more likely to start employment further up the job ladder, reducing the frequency of transitions between employers. The rising share of college graduates puts further pressure on labor markets by increasing competition for jobs from top to bottom. In equilibrium workers trade down to jobs with lower skill intensity to gain employment, but find it harder to move up as they are competing with more highly educated workers. I quantitatively assess whether such mechanisms contribute to the fall in labor market dynamism, by estimating the model using data on labor market flows. I find that routine-biased technological change accounts for 40% of the decline in job-to-job mobility.