This paper documents the pervasiveness of job polarization in 16 Western European countries over the period 1993–2010. It then develops and estimates a framework to explain job polarization using routine-biased technological change and offshoring. This model can explain much of both total job polarization and the split into within-industry and between-industry components.

The structure of employment is always changing, and economists are always trying to understand those changes. In the 1990s the idea of skill-biased technological change (SBTC) was used to understand the shift in employment toward more educated workers (see David H. Autor and Lawrence F. Katz 1999, for a survey). However, in recent years, it has become appar ent that a more nuanced approach is needed. The idea of SBTC might lead one to predict a uni form shift in employment away from low-skilled and toward high-skilled occupations, but studies for the United States (Autor, Katz, and Melissa S. Kearney 2006) and the United Kingdom (Goos and Manning 2007) have shown that there is growth in employment in both the high est-skilled (professional and managerial) and lowest-skilled (personal services) occupations, with declining employment in the middle of the distribution (manufacturing and office jobs). This is what Goos and Manning (2007) term job polarization (although see the introduc to Goos and Manning 2007 for antecedents of these ideas). There are several hypotheses about the rea sons for job polarization. First, the routiniza tion hypothesis (first put forward by Autor, Frank Levy, and Richard Murnane 2003) sug gests that the effect of technological progress is to replace routine labor which tends to be clerical and craft jobs in the middle of the wage distribution. Second, there is the view that globalization in general, and offshoring in par ticular, is an important source of change in the job structure in the richest countries (see, for example, Alan S. Blinder 2007). Third, there may be a link between job polarization and

We answer three core questions about the hypothesized role of newly emerging job categories (“new work”) in counterbalancing the erosive effect of task-displacing automation on labor demand: what is the substantive content of new work, where does it come from, and what effect does it have on labor demand? We construct a novel database spanning eight decades of new job titles linked to U.S. Census microdata and to patent-based measures of occupations’ exposure to labor-augmenting and labor-automating innovations. The majority of current employment is in new job specialties introduced since 1940, but the locus of new-work creation has shifted from middle-paid production and clerical occupations over 1940–1980 to high-paid professional occupations and secondarily to low-paid services since 1980. New work emerges in response to technological innovations that complement the outputs of occupations and demand shocks that raise occupational demand. Innovations that automate tasks or reduce occupational demand slow new-work emergence. Although the flow of augmentation and automation innovations is positively correlated across occupations, the former boosts occupational labor demand while the latter depresses it. The demand-eroding effects of automation innovations have intensified in the past four decades while the demand-increasing effects of augmentation innovations have not.

We estimate the impact of firm-level automation on individual worker outcomes by combining Dutch microdata with a direct measure of automation expenditures covering all private nonfinancial sector firms. Using a novel difference-in-differences event-study design leveraging lumpy investment, we find that automation increases the probability of incumbent workers separating from their employers. Workers experience a five-year cumulative wage income loss of 9% of one year’s earnings, driven by decreases in days worked. These adverse impacts of automation are larger in smaller firms, and for older and middle-educated workers. By contrast, no such losses are found for firms’ investments in computers.