Technological change and labor market inequality: A microeconometric perspective on selected issues

The relation between technological progress and inequality has a long tradition in economics, of which the most recent chapter concerns the increase in automation induced by the fall in computing prices. The greater automation of tasks shifts the demand for labor, reducing the demand for workers in activities that could be performed by machines. Di erent degree of complementarity between various types of labor and new technologies leads to changes in the wage distribution that favor high skilled workers. Both patterns received con rmation in some developed countries. Earlier studies show that technological progress induced a greater polarization of the labor market: average wages and employment grew disproportionately in occupations at the top and at the bottom of the income distribution. However, these analyses tend to focus on aggregate data, which limited the hypotheses to be tested. In this thesis, we contribute to the literature by analyzing the relationship between technological change and two labor market outcomes (wages and employment) using individual level data. Such data allow answering new questions. First, while literature indicates an increase in wage inequality between occupations, we analyze whether a similar process is visible within occupations. Technological progress raised the demand for complex tasks, involving autonomy and creativity of the workers, where di erences in productivity among workers might be more notorious, leading in turn to greater wage inequality. Alternatively, technological progress could have also increase income inequality by promoting reallocation of workers, as workers changing jobs might lack the skills required to perform at the same level as more tenured workers. Using data from the European Union, we show that both mechanisms played a role. We observe that occupations where activities are complementary to machines present higher wage dispersion. Second, literature analyzed the polarization of labor demand employing aggregate data, which is agnostic on how workers adjust to the new labor market conditions. Workers in occupations more prone to automation might have experienced longer unemployment patterns and more job instability as a result of the need to adapt their skills to the new demand. Moreover, among older workers, changes in the labor demand could trigger movements out of the labor market. These considerations stand at the heart of the second part of the analysis, for which we employ panel data from Germany and Great Britain. The results indicate that concerns over more unstable careers and longer unemployment should be taken seriously. However, we did not nd evidence that workers in occupations more prone to automation modi ed their labor supply decisions as a result of technological change