Automation, Firms, and Labor Markets
Tuesday, Jan. 5, 2021 3:45 PM - 5:45 PM (EST)
- Chair: James Bessen, Boston University
Displacement and Inequality: Task Structure of Production and Changes in United States Wage Structure
AbstractThis paper develops a framework that links automation to inequality. At the center of the framework is the substitution of machines for tasks brought about by the automation process. Critically, workers have different competitive advantages and specialize in different industries and occupations. The pattern of automation then creates downward pressure on the wages of different groups of workers and shapes the structure of wages. The theoretical framework characterizes the direct and the general equilibrium (indirect) effects of automation. The general equilibrium effects involve, for example, the fact that once the tasks performed by some workers are automated, these workers compete for jobs previously performed by other workers. We then derive a flexible framework based on this theoretical model for estimating the extent of inequality created by automation. Our empirical framework flexibly includes the standard forces emphasized in the literature, including skill-biased technological change, gender-biased technological change, and changes in experience premia as well as inter-industry wage premia that may be time-varying. We estimate this model on data on the evolution of wages by detailed demographic groups. Our estimates indicate that the majority of the changes in the US wage structure are due to automation. For example, more than 80% of the changes in the college-high school wage premia are explained by automation patterns, and very little is accounted for by standard skill-biased technological change channel.
Robots and Firms
AbstractWe study the microeconomic implications of robot adoption using a rich panel data-set of Spanish manufacturing firms over a 27-year period (1990-2016). We provide causal evidence on two central questions: (1) Which firm characteristics prompt firms to adopt robots? (2) What is the impact of robots on adopting firms relative to non-adopting firms? To address these questions, we look at our data through the lens of recent attempts in the literature to formalize the implications of robot technology. As for the first question, we establish robust evidence for positive selection, i.e., ex-ante better performing firms (measured through output and labor productivity) are more likely to adopt robots. On the other hand, conditional on size, ex-ante more skill-intensive firms are less likely to do so. As for the second question, we find that robot adoption generates substantial output gains in the vicinity of 20-25% within four years, reduces the labor cost share by 5-7%-points, and leads to net job creation at a rate of 10%. These results are robust to controlling for non-random selection into robot adoption through a difference-in-differences approach combined with a propensity score reweighting estimator. To further validate these results, we also offer structural estimates of total factor productivity (TFP) where robot technology enters the (endogenous) productivity process of firms. The results demonstrate a positive causal effect of robots on productivity, as well as a complementarity between robots and exporting in boosting productivity.
University of British Columbia
- J2 - Demand and Supply of Labor
- O3 - Innovation; Research and Development; Technological Change; Intellectual Property Rights