Andrea Morrison, Sergio Petralia, and Dario Diodato (2018), Papers in Evolutionary Economic Geography n.18.35
More than 30 million people migrated to the US between the 1850s and 1920s. In the order of thousands became inventors and patentees. Drawing on an original dataset of immigrant inventors to the US, we assess the city-level impact of immigrants patenting and their potential crowding out effects on US native inventors. Our study contributes to the different strands of literature in economics, innovation studies and economic geography on the role of immigrants as carriers of knowledge. Our results show that immigrants’ patenting is positively associated with total patenting. We find also that immigrant inventors crowd-in US inventors. The growth in US inventors’ productivity can be explained also in terms of knowledge spill-overs generated by immigrants. Our findings are robust to several checks and to the implementation of an instrumental variable strategy.
Ljubica Nedelkoska, Dario Diodato, and Frank Neffke (2018), CID Research Fellow and Graduate Student Working Paper n.93
The degree to which modern technologies are able to substitute for groups of job tasks has renewed fears of near-future technological unemployment. We argue that our knowledge, skills and abilities (KSA) go beyond the specific tasks we do at the job, making us potentially more adaptable to technological change than feared. The disruptiveness of new technologies depends on the relationships between the job tasks susceptible to automation and our KSA. Here we first demonstrate that KSA are general human capital features while job tasks are not, suggesting that human capital is more transferrable across occupations than what job tasks would predict. In spite of this, we document a worrying pattern where automation is not randomly distributed across the KSA space – it is concentrated among occupations that share similar KSA. As a result, workers in these occupations are making longer skill transitions when changing occupations and have higher probability of unemployment.