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on Network Economics |
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Issue of 2019‒05‒06
two papers chosen by Pedro CL Souza Pontifícia Universidade Católica do Rio de Janeiro |
| By: | Bernstein, Shai (Stanford University GSB and NBER); Diamond, Rebecca (Stanford University GSB and NBER); McQuade, Timothy James (Stanford University GSB); Pousada, Beatriz (?) |
| Abstract: | We characterize the contribution of immigrants to US innovation, both through their direct productivity as well as through their indirect spillover effects on their native collaborators. To do so, we link patent records to a database containing the first five digits of 160 million of Social Security Numbers (SSN). By combining this part of the SSN together with year of birth, we identify whether individuals are immigrants based on the age at which their Social Security Number is assigned. We find that over the course of their careers, immigrants are more productive than natives, as measured by number of patents, patent citations, and the economic value of these patents. Immigrant inventors are more likely to rely on foreign technologies, to collaborate with foreign inventors, and to be cited in foreign markets, thus contributing to the importation and diffusion of ideas across borders. Using an identification strategy that exploits premature inventor deaths, we find that immigrant collaborators create especially strong positive externalities on the innovation production of natives, while natives create especially large positive externalities on immigrant innovation production, suggesting that combining these different knowledge pools into inventor teams is important for innovation. A simple decomposition suggests that despite immigrants only making up 16% of inventors, they are responsible for 30% of aggregate US innovation since 1976, with their indirect spillover effects accounting for more than twice their direct productivity contribution. |
| Date: | 2018–11 |
| URL: | http://d.repec.org/n?u=RePEc:ecl:stabus:3748&r=all |
| By: | Dariel, Aurelie (New York University, Abu Dhabi); Riedl, Arno (Maastricht University); Siegenthaler, Simon (University of Texas at Dallas) |
| Abstract: | Information asymmetries can prevent markets from operating efficiently. An important example is the labor market, where employers face uncertainty about the productivity of job candidates. We examine theoretically and with laboratory experiments three key questions related to hiring via referrals when employees have private information about their productivity. First, do firms use employee referrals when there are social ties between a current employee and a future employee? Second, does the existence of social ties and hiring through employee referrals indeed alleviate adverse selection relative to when social ties do not exist? Third, does the existence of social ties have spill-over effects on wages and hiring in competitive labor markets? The answers to all three questions are affirmative. However, despite the identified positive effect of employee referrals, hiring decisions fall short of the (second-best) efficient outcome. We identify risk aversion as a potential reason for this. |
| Keywords: | adverse selection, labor market, employee referrals, social networks |
| JEL: | C92 D82 D85 E20 |
| Date: | 2019–04 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp12287&r=all |