Academic Migration and Academic Networks: Evidence from Scholarly Big Data and the Iron Curtain

Abstract

Iron Curtain and Big Data are two words usually used to denote completely different eras. Yet, the context the former offers and the rich data source the latter provides, complement each other in a perfect manner enabling the causal identification of the effect of networks on migration. Using Microsoft Academic Knowledge Graph, a scholarly big data source, mapping of academics' networks is achieved and information about the size and quality of their their co-authorships, by location is achieved. Focusing on academics from Eastern Europe (henceforth EE) from 1980-1988 and their academic networks (1980-1988), I investigate the effect of academic network characteristics, by location, on the probability to migrate post the fall of the Berlin Wall in 1989 and up to 2003, marking the year many EE countries held referendums or signed treaties to join the EU. The timing offers unique context in which there was no anticipation of the fall of the Eastern Bloc and together with the data that offers unique rich information, identification is achieved. Approximately 30k academics from EE were identified, from which 3% were migrants. Using this context and this data, I test the assumption that the effect of the size and quality pre 1989 academic networks, classified by location home, destination and foreign, on the probability to migrate, goes through two different and distinct channels: the cost and signalling channels, respectively. The cost channel is how the network characteristic reduces or increases the cost of migration and thus acting as a facilitator or a de-facilitator of migration. The signal channel on the other hand in which the network characteristic serves as a signal for the academic himself and his quality and his potential contribution and addition to the new host institution, thus also serving as a facilitator or a de-facilitator of migration. From OLS, Logit and MNL regressions, I find indeed that the cost channel operates through network size, in which an increase in home network size reduces the probability to migrate by 0.1-0.05pp, with a stronger effect for out of EE migration, resembling an increase in cost of migration as more connections are left at home. Following the same logic, an increase in destination and foreign network size increase the probability to migrate by 7.7pp and 0.1pp respectively. An increase in network quality, proxied through the average rank and citations of the co-authors, across all locations, increases significantly the probability to migrate, however, the effect is not economically significant. I also find evidence that confirms that size matters more than quality, which is argued to be specific to this context and how academics from EE were strongly isolated from the rest of the academic world. I find heterogeneous effects by field of study that align with previous lines of research. I find that field that were more reputable in the region, like Mathematics, the signalling channel outweighs the cost channel in some scenarios, and other fields with larger network and language barriers and less quality signalling, like Social Sciences and Arts and Humanities, foreign networks are much more important as a facilitator of migration.