Knowledge spillovers—non-rival information goods with the potential to be adapted by neighboring producers—have been the focus of a large body of empiri- cal and theoretical economic research. However, the majority of existing work only examines two industries (academic and patent citation networks), and only focuses on estimating the effects of individual geopolitical units on knowledge spillovers. In this study, I use a regression framework to disentangle the effects of various levels of geopolitical colocation and geographic separation on knowledge spillovers within the recorded music industry. To estimate knowledge spillovers, I use a traditional measure of artist similarity and I construct a novel measurement from a compari- son across artists' Wikipedia pages. I find that colocation within geopolitical units increases knowledge transfers substantially, with the effects of city and country colocation being larger than the effect of state colocation. These effects are more pronounced than the effect of pure geographic separation, and they are weaker than those observed by comparable studies in patent-citation networks.
"},{"label":"Degree","value":["Bachelor of Arts with Departmental Honors"]},{"label":"Administrative Note","value":"2017