Big Data Investment, Skills, and Firm Value

Analysis of how labor market factors have shaped early returns on big data investment using a new data source---the LinkedIn skills database--- underscores the importance of geography, corporate investment, and skill acquisition channels for explaining productivity growth differences during the spread of new information technology innovations.

Abstract

This paper considers how labor market factors have shaped early returns to investment in big data technologies. It tests the hypothesis that returns to early investments in Hadoop — a key big data infrastructure technology — have been concentrated in select labor markets due to the importance of aggregate corporate investment levels within a labor market for producing a supply of complementary technical skills during the early stages of technology diffusion. The analysis uses a new data source — the LinkedIn skills database — enabling direct measurement of firms’ investments into emerging technical skills such as Hadoop, Map/Reduce, and Apache Pig. Productivity estimates indicate that from 2006 to 2011, firms’ Hadoop investments were associated with 3% faster productivity growth, but only for firms a) with significant existing data assets and b) in labor networks characterized by significant aggregate Hadoop investment. Evidence for the importance of labor market concentration disappears for investments in mature data technologies, such as SQL-based databases, for which the skills are diffused and readily available through universities and other channels. These findings underscore the importance of geography, corporate investment, and channels for technical skill acquisition for explaining differences in productivity growth rates across labor markets during the spread of new IT innovations.