Learning With Friends: A Theoretical Note On The Role of Network Externalities In Human Capital Models For The New Industry

Abstract

Contemporary literature on how individuals learn in the 21st-century reveal critical differences from learning patterns in the mid-20th century–a period in which celebrated, pioneering works of Mincer, Becker and Ben-Porath on human capital were developed. Education and learning theories have evolved, but the prevailing human capital theories have not. Given continued technological progress, and the rise in available knowledge through the Internet, learning in networks is a distinct feature of the 21st-century industry. The connectivist theory of learning in the digital age is explored and substantiated. Using optimal control theory and dynamic optimisation, we define optimal conditions for knowledge generation and growth of learning networks. We find that knowledge per learner grows exponentially when the obsolescence rate of knowledge is less than the departure rate of learners from the learning network. We also find that a learning network will continue to grow as long as learners are sufficiently impatient and that technology sufficiently becoming obsolete faster. Furthermore, we show a positive relationship between the size of the network and wealth on knowledge. That is, as long as the remaining wealth on knowledge is increasing, the learning network will continue to grow over time. We present insights for policy consideration that address the necessary and sufficient conditions for sustained knowledge generation and the growth of the learning network.