Knowledge that Transforms

[This paper investigates the role of ethnic matching between buyers and sellers in Singapore’s public housing market. We find that sellers sell homes in blocks with a high concentration of their own (other) ethnic group (s) at significant premiums (discounts). Chinese sellers earn 1.7% higher premiums when selling homes to Chinese buyers in high Chinese concentrations housing blocks, but Malay sellers accept 1.6% discounts from Malay buyers in the same blocks. We find that the high volume of within-ethnicity transactions with the price discounts is supported by the ethnic social networks, that is, through ethnicity-specialized real estate agents.]

We provide large-scale evidence on the occurrence and value of FinTech innovation. Using data on patent filings from 2003 to 2017, we apply machine learning to identify and classify innovations by their underlying technologies. We find that most FinTech innovations yield substantial value to innovators, with blockchain being particularly valuable. For the overall financial sector, internet of things (IoT), robo-advising, and blockchain are the most valuable innovation types. Innovations affect financial industries more negatively when they involve disruptive technologies from nonfinancial startups, but market leaders that invest heavily in their own innovation can avoid much of the negative value effect.ReceivedMay 31, 2017; editorial decision September 30, 2018 by Editor Andrew Karolyi.