To mitigate asymmetric information in the consumer lending market, lenders typically rely on credit information to grant loans. In this paper, we study how the digitization of employment and income verification promotes inclusive access to credit by further reducing asymmetric information over...

Machine learning tools such as neural networks are increasingly applied in marketing and economics to learn complex relations in data. The learned relations allow machines to perform various tasks, such as recognizing objects from images or recognizing emotions from speech. This paper explores...

Abstract We study how receiving a bonus changes the demand for auto loans and the risk of future delinquency. Unlike traditional consumer products, auto loans have a long-term impact on consumers' financial state because of the monthly payment obligation. Using a large consumer panel data set of...

This paper empirically investigates how marketers can retarget consumers who have searched online but did not purchase, based on their search behaviors. To infer the relationship between search activities and preferences, we estimate a structural search model that characterizes the consumer...

This paper shows that the introduction of the "gig-economy" changes the way employees respond to job loss. Using administrative data on unemployment insurance (UI) claims matched with the credit profiles of individuals in the U.S., we show that laid-off employees with access to Uber are less...