We model the competition between digital forms of fiat money and private digital money (PDM). Countries strategically digitize their fiat money -- upgrading existing or launching new payment systems (including CBDCs) -- to enhance adoption and counter PDM competition. A pecking order emerges:...

We model platform competition with endogenous data generation, collection, and sharing, thereby providing a unifying framework to evaluate data-related regulation and antitrust policies. Data are jointly produced from users' economic activities and platforms' investments in data infrastructure....

We introduce a general approach for analyzing large-scale text-based data, combining the strengths of neural network language processing and generative statistical modeling to create a factor structure of unstructured data for downstream regressions typically used in social sciences. We generate...

We conceptually identify and empirically verify using marketplace lending data the features distinguishing FinTech platforms from non-financial platforms: (i) Long-term contracts introducing default risk at both the individual and platform levels; (ii) Lenders' investment diversification to...

The rise of super-app digital wallets provides not only a conduit to banks but also internal payment options, including Buy-Now-Pay-Later (BNPL). We examine, for the first time, transactions matched with merchant and consumer information, from a leading e-wallet super-app, and complement the...

We develop a dynamic asset pricing model of cryptocurrencies/tokens that allows users to conduct peer-to-peer transactions on digital platforms. The equilibrium value of tokens is determined by aggregating heterogeneous users' transactional demand rather than discounting cash flows, as is done...