With the rise of social media and streaming platforms, firms and brand-owners increasingly depend on influencers to attract consumers, who care about both common product quality and consumer-influencer interaction. Sellers thus compete in both influencer and product markets. As outreach and...

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 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 describe the landscape of taxation in the crypto markets, especially that concerning U.S. taxpayers, and examine how recent increases in tax scrutiny have led to changes in trading behavior by crypto traders. We predict under a simple theoretical framework and then empirically document that...

We introduce systematic tests exploiting robust statistical and behavioral patterns in trading to detect fake transactions on 29 cryptocurrency exchanges. Regulated exchanges feature patterns consistently observed in financial markets and nature; abnormal first-significant-digit distributions,...

We develop a new class of tree-based models (P-Tree) for analyzing (unbalanced) panel data utilizing global (instead of local) split criteria that incorporate economic guidance to guard against overfitting while preserving interpretability. We grow a P-Tree top-down to split the cross section of...

We build a two-country general equilibrium model to analyze the effects of cross-border data flows and pre-existing development gaps in data economies on each country's production and international trade. Raw data as byproducts of consumption can be transformed into various types of working data...