We study trading dynamics in an asset market where the quality of assets is private information and finding a counterparty takes time. When trading ceases in equilibrium as a response to an adverse shock to asset quality, a government can resurrect trading by buying up lemons which involves a financial loss. The optimal policy is centred around an announcement effect where trading starts already before the intervention for two reasons. First, delaying the intervention allows selling pressure to build up thereby improving the average quality of assets for sale. Secondly, intervening at a higher price increases the return from buying an asset of unknown quality. It is optimal to intervene immediately at the lowest price when the market is sufficiently important. For less important markets, when the shock to quality and search frictions are small, it is optimal to rely on the announcement effect. Here delaying the intervention and fostering the effect by intervening at the highest price tend to be complements.

Can securities be settled on a blockchain, and, if so, what are the gains relative to existing settlement systems? The main benefit of a blockchain is faster and more flexible settlement, whereas settlement fails need to be ruled out where participants fork the chain to cancel trading losses. With a proof-of-work protocol, the blockchain needs to restrict settlement speed through block size and time in order to generate transaction fees, which finance costly mining. Despite mining being a deadweight cost, our estimates for the U.S. corporate debt market yield net gains from a blockchain in the range of 1–4 bps. Received May 31, 2017; editorial decision May 29, 2018 by Editor Itay Goldstein.

Why do BigTech platforms introduce payment services? And do their users benefit? Digital platforms often run business models where activities on the platform generate data that can be monetized off the platform. The platform then trades off the value of such data against the cost that arises from subsidizing activities in order to compensate users for their loss of privacy. The way data interact with payments determines whether payments are introduced and how the introduction impacts users. When data help to provide better payments (data-driven payments), platforms have too little incentives to introduce payments, even though users benefit. Introduction is more likely when payments also generate additional data (payment-driven data), but the adoption of better payments may then hurt users.

This paper develops a micro-founded general equilibrium model of payments to study the impact of a central bank digital currency (CBDC) on intermediation of private banks. If banks have market power in the deposit market, a CBDC can enhance competition, raising the deposit rate, expanding intermediation, and increasing output. A calibration to the US economy suggests that a CBDC can raise bank lending by 1.57% and output by 0.19%. These crowding-in effects remain robust, albeit with smaller magnitudes, after taking into account endogenous bank entry. We also assess the role of a non-interest-bearing CBDC as the use of cash declines.