After initial investments, relationship financiers routinely observe interim information about projects before continuing financing them. Meanwhile, entrepreneurs produce information endogenously and issue securities to incumbent insider and competitive outsider investors. In such persuasion games with differentially informed receivers and contingent transfers, entrepreneurs’ endogenous experimentation reduces insiders’ information monopoly but impedes relationship formation through an “information production hold-up.” Insiders’ information production and interim competition mitigate this hold-up and jointly explain empirical links between competition and relationship lending. Optimal contracts restore first-best outcomes using convertible securities for insiders and residuals for outsiders. Our findings are robust under various extensions and alternative specifications.

Abstract Persistent performance in venture capital is routinely interpreted as evidence for skill. We present a dynamic model of delegated investment with endogenous fund heterogeneity and deal flow, which generates performance persistence without skill differences and predicts mean reversion in long-term performance. Investors working with multiple funds use contingent payments and tiered contracts to induce proper project nurturing and managerial effort. Successful funds receive continuation contracts that tolerate investment failure and encourage innovation, and subsequently finance entrepreneurs through a path-dependent assortative matching favoring incumbents. Recent empirical findings corroborate the model’s general implications, and the economic mechanisms are robust to short-term contracting, endogenous bargaining, and double moral hazard issues.

ABSTRACT Economic interactions often involve sequential actions, observational learning, and contingent project implementation. We incorporate all‐or‐nothing thresholds in a canonical model of information cascades. Early supporters effectively delegate their decisions to a “gatekeeper,” resulting in unidirectional cascades without herding on rejections. Project proposers can consequently charge higher prices. Proposal feasibility, project selection, and information aggregation all improve, even when agents can wait. Equilibrium outcomes depend on crowd size, and project implementation and information aggregation achieve efficiency in the large‐crowd limit. Our key insights hold under thresholds in dollar amounts and alternative equilibrium selection, among other model extensions.

We model the competition between digital forms of fiat money and private digital money. Countries digitize their currencies–by upgrading existing or launching new payment systems (including CBDCs)–to compete with foreign fiat currencies and private digital money. A pecking order emerges: less dominant currencies digitize earlier, reflecting a first-mover advantage; dominant currencies delay digitization until they face competition; the weakest currencies forgo digitization. However, delayed digitization allows private digital money to gain widespread adoption, eventually weakening fiat money’s role. We highlight how geopolitical considerations, stablecoins, and interoperability between fiat and private digital money shape the dynamics of currency competition.

Blockchain technology provides decentralized consensus and potentially enlarges the contracting space through smart contracts. Meanwhile, generating decentralized consensus entails distributing information that necessarily alters the informational environment. We analyze how decentralization relates to consensus quality and how the quintessential features of blockchain remold the landscape of competition. Smart contracts can mitigate informational asymmetry and improve welfare and consumer surplus through enhanced entry and competition, yet distributing information during consensus generation may encourage greater collusion. In general, blockchains sustain market equilibria with a wider range of economic outcomes. We further discuss the implications for antitrust policies targeted at blockchain applications.Received May 31, 2017; editorial decision May 29, 2018 by Editor Itay Goldstein.

Abstract We explore the effects of a blockchain-based environmental monitoring technology on emissions. Our model of firm competition in the presence of regional regulators reveals that blockchain adoption reduces industrial pollution but triggers business relocation, creating trade-offs between local emission reduction and economic contraction. When pollution-induced social losses are highly dispersed across cities, a partial-adoption equilibrium fails to mitigate aggregate emissions because of the pollution leakage. We further present the first piece of empirical evidence corroborating model predictions, by taking advantage of a recent regulation change in China. The concentrations of SO2, NO2, and CO in blockchain-adopting cities are on average 16.6 percent, 7.9 percent, and 4.6 percent, respectively, lower than other cities. However, blockchain-based monitoring disproportionately hurts the industrial sector, and the average economic growth are 1.8–2.6 percent lower than other cities. Firms in adopting cities open more non-local plants to avoid regulation.

We model a dynamic economy with strategic complementarity among investors and study how endogenous government interventions mitigate coordination failures. We establish equilibrium existence and uniqueness, and we show that one intervention can affect another through altering the public information structure. A stronger initial intervention helps subsequent interventions through increasing the likelihood of positive news, but also leads to negative conditional updates. Our results suggest optimal policy should emphasize initial interventions when coordination outcomes tend to correlate. Neglecting informational externalities of initial interventions results in over- or under-interventions. Moreover, saving smaller funds disproportionally more can generate greater informational benefits at smaller costs.

We document that value-to-price, the ratio of Residual-Income-Model-based valuation to market price, subsumes the power of book-to-market ratio and many other value or quality measures in predicting stock returns. Long-short value-to-price portfolios hedge against momentum, revitalize the seemingly missing value premium over past decades, and generate significant returns after adjusting for common factors. The value-price-divergence (VPD) factor constructed from the average returns of these portfolios within small and big stocks is not spanned by these known factors. Max Sharpe ratio and constrained R-squared tests reveal that VPD is a better substitute for the traditional value factor and that a four-factor model using the VPD, market, momentum, and size factors outperforms most extant benchmarks in explaining the cross-section of expected equity returns, including value-to-price portfolios as test assets. The findings remain robust under alternative specifications of equity cost of capital.

Central banks around the world are exploring the possibility of Central Bank Digital Currencies (CBDCs) for retail and wholesale use. While no major economy is yet to fully introduced a CBDC, some countries have begun pilot programs. The purpose of this paper is to highlight the potential benefits and risks associated with CBDCs, including challenges and opportunities associated with proposed CBDC regulation in the United States and the European Union. The paper also discusses the CBDC landscape in Asia. It highlights some of the key findings of the research presented in this special issue on FinTech and CBDCs. Lastly, the paper offers thoughts for potential future research in areas such as the actual designs of CBDCs and their uses, ‘DeFi’ versus ‘CeFi’, their interoperability and stability, and concerns over cybercrime.

We describe the taxation landscape in the cryptocurrency markets, especially concerning U.S. taxpayers, and examine how recent increases in tax scrutiny have led to changes in crypto investors' trading behavior. We argue conceptually and then empirically document that increased tax scrutiny leads crypto investors to utilize conventional tax planning with tax-loss harvesting as an alternative to non-compliance. In particular, domestic traders increase tax-loss harvesting following the increase in tax scrutiny, and U.S. exchanges exhibit a significantly greater amount of wash trading. Additional findings suggest that broad-based and targeted changes in tax scrutiny can differentially affect crypto traders’ preference for U.S.-based exchanges. We also discuss other gray areas for tax regulation related to new crypto assets, such as Non-Fungible Tokens and Decentralized Finance protocols, that further highlight the importance of coordinating tax policy and other regulations.