How does financial market concentration affect capital allocation? We propose a complete-markets model in which real investment and financial price impact are jointly determined in general equilibrium. We identify a two-way feedback mechanism whereby price impact induces misallocation and misallocation raises price impact. The mechanism is stronger if productivity is low or productivity dispersion is high. Given rising dispersion, the model can rationalize trends in corporate discount rates, cash holdings, investment, asset prices, and capital reallocation over the last two decades, even when market concentration is relatively stable. Overall, our findings suggest that financial market concentration may hamper allocative efficiency.

We examine the pecuniary externalities that arise when active fund manager compensation contracts have common components. This commonality in the compensation structure and loadings on each component across funds reduces asset price informativeness, amplifies the distortions from active managers’ benchmark-hedging demand, and lowers the price of risk in financial markets. This is because contract commonality distorts investors’ capital allocation to active management, and active managers’ information acquisition and trading decisions. From a normative perspective, contract commonality increases the rigidity of the active industry size and performance-based fee. As a result, they do not vary enough with financial market conditions compared with a Planner’s economy. Quantitatively, an increase in asset payoff uncertainty increases the size and performance-based fee twice as much in the Planner economy compared with the decentralized economy. From a positive perspective, contract commonality contributes to the inconsistency of several widely adopted measures of active manager skill.

We examine how portfolio regulations affect risk sharing between financial institutions with market power. Unconstrained access to complete markets permits flexible exploitation of market power and induces inefficient risk sharing. Appropriate portfolio restrictions counteract this, improving liquidity and risk sharing by bundling securities with offsetting strategic incentives. However, excessive regulation can be counterproductive, destroying gains from trade. An application of our theory shows that cross-asset spillovers are critical for policy evaluation: in general equilibrium, risk sharing can improve even if certain asset-specific liquidity measures deteriorate. We also discuss the effects of asymmetric regulation for different institutions.

China’s economic model involves regular and intensive government interventions in financial markets, while Western policymakers often refrain from substantial interventions outside crisis periods. We develop a theoretical framework to rationalize the approaches of both China and the West to managing the financial system as being optimal given the differences in their respective economies. In this framework, a government leans against trading of noise traders but at the expense of introducing policy noise to the market. Our welfare analysis shows that under certain underlying economic conditions, the optimal government policy induces a government-centric equilibrium, in which government intervention is so intensive that all investors choose to acquire private information about policy noise rather than fundamentals. This policy regime characterizes China’s approach with financial stability prioritized over other policy objectives.

We examine decentralization of digital platforms through tokenization as an innovation to resolve the conflict between platforms and users. By delegating control to users, tokenization through utility tokens acts as a commitment device that prevents a platform from exploiting users. This commitment comes at the cost of not having an owner with an equity stake who, in conventional platforms, would subsidize participation to maximize the platform's network effect. This trade‐off makes utility tokens a more appealing funding scheme than equity for platforms with weak fundamentals. The conflict reappears when nonusers, such as token investors and validators, participate on the platform.

This paper develops a model with a tractable log‐linear equilibrium to analyze the effects of informational frictions in commodity markets. By aggregating dispersed information about the strength of the global economy among goods producers whose production has complementarity, commodity prices serve as price signals to guide producers' production decisions and commodity demand. Our model highlights important feedback effects of informational noise originating from supply shocks and futures market trading on commodity demand and spot prices. Our analysis illustrates the weakness common in empirical studies on commodity markets of assuming that different types of shocks are publicly observable to market participants.

We develop a model to analyze information aggregation and learning in housing markets. Households enter a neighborhood by buying houses and consuming each other’s final goods. In the presence of pervasive informational frictions, housing prices serve as important signals to households and capital producers about the neighborhood’s economic strength. Our model provides a novel amplification mechanism in which noise from housing markets propagates throughout the local economy via learning because of the complementarity in households’ decisions, distorting migration into the neighborhood and the supply of capital and labor. We provide consistent evidence based on the recent U.S. housing cycle.

By exploiting variation in state capital gains taxation as an instrument, we analyze the economic consequences of housing speculation during the U.S. housing boom in the 2000s. We find that housing speculation, anchored, in part, on extrapolation of past housing price changes, led not only to greater price appreciation, economic expansions, and housing construction during the boom in 2004–2006 but also to more severe economic downturns during the subsequent bust in 2007–2009. Our analysis supports supply overhang and local household demand as two key channels for transmitting these adverse effects.

China's gradualistic approach allowed the government to learn how the economy reacts to small policy changes, and to adjust its reforms before implementing them in full. With fully developed financial markets, however, private actors may front-run future policy changes, making it impossible to implement policies gradually. With financial markets, the government faces a time-inconsistency problem. The government would like to commit to a gradualistic approach, but after it observes the economy's quick reaction, it has no incentive to implement its policies in small steps.