This paper uses segmented dual-class shares of Chinese firms—A shares traded in mainland China by local investors and H shares traded in Hong Kong by foreign investors—to document a rich pattern in the differential reactions of local and foreign investors to analyst recommendations. This pattern reveals that social connections between analysts and investors affect investor reactions to analyst recommendations. Because of the investors’ differential reactions, analyst recommendations may exacerbate, rather than attenuate, the market segmentation between the two share classes. Received January 28, 2016; editorial decision October 23, 2016 by Editor Robin Greenwood.

We study rollover risk and collateral value in a dynamic asset pricing model with endogenous debt financing by extending the framework of Geanakoplos (2009) with a generic binomial tree and time-varying heterogeneous beliefs. Optimistic borrowers face rollover risk if the belief dispersion between the borrowers and the pessimistic lenders widens after interim bad news. We demonstrate the optimality of the maximum riskless short-term debt financing for optimistic borrowers even in the presence of the rollover risk. We also highlight the role of interim trading which, by allowing creditors to sell seized collateral to other optimists with saved cashes, boosts the asset's collateral value and equilibrium price.

In 2005–2008, over a dozen put warrants traded in China went so deep out of the money that they were almost certain to expire worthless. Nonetheless, each warrant was traded more than three times each day at substantially inflated prices. This bubble is unique in that the underlying stock prices make warrant fundamentals publicly observable and that warrants have predetermined finite maturities. This sample allows us to examine a set of bubble theories. In particular, our analysis highlights the joint effects of short-sales constraints and heterogeneous beliefs in driving bubbles and confirms several key findings of the experimental bubble literature.

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.

Our model shows that deterioration in debt market liquidity leads to an increase in not only the liquidity premium of corporate bonds but also credit risk. The latter effect originates from firms' debt rollover. When liquidity deterioration causes a firm to suffer losses in rolling over its maturing debt, equity holders bear the losses while maturing debt holders are paid in full. This conflict leads the firm to default at a higher fundamental threshold. Our model demonstrates an intricate interaction between the liquidity premium and default premium and highlights the role of short‐term debt in exacerbating rollover risk.

During the COVID-19 pandemic (2020-2022), Chinese cities witnessed a paradox: residential land and new house prices surged while transaction volumes plummeted. We attribute this to local governments’ active price management through supply controls, land acquisitions by local government financing vehicles (LGFVs), and limits on new home sales permits. Cities more dependent on land sales and land-backed debt before the pandemic experienced greater price increases and price–volume divergence, with LGFVs buying more land at higher prices than other buyers. These interventions helped sustain fiscal financing but deepened developers’ financial distress, revealing unintended consequences of local governments’ fiscal strategies during downturns.

To dampen trading frenzy in the stock market, the Chinese government tripled the stamp tax for stock trading on May 30, 2007. The greatly increased trading cost triggered a migration of the trading frenzy from the stock market to the warrant market, which was not subject to the stamp tax. This migration exacerbated a price bubble in the warrant market. Our analysis of investor account data uncovers not only large inflows of new investors to the warrant market but also greatly intensified trading by existing warrant investors. This episode exemplifies the so-called “whack-a-mole” game in financial regulations.

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.