The authors simultaneously address three basic issues regarding the corporation: the optimal scope of operation, the optimal financial structure, and the relationship between these two. The starting point is that financial structure serves as a bonding device on the managers' self-interest behavior. The effectiveness of this bonding depends on the distribution of the firm's future cash flow, which in turn depends on the firm's scope. The authors' theory also links the firm's investment decisions to its operation scope. As empirical implications, the theory reconciles the failure of the 1960s U.S. conglomerates with the success of the Japanese keiretsu.
When a group of investors with dispersed private information jointly invest in a risky project, how should they divide the project's profit? We show that a simple contract dividing profits in proportion to investors' risk tolerances may facilitate information aggregation by altering investors' risk‐taking incentives when they decide on how investment strategies respond to private information. Our results provide a contracting‐based approach for information aggregation, which is an alternative to learning from endogenous market variables (e.g., prices) via contingent schedules as seen in well‐known rational expectations equilibrium models.
I study whether the capital gains tax is an impediment to selling by some investors and if so, to what degree associated delayed selling affects stock prices. I find that selling decisions by institutions serving tax‐sensitive clients are sensitive to cumulative capital gains, a pattern not observed for institutions with predominantly tax‐exempt clients. Moreover, tax‐related underselling impacts stock prices during large earnings surprises for stocks held primarily by tax‐sensitive investors. The corresponding price reactions are less negative (more positive) with higher cumulative capital gains. This price pressure pattern is more severe when arbitrage is more costly.
Dealers in the over‐the‐counter municipal bond market form trading networks with other dealers to mitigate search frictions. Regulatory data show that this network has a core‐periphery structure with 10 to 30 hubs and over 2,000 peripheral broker‐dealers in which bonds flow from periphery to core and partially back. Central dealers charge investors up to double the round‐trip markups compared to peripheral dealers. In turn, central dealers provide immediacy by matching buyers with sellers more directly and prearranging fewer trades, especially during stress times. Investors thus face a trade‐off between execution cost and speed, consistent with network models of decentralized trade.
The acceleration of the U.S. productivity growth in the late 1990s suggests a significant advance in technological innovation, making the perceived probability of entering a “new economy” ever increasing. Based on macroeconomic data, we identify a Bayesian investor's belief evolution when facing a possible structural break in the economy. We show that such belief evolution plays a significant role in explaining both the stock market boom and crash during 1998 to 2001. We conclude that a rational investor's uncertainty about the future of the U.S. economy provides an alternative explanation for the late 1990s stock market “bubble.”
The acceleration of the U.S. productivity growth in the late 1990s suggests a significant advance in technological innovation, making the perceived probability of entering a “new economy” ever increasing. Based on macroeconomic data, we identify a Bayesian investor's belief evolution when facing a possible structural break in the economy. We show that such belief evolution plays a significant role in explaining both the stock market boom and crash during 1998 to 2001. We conclude that a rational investor's uncertainty about the future of the U.S. economy provides an alternative explanation for the late 1990s stock market “bubble.”