This paper integrates elements from the theory of agency, the theory of property rights and the theory of finance to develop a theory of the ownership structure of the firm. We define the concept of agency costs, show its relationship to the ‘separation and control’ issue, investigate the nature of the agency costs generated by the existence of debt and outside equity, demonstrate who bears costs and why, and investigate the Pareto optimality of their existence. We also provide a new definition of the firm, and show how our analysis of the factors influencing the creation and issuance of debt and equity claims is a special case of the supply side of the completeness of markets problem.

This paper analyzes the survival of organizations in which decision agents do not bear a major share of the wealth effects of their decisions. This is what the literature on large corporations calls separation of “ownership ” and “control.” Such separation of decision and risk bearing functions is also common to organizations like large professional partnerships, financial mutuals and nonprofits. We contend that separation of decision and risk bearing functions survives in these organizations in part because of the benefits of specialization of management and risk bearing but also because of an effective common approach to controlling the implied agency problems. In particular, the contract structures of all these organizations separate the ratification and monitoring of decisions from the initiation and implementation of the decisions.

Implicit in the prices of traded financial assets are Arrow-Debreu prices or, with continuous states, the state-price density (SPD). We construct a nonparametric estimator for the SPD implicit in option prices and derive its asymptotic sampling theory. This estimator provides an arbitrage-free method of pricing new, complex, or illiquid securities while capturing those features of the data that are most relevant from an asset-pricing perspective, e.g., negative skewness and excess kurtosis for asset returns, volatility "smiles" for option prices. We perform Monte Carlo experiments and extract the SPD from actual S&P 500 option prices.

This paper investigates the empirical characteristics of investor risk aversion over equity return states by estimating a time-varying pricing kernel, which we call the empirical pricing kernel (EPK). We estimate the EPK on a monthly basis from 1991 to 1995, using S&P 500 index option data and a stochastic volatility model for the S&P 500 return process. We find that the EPK exhibits countercyclical risk aversion over S&P 500 return states. We also find that hedging performance is significantly improved when we use hedge ratios based the EPK rather than a time-invariant pricing kernel.

Do the implications for business cycle issues change when we switch from studying infinitely lived, representative-agent models to more sophisticated demographic structures with finitely lived agents? This article addresses that question by using a large, overlapping-generations model that is calibrated to U.S. demographic properties, microeconomic evidence, and National Income and Product Accounts. The finding is that the answers obtained are basically the same for the two kinds of models. The article also explores the relative volatility of hours across age groups, an issue that cannot be addressed by using the infinitely lived, representative-agent abstraction. P.O. Box 291, Minneapolis, MN 55480-0291, U.S.A. vr0j@tom.mpls.frb.fed.us. Parts of this research have been funded by the National Science Foundation. Some of the material in this article is from the second chapter of my dissertation. The help and patience of Ed Prescott and Finn Kydland are acknowledged. Thanks als...

We develop a framework for trading in compound securities: financial instruments that pay off contingent on the outcomes of arbitrary statements in propositional logic. Buying or selling securities -- which can be thought of as betting on or against a particular future outcome -- allows agents both to hedge risk and to profit (in expectation) on subjective predictions. A compound securities market allows agents to place bets on arbitrary boolean combinations of events, enabling them to more closely achieve their optimal risk exposure, and enabling the market as a whole to more closely achieve the social optimum. The tradeoff for allowing such expressivity is in the complexity of the agents' and auctioneer's optimization problems.

According to economic theory, supported by empirical and laboratory evidence, the equilibrium price of a financial security reflects all of the information regarding the security's value. We investigate the dynamics of the computational process on the path toward equilibrium, where information distributed among traders is revealed stepby -step over time and incorporated into the market price. We develop a simplified model of an information market, along with trading strategies, in order to formalize the computational properties of the process. We show that securities whose payoffs cannot be expressed as a weighted threshold function of distributed input bits are not guaranteed to converge to the proper equilibrium predicted by economic theory. On the other hand, securities whose payoffs are threshold functions are guaranteed to converge, for all prior probability distributions. Moreover, these threshold securities converge in at most n rounds, where n is the number of bits of distributed information. We also prove a lower bound, showing a type of threshold security that requires at least n/2 rounds to converge in the worst case.

We consider a permutation betting scenario, where people wager on the final ordering of n candidates: for example, the outcome of a horse race. We examine the auctioneer problem of risklessly matching up wagers or, equivalently, finding arbitrage opportunities among the proposed wagers. Requiring bidders to explicitly list the orderings that they’d like to bet on is both unnatural and intractable, because the number of orderings is n! and the number of subsets of orderings is 2 n!. We propose two expressive betting languages that seem natural for bidders, and examine the computational complexity of the auctioneer problem in each case. Subset betting allows traders to bet either that a candidate will end up ranked among some subset of positions in the final ordering, for example, “horse A will finish in positions 4, 9, or 13-21”, or that a position will be taken by some subset of candidates, for example “horse A, B, or D will finish in position 2”. For subset betting, we show that the auctioneer problem can be solved in polynomial time if orders are divisible. Pair betting allows traders to bet on whether one candidate will end up ranked higher than another candidate, for example “horse A will beat horse B”. We prove that the auctioneer problem becomes NP-hard for pair betting. We identify a sufficient condition for the existence of a pair betting match that can be verified in polynomial time. We also show that a natural greedy algorithm gives a poor approximation for indivisible orders.

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The role of ordinary options in facilitating the completion of securities markets is examined in the context of a model of contingent claims sufficiently general to accommodate the continuous distributions of asset pricing theory and option pricing theory. In this context, it is shown that call options written on a single security approximately span all contingent claims written on this security and that call options written on portfolios of call options on individual primitive securities approximately span all contingent claims that can be written on these primitive securities. In the case of simple options, explicit formulas are given for the approximating options and portfolios of options. These results are applied to the pricing of contingent claims by arbitrage and to irrelevance propositions in corporate finance. The role of complete contingent-claims markets in the optimal allocation of risk bearing is well known [Arrow (1964) and Debreu (1959)] and is the cornerstone of the economic theory of financial markets [Mossin (1977)]. As a consequence, it becomes important from a practical as well as a scholarly perspective to determine how complex the securities markets must be in order to achieve the allocational efficiencies of complete markets. The literature on this question has grown to be sizable. Much of this literature has been reviewed in John (1981, 1984) and Amershi (1985). A seminal contribution concerning the complexity of complete securities markets was made by Ross (1976) in analyzing the role of conventional options in com-