Does Corporate Finance Frictions Matter for Asset Returns?
---- A General Equilibrium-Mechanism Design Approach
This article summarizes some of my recent research on the general equilibrium-mechanism design
approach to asset pricing. Much of my work on this topic is done with my coauthor, Rui Li.
The general theme of this line of research is to integrate “corporate finance” frictions into general
equilibrium asset pricing models and study the interaction of the two in a unified framework. By
corporate finance friction, I mean the presence of moral hazard, adverse selection, or lack of contract
enforcement, etc., which makes resource allocation among firms a nontrivial problem. 1 I will focus on a
particular type of friction, namely, separation of ownership and control.
Separation of ownership and control is one of the key organizational features of modern firms that
affect their investment, payout and financing decisions. Rui and I are interested in understanding how
this feature impacts the valuation and return of firms’ assets. To answer this question, we take a general
equilibrium-mechanism design approach. I first provide an overview of the general equilibriummechanism design approach and then outline some progress we made under this approach in answering
the above questions.
What is the general equilibrium-mechanism design approach?
The General Equilibrium-Mechanism Design approach refers to the following modeling strategy.
First, start with structural assumptions, for example, assumptions on preferences, production
technologies, economic agents’ information and beliefs, and commitment and contract enforcement
technologies.
Second, solve for the (constrained) efficient allocation given the structural assumptions.
Finally, find out a decentralized mechanism (hopefully) that implement the constrained efficient
allocations, and interpret such implementation as asset prices, investment and payout policies, and
financing decisions of firms.2
Why general equilibrium-mechanism design approach?
The general equilibrium-mechanism design approach is a generalization of the general equilibrium
approach emphasized by modern macroeconomics. The advantage of the general equilibrium approach
has been advocated by many economists, for example, Prescott (2003). General equilibrium modeling
1
Resource allocation among firms in neoclassical models is trivial in the sense that the optimal allocation problem
is static, and aggregate production can be studied by assuming a representative firm.
2
Decentralized mechanisms do not always exist. As far as asset pricing is concerned, it seems make sense to
develop a notion of decentralizable constrained efficiency, that is, make “decentralizability” part of the feasibility
constraint on efficiency in such cases.
avoids making assumptions that are endogenous to the economic system in which the researcher is
interested. It possesses good welfare properties so that there is no incentive for agents to make joint
deviations (formally, competitive equilibrium allocations are in the core.). It builds on micro-foundations
that allow researchers to calibrate parameters of the model from micro-evidences.
Research in financial economics, especially corporate finance, emphasizes the importance of frictions
such as moral hazard, adverse selection, and contract enforcement in understanding firms’ investment
and production decisions. In the presence of such frictions, competitive equilibrium no longer exits;
therefore the general equilibrium approach cannot be applied directly. The general equilibriummechanism design principle is the extension of the general equilibrium tradition in such environments. It
emphasizes that assumptions need to be structural. It focuses on constrained efficient allocations
because they have good welfare properties. Finally, it is micro-founded by construction.
The general equilibrium-mechanism design approach is useful for understanding implications of frictions
like moral hazard, adverse selection, and contract enforceability on asset returns. A large literature in
asset pricing emphasizes the link between firms’ production and investment decisions and the return on
their financial assets. If frictions such as moral hazard, adverse selection, and contract enforceability are
important determinants of firms’ decisions on the real side, we should also pay attention to their
implications on asset prices. To this end, the general equilibrium-mechanism design approach is needed.
What Do We Know?
1. The Benchmark Case: Separation of Ownership and Control is Irrelevant.
We first study a benchmark case and prove an irrelevance result. In “Private Information and The CrossSection of Equity Returns: An Irrelevance Result”, we study how the presence of moral hazard and
adverse selection in firms affects the expected return of their equity. We show that in a large class of
models, the presence of moral hazard or adverse selection problem is irrelevant for the expected return
on firms’ equity under the optimal contract.
The key condition for the irrelevance result requires that the manager’s utility function to be additively
separable with respect to consumption and effort.
2. Dynamic Contracting in a Neoclassical Production Economy
In light of the above result, we start to build models with non-separable preferences. There are two
important elements in the class of models we construct. First, we focus on the delegated investment
problem, where managers have a technology that can secretly transform investment goods into his
private consumption. From an empirical point of view, investment is one of the most important
decisions managers make, and has been demonstrated by the asset pricing literature as having
important impact of the return of firms’ asset. From the theoretical point of view, because managers
can substitute investment and consumption, this feature of the model breaks the separability of
consumption and effort (investment) and make separation of ownership and control potentially relevant
for asset returns through investment decisions.
Second, we incorporate recursive preferences in our analysis. Conceptually, recursive preferences
separate risk aversion and intertemporal elasticity of substitution. This allows researchers to calibrate
the model to the relevant micro-evidence in quantitative work. This is extremely relevant in our case,
because we show risk aversion and IES have dramatically different effects on the optimal contract. In
addition, it breaks the additive separability of utility, making it possible to allow private information to
affect asset returns. Finally, it connects naturally to long-run risks (Bansal and Yaron (2004)), which has
been demonstrated as being important in understanding asset returns.
In “Delegated Investment, Q-Theory, and Firm Dynamics”, we incorporate the delegate investment
problem into a general equilibrium with neoclassical production technologies. Building on continuous
time techniques, we are able to solve the optimal contract and characterize the implied firm dynamics.
We show incorporating this basic friction in an otherwise standard neoclassical framework allow our
model to reproduce some of the salient features of the data on firms’ investment and payout policies,
and those of the size distribution of firms. In our model, small firms invest more, pay less dividend and
grow faster than larger firms. Our model also reproduces the Pareto-like size distribution of firms.
Optimal risk sharing requires managers' equity share to decrease with firm size. This in turn implies that
it is harder to prevent private benefit in larger firms, where managers have lower equity stake under the
optimal contract. Consequently, smaller firms invest more, pay less dividend, and grow faster.
3. Dynamic Contracting, Long-run Risk and the Cross-section of Equity Returns
To be Added.