Tailored Claims and Governance: The Fit Between Employees and Shareholders

Abstract:     
We generalize the internal labor markets (ILM) analysis of the employment relationship to provide a comprehensive model of the relationships among employees, capital providers (particularly shareholders), and the firm. We start by showing that all are variable claimants and all participate in governance, but that the characteristic differences in the payment streams and governance rights of employees and shareholders can be explained by differences in the four principal industrial organization (IO) factors -- investments in match, asymmetry of information, risk aversion and transaction costs. In arriving at these results, we analyze the ways in which employees are typically variable but not residual claimants and why making employees residual claimants over the relevant set of assets, while providing strong incentives for maximizing the value of those assets, is typically not incentive compatible. Our principal conclusions are the following. First, the ownership rights of shareholders have direct parallels in the employment relationship, with the difference between the two parallel tracks reflecting the parties' ability to gain from investments in match, their willingness to trade off higher return for greater risk and their incentive-compatible solutions to the problems of asymmetric information and transaction costs. Second, in terms of the four critical IO factors, the shareholder/managers of the closely held corporation share many features with employees in the classic internal labor market, and that the characteristic arrangements that emerge strongly resemble the solutions of the ILM. Finally, we show that both relationships are fundamentally different from the relationship between the publicly held firm and its suppliers of equity capital, and that the arrangements between shareholders and the publicly held firm are the limit case in which investments in match approach zero.

JEL Classifications: J54, G34

Working Paper Series