Agency theory

Solo disponible en BuenasTareas
  • Páginas : 25 (6240 palabras )
  • Descarga(s) : 0
  • Publicado : 29 de mayo de 2011
Leer documento completo
Vista previa del texto
Lecture Note 1 Agency Theory1 R. Gibbons MIT
This note considers the simplest possible organization: one boss (or “Principal”) and one worker (or “Agent”). One of the earliest applications of this Principal-Agent model was to sharecropping, where the landowner was the Principal and the tenant farmer the Agent, but in this course we will typically talk about more familiar organization structures.For example, we might consider a firm’s shareholders to be the Principal and the CEO to be the Agent. One can also enrich the model to analyze a chain of command (i.e., a Principal, a Supervisor, and an Agent), or one Principal and many Agents, or other steps towards a full-fledged organization tree. The central idea behind the Principal-Agent model is that the Principal is too busy to do a givenjob and so hires the Agent, but being too busy also means that the Principal cannot monitor the Agent perfectly. There are a number of ways that the Principal might then try to motivate the Agent: this note analyzes incentive contracts (similar to profit sharing or sharecropping); later notes discuss richer and more realistic models. Taken literally and alone, the basic Principal-Agent model mayseem too abstract to be useful. But we begin with this model because it is an essential building block for many discussions throughout the course—concerning not only managing the incentives of individuals but also managing the incentives of organizational units (such as teams or divisions) and of firms themselves (such as suppliers or partners). Furthermore, this abstract model allows us toconsider the nature and use of economic models more generally, as follows.

1 This note draws on R. Gibbons, “Incentives in Organizations,” Journal of Economic Perspectives 12 (1998): 115-132 and R. Gibbons, “Incentives Between Firms (and Within),” forthcoming in Management Science and available at



R. Gibbons

1. An Introduction toEconomic Modeling We will use several economic models in this course, so it may be helpful to begin by describing what an economic model is and what it can do. We will defer discussion of whether such models are useful until after we have a few under our belts! An economic model is a simplified description of reality, in which all assumptions are explicit and all assertions are derived. Such a modelcan produce qualitative and/or quantitative predictions. A qualitative prediction is that “x goes up when y falls.” A quantitative prediction is that x = 1/y. A model’s (qualitative or quantitative) predictions are useful when they are robust within the environment(s) of interest. Quantitative predictions often hinge on specific assumptions from the model. If the model will be applied in oneparticular environment (such as a queuing model describing the lines at the Refresher Course, or the Black-Scholes model for option pricing) then the specific assumptions need to match the environment fairly closely, otherwise the quantitative predictions will not be useful in that environment. One might call this “engineering modeling” rather than “economic modeling.” Qualitative predictions are oftenmore robust, in two senses. First, qualitative predictions may continue to hold if one makes small changes in the model’s specific assumptions. For example, a model’s quantitative predictions might depend on whether a particular probability distribution is normal, exponential, or uniform, but the model’s qualitative predictions might hold for any single-peaked (i.e., hill-shaped) distribution,including the three mentioned above as well as others. Qualitative predictions can also be robust in a second (and, for our purposes, more important) sense: a simple model’s qualitative predictions may be preserved even if one adds much more richness to the model. The major points we will derive from the economic models in this course are robust predictions in this latter sense. That is, adding...
tracking img