 pricing (Kahn and Shew 1987; Park and Mitchell 1987). The combination of transaction costs and the inefficiency caused by the inability to precisely tailor prices to current demand may be sufficient to render usage-based pricing uneconomical. In addition, networks are complex systems that can adapt in ways that are hard to predict. For example, increasing a particular flow through a saturated net- work element by ten percent will not necessarily reduce the carrying capacity of the network by ten percent, because the network may be able to compensate by rerouting traffic through other paths. Networks' ability to compensate for changes in network flows can cause the elements that are saturated to shift in discontinuous ways that greatly complicate determining the precise impact of increasing a net- work flow at any particular time. Customers' aversion to complex pricing regimes further limits networks' ability to implement usage-sensitive prices (Telephony 1975). Furthermore, the fact that capacity expansion typically takes time and is subject to indivisibilities dictates that capacity will generally be added before it is needed. In addition, networks always maintain a certain level of excess capacity to insure against unexpected surges in demand. As a result, the network will always appear slack even when the excess capacity is simply a reflection of proper network management. The impracticality of designing a pricing regime that was precisely calibrated to the actual congestion costs associated with an incremental call led carriers imple- menting LMS to adopt pricing regimes that broke the day into three discrete periods: peak, near peak (called "shoulder rates"), and off peak. Empirical studies of these experiments have split on the economic impact of LMS. 13 Some have concluded that the combination of metering costs and the misincentives created by the inability to set prices precisely equal to congestion costs were sufficient to render LMS uneco- nomical (Park and Mitchell 1987). Others have concluded that ad