| Summary: | Demand forecasts are an essential tool for planning capacity and
formulating policy. Traffic estimates are becoming increasingly
unreliable, however, as accelerating rates of use and new
communications applications invalidate conventional forecasting
assumptions.
This paper presents an alternative approach to the study of
telecommunications demand: build aggregate estimates for demand
based on the elasticity of demand for bandwidth.
We argue that price elasticity models are necessary to grasp the
interaction between Moore-type technological progress and non-linear
demand functions.
Traditional marketing models are premised on existing or, at best,
foreseeable services. But in a period of sustained price declines,
applications-based forecasts will be unreliable. Dramatically lower
prices can cause fundamental changes in the mix of applications and,
hence, the nature of demand.
We consider the option of posing demand theoretically in terms of
service attributes. Our conclusion is that the positive feedback loop of
technology-driven price decreases and high-elasticity demand will
quickly make it possible to base forecasts on bandwidth elasticity
alone.
Industry analysts and policymakers need models of consumer demand
applicable under dynamic conditions. We conclude by drawing
implications of our demand model for network planning, universal
service policies, and the commoditization of communications carriage.
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