Multi-Modal Competition and the Future of Mail
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Multi-Modal Competition and the Future of Mail

Edited by Michael A. Crew and Paul R. Kleindorfer

This compilation of original papers selected from the 19th Conference on Postal and Delivery Economics and authored by an international cast of economists, lawyers, regulators and industry practitioners addresses perhaps the most significant problem that has ever faced the postal sector – electronic competition from information and communication technologies. This has increased significantly over the last few years with a consequent serious drop in mail volume.
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Chapter 6: Uncertainty and Projections of the Demand for Mail

Frédérique Fève, Jean-Pierre Florens, Leticia Veruete-McKay, Frank Rodriguez, Soterios Steri and Frank Rodriguez


* Frédérique Fève†, Jean-Pierre Florens‡, Leticia Veruete-McKay§, Soterios Soteri¶ and Frank Rodriguez†† 09 10 11 12 13 1 INTRODUCTION Projections of the demand for mail are an important driver of business decisions in the postal sector. Such projections, for example, support investment decisions, help determine the nature and scope of regulatory controls and represent a key variable in business valuations. However, given the long-term nature of such decisions and, in many instances, their ‘irreversibility’, it is important that postal operators assess and manage appropriately the risks and uncertainties inherent in projecting mail volumes over the medium and long terms. While much has been published on the principles of forecasting and there is also a substantial literature examining factors driving the demand for mail historically, there are relatively few papers that consider specifically the important area of the forecasting of mail volumes.1 Until relatively recently the results from modeling historical data using time-series econometric techniques could then be used to project forward prospects for mail volumes. More recently, however, significant structural change in the mail market has made such forecasting more complex and subject to considerable levels of uncertainty. We have explored these issues from a theoretical perspective in two previous papers. In Fève et al. (2010) we set out a methodological framework in which, in an evolving market environment where there is a lack of historical data, an integral part of the forecasting process for future levels of demand is to follow a Bayesian approach and incorporate...

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