A panel data analysis of inefficiency and heterogeneity in the postal sector

Cazals, Catherine, Dudley, Paul, Florens, Jean-Pierre and Jones, Michael (2012) A panel data analysis of inefficiency and heterogeneity in the postal sector. In: Multi-Modal Competition and the Future of Mail Crew, Michael A. and Kleindorfer, Paul R. (eds.) Michael A. Crew and Paul R. Kleindorfer. Chapter 8. pp. 109-123. ISBN 9780857935816

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Official URL: http://tse-fr.eu/pub/30593


The analysis of efficiency is of great interest for policy decision makers, particularly for businesses and regulators. Many methods may be applied to estimate inefficiencies of production units. These methods include deterministic or stochastic methods and parametric or non-parametric methods, applied on cross-sectional or panel data. However the most often used in the applied literature is the parametric stochastic frontier analysis (SFA), for which a particular form for the studied efficiency frontier (production or cost) is specified and some particular distribution for inefficiencies is assumed. Different specifications and assumptions may be more appropriate in some applications than others, and this may depend on the structure of the dataset and the policy questions involved for the sector in question. The present chapter examines these questions concerning the appropriate SFA method and specification to apply to delivery office data in the postal sector. The delivery offices in the postal sector are particularly suited to frontier and efficiency estimation. First, there are numerous operational offices, each fulfilling a similar purpose and function, and thereby providing a sizeable dataset for comparison. Second, the operational office functions, particularly in delivery, are highly labor intensive, thereby creating scope for the practice and efficiency of one office to differ from that of another.

Item Type: Book Section
Language: English
Date: 2012
Additional Information: DOI : 10.4337/9780857935823.00013
Divisions: TSE-R (Toulouse)
Site: UT1
Date Deposited: 25 Aug 2016 10:13
Last Modified: 27 Mar 2018 15:07
OAI ID: oai:tse-fr.eu:30593
URI: http://publications.ut-capitole.fr/id/eprint/22259

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