Demand Estimation in the Presence of Revenue Management

Estimation de la demande en présence de revenue management

Xavier d'Haultfoeuille, Philippe Février and Lionel Wilner
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Xavier d'Haultfoeuille: CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - Groupe ENSAE-ENSAI - Groupe des Écoles Nationales d'Économie et Statistique - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - Groupe ENSAE-ENSAI - Groupe des Écoles Nationales d'Économie et Statistique - IP Paris - Institut Polytechnique de Paris - CNRS - Centre National de la Recherche Scientifique
Philippe Février: CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - Groupe ENSAE-ENSAI - Groupe des Écoles Nationales d'Économie et Statistique - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - Groupe ENSAE-ENSAI - Groupe des Écoles Nationales d'Économie et Statistique - IP Paris - Institut Polytechnique de Paris - CNRS - Centre National de la Recherche Scientifique

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Abstract: Yield management has become a standard tool in several industries to increase the profits of firms facing demand uncertainty or consumers heterogeneity. But this technique also raises econometric problems in the estimation of demand models. Quantity-based management, in particular, is the source of both an endogeneity and a right-censoring problem. Disposing of macro data only and ignoring these issues leads to an aggregation bias. We develop a structural model of demand in the presence of quantity-based management. We show that the price elasticity is identified in this model provided that (i) we observe two subpopulations that face different prices but are not separated in the yield management policy, (ii) the highest prices and quantities sold at these prices are observed, (iii) the highest prices vary with time or across markets. We apply our method to the French railroad industry, using disaggregated data on trips between Paris and big cities on the period 2007-2009. Our estimates of the price-elasticity are consistent with a rather responsive demand, from 1.7 to 2 in economy class and from 1.3 to 1.5 in business class.

Keywords: revenue management; demand estimation; price-elasticity; railways transportation; modèles structurels de demande; élasticité-prix; transport ferroviaire. (search for similar items in EconPapers)
Date: 2012-10
Note: View the original document on HAL open archive server: https://insee.hal.science/hal-05466798v1
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Working Paper: Demand Estimation in the Presence of Revenue Management (2012)
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