Which Brands gain Share from which Brands? Inference from Store-Level Scanner Data

This file is part of IDEAS, which uses RePEc data

Which Brands gain Share from which Brands? Inference from Store-Level Scanner Data

Author Info

Rutger van Oest () (Tilburg University)
Philip Hans Franses () (Faculty of Economics, Erasmus Universiteit Rotterdam)

Abstract

Market share models for weekly store-level data are useful to understand competitive structures by delivering own and cross price elasticities. These models can however not be used to examine which brands lose share to which brands during a specific period of time. It is for this purpose that we propose a new model, which does allow for such an examination. We illustrate the model for two product categories in two markets, and we show that our model has validity in terms of both in-sample fit and out-of-sample forecasting. We also demonstrate how our model can be used to decompose own and cross price elasticities to get additional insights into the competitive structure.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help file. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

Publisher Info
Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 03-079/4.

Download reference. The following formats are available: HTML, plain text, BibTeX, RIS (EndNote), ReDIF
Length:
Date of creation: 06 Oct 2003
Date of revision:
Handle: RePEc:dgr:uvatin:20030079

Contact details of provider:
Web page: http://www.tinbergen.nl/

For technical questions regarding this item, or to correct its listing, contact: (Walther Schoonenberg).

Find related papers by JEL classification:
C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - General
C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
M31 - Business Administration and Business Economics; Marketing; Accounting - - Marketing and Advertising - - - Marketing

This paper has been announced in the following NEP Reports:

NEP-ALL-2003-10-20 (All new papers)
NEP-COM-2003-10-20 (Industrial Competition)

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

Kumar, V. & Heath, Timothy B., 1990. "A comparative study of market share models using disaggregate data," International Journal of Forecasting, Elsevier, vol. 6(2), pages 163-174, July. [Downloadable!] (restricted)
Chen, Youhua & Kanetkar, Vinay & Weiss, Doyle L., 1994. "Forecasting market shares with disaggregate or pooled data: a comparison of attraction models," International Journal of Forecasting, Elsevier, vol. 10(2), pages 263-276, September. [Downloadable!] (restricted)

Full references

Statistics
Access and download statistics

Did you know? You can create a compilation of all publications of a group of people, say alumni of a program, your students or memers of an association.

This page was last updated on 2008-8-27.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.