Estimating individual cross-section coefficients from the random coefficient regression model

Robert P. Leone*, H. Dennis Oberhelman, Francis J. Mulhern

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Marketing researchers frequently encounter cross-sectional, time-series data when developing sales response models. One approach to analyzing such data is to estimate a separate OLS equation for each cross-section. Alternatively, one could pool the data from all cross-sections to estimate a single set of response coefficients for all cross-sections. However, when data are pooled, the responsiveness of individual cross-sections cannot be evaluated. In this note, we introduce a version of the random coefficient model that can be used to estimate separate sets of response coefficients for each cross-section, thereby circumventing the assumption that coefficients are homogeneous in all cross-sections. We demonstrate this approach with an empirical model that relates brand level sales to price and advertising.

Original languageEnglish (US)
Pages (from-to)45-51
Number of pages7
JournalJournal of the Academy of Marketing Science
Issue number1
StatePublished - Dec 1 1993

ASJC Scopus subject areas

  • Business and International Management
  • Economics and Econometrics
  • Marketing


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