TY - JOUR
T1 - Estimating individual cross-section coefficients from the random coefficient regression model
AU - Leone, Robert P.
AU - Oberhelman, H. Dennis
AU - Mulhern, Francis J.
PY - 1993/12/1
Y1 - 1993/12/1
N2 - 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.
AB - 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.
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U2 - 10.1177/0092070393211006
DO - 10.1177/0092070393211006
M3 - Article
AN - SCOPUS:68549113276
SN - 0092-0703
VL - 21
SP - 45
EP - 51
JO - Journal of the Academy of Marketing Science
JF - Journal of the Academy of Marketing Science
IS - 1
ER -