Endogeneity of store attributes in heterogeneous store-level sales response models |
| |
Authors: | Harald Hruschka Ralf G Gerhardt |
| |
Affiliation: | (1) Department of Agricultural and Applied Economics, University of Georgia, Athens, GA 30602-7509, USA;(2) Department of Applied Economics, University of Minnesota, St. Paul, MN 55108-6040, USA |
| |
Abstract: | Retailing firms as a rule decide on store attributes (e.g., store size) considering an assessment of future sales of these
stores. Typically, managers allocate better or more equipment to stores for which they expect higher sales. Models which ignore
the fact that this behavior leads to endogeneity overestimate effects of these attributes. Managers, who base decisions on
such models, loose profits by installing more (or more costly) equipment. The number of papers studying store-level sales
response models accounting for endogeneity appears to be very limited. We consider potential endogeneity of store attributes
in the sales response function by an instrumental variable approach. We also allow for heterogeneity across stores by assuming
that store-level coefficients are generated by a finite mixture distribution. Models are estimated by a Markov chain Monte
Carlo simulation technique which combines two Gibbs sampling algorithms. In the empirical study both heterogeneity and endogeneity
turn out to influence estimates. For a cross section of more than 1,000 gas stations credible intervals of differences of
coefficients are computed between models ignoring and models considering endogeneity. These intervals indicate that models
which ignore endogeneity overestimate the effects of two store attributes on sales. We also discuss managerial implications
of these endogeneity biases. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|