Abstract
This paper empirically examines parameter sensitivity to choice set specification in the context of shopping destination choice, using supermarket choice data from Gainesville, Horida. We estimate parameters of the widely applied multinomial logit (MNL) discrete choice mode) multiple times. Each estimation uses, for all observations, a single randomly selected subset of the universal choice set. The distribution of parameter estimates is examined for specific market segments and choice subset sizes. The results indicate that the parameters of the model can be quite sensitive to the selection of the choice set used in the calibration. However, this sensitivity is not even across all parameters and there are some interesting variations. Distance deterrence and chain image parameters, for example, exhibit much more stability than parameters for store size and store competition. Li addition, model parameters show encouraging stability with relatively small choice sets of seven to ten stores.
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