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Random Utility Models are commonly used to model the choice among a set of alternatives. Often, due to data or computational constraints, the analyst must use aggregated alternatives to estimate the model. These aggregates are defined by averaging characteristics of alternatives over prespecified groups. In this analysis, we demonstrate that unless some very restrictive conditions hold, the use of aggregated alternatives will lead to biased results. Then, using a data set of recreational fishing in Wisconsin, we show the effects that this bias can have on the results estimated from the model.
Parsons et al. (Sun,) studied this question.