The authors show how to use microlevel survey data from a tracking study on brand awareness in conjunction with data on sales and advertising expenditures to improve the specification, estimation, and interpretation of aggregate discrete choice models of demand. In a departure from the commonly made full information assumption, they incorporate limited information in the form of choice sets to reflect that consumers may not be aware of all available brands at purchase time. They find that both the estimated brand constants and the price coefficient are biased downward when consumer heterogeneity in choice sets is ignored. These biased estimates can lead firms to make costly price-setting mistakes. In addition, the tracking data enable the authors to identify separately two processes by which advertising influences market shares. They find that advertising has a direct effect on brand awareness (inclusion in choice set) in addition to its effect on consumer preferences (increase in utility). This improved understanding of how advertising works enhances researchers’ ability to make policy recommendations.
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