Incorporating State Dependence in Aggregate Brand-level Demand Models

Abstract

Empirical investigations of household-level data show that state dependence is a signicant determinant of consumers’ choices in frequently purchased product categories. In this paper we examine how one can incorporate state dependence in an aggregate demand model for brandlevel data which are more often available and frequently used in applied research in marketing and economics. We dene state dependence as consumers receiving higher utility when buying the same brand in two consecutive periods. The main challenge we face is that we do not observe what portion of consumers who chose a given brand had chosen the same brand in the previous period. We overcome this challenge by constructing the brand choice probability using observed market shares from the previous period and the law of total probability. Through Monte Carlo simulations we show that our model is a good approximation of household-level models. We apply our method to estimating demand for salty snacks using a multi-market brand-level data provided by IRI. We nd signicant

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