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Hybrid consumption paths in the attribute space: A model and application with scanner data;
State dependence and optimal consumption patterns: A dynamic model with applications to scanner data.
Jiménez-Martín, Sergi; Ladrón de Guevara, Antonio
Universitat Pompeu Fabra. Departament d'Economia i Empresa
This paper presents and estimates a dynamic choice model in the attribute space considering rational consumers. In light of the evidence of several state-dependence patterns, the standard attribute-based model is extended by considering a general utility function where pure inertia and pure variety-seeking behaviors can be explained in the model as particular linear cases. The dynamics of the model are fully characterized by standard dynamic programming techniques. The model presents a stationary consumption pattern that can be inertial, where the consumer only buys one product, or a variety-seeking one, where the consumer shifts among varied products.We run some simulations to analyze the consumption paths out of the steady state. Underthe hybrid utility assumption, the consumer behaves inertially among the unfamiliar brandsfor several periods, eventually switching to a variety-seeking behavior when the stationary levels are approached. An empirical analysis is run using scanner databases for three different product categories: fabric softener, saltine cracker, and catsup. Non-linear specifications provide the best fit of the data, as hybrid functional forms are found in all the product categories for most attributes and segments. These results reveal the statistical superiority of the non-linear structure and confirm the gradual trend to seek variety as the level of familiarity with the purchased items increases.
2008-03-13
Management and Organization Studies
Business Economics and Industrial Organization
Labour, Public, Development and Health Economics
Statistics, Econometrics and Quantitative Methods
dynamic choice model
rational consumers
inertia
variety seeking
hybrid behavior
scanner data
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Working Paper
         

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