A simple method to estimate discrete-type random coefficients logit models

Naoshi Doi

International Journal of Industrial Organization, 2022, vol. 81, issue C

Abstract: This paper proposes a new method for estimating random coefficients logit models using aggregate data. The method analytically obtains the value of the econometric error term and thus does not require numerical calculations, in contrast to the contraction mapping established by Berry et al. (1995). The proposed approach drastically reduces the computation time and is applicable for models with discrete-type heterogeneity in consumer tastes. The approach requires additional data on total sales for each consumer type, though such data do not have to be observed at the product-level. This data requirement implies that the method mainly captures observed heterogeneity.

Keywords: Demand estimation; Random-coefficient discrete choice model; Latent class model (search for similar items in EconPapers)
JEL-codes: C13 C51 D12 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:indorg:v:81:y:2022:i:c:s0167718722000017

DOI: 10.1016/j.ijindorg.2022.102825

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