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- W3138299630 abstract "This paper proposes a new method to estimate random coefficients logit models using aggregate data. The method is applicable for models with discrete-type heterogeneity in consumer tastes when data on sales aggregated by consumer type are available. The method analytically obtains the value of the econometric error term and thus does not require numerical calculations, such as the contraction mapping established by Berry, Levinsohn, and Pakes (1995). Consequently, the method no longer suffers from problems due to numerical errors in the contraction mapping, including lack of convergence and incorrect parameter estimates. In addition, the computation time is drastically reduced. Simulation exercises show that the proposed method is approximately 40-90 times faster on average than the established method." @default.
- W3138299630 created "2021-03-29" @default.
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- W3138299630 date "2020-01-01" @default.
- W3138299630 modified "2023-09-24" @default.
- W3138299630 title "Estimation of Discrete-type Random Coefficients Logit Models using Type-level Sales Data" @default.
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- W3138299630 doi "https://doi.org/10.2139/ssrn.3729184" @default.
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