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blp.pdf
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Summary

The BLP model is a canonical random coefficients logit model that estimates demand for differentiated products. It assumes that individual taste parameters belong to a location-scale family and can be rewritten as a function of mean utility parameters. The model is estimated using a contraction mapping to solve for mean utility parameters, and classical estimation approaches include GMM and MPEC. Bayesian estimation is also possible, using a likelihood function defined through the share inversion and a prior distribution for the parameters. The model accounts for unobserved heterogeneity and endogeneity of product characteristics, and has been widely used in empirical industrial organization and marketing applications.

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Description

The BLP model is a canonical random coefficients logit model that estimates demand for differentiated products.

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  • File Format: PDF
  • File Size: 206 KB
  • Pages: 8
  • Language: EN
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