Differentiated Products Demand Systems from a Combination of Micro and Macro Data: The New Car Market

Abstract

In this paper, we consider how rich sources of information on consumer choice can help to identify demand parameters in a widely used class of differentiated products demand models.Most important, we show how to use "second-choice" data on automotive purchases to obtain good estimates of substitution patterns in the automobile industry.We use our estimates to make out-of-sample predictions about important recent changes in industry structure.We thank numerous seminar participants, two referees, and the editors Lars Hansen and John Cochrane for helpful suggestions.We also thank the National Science Foundation for financial support, through grants 9122672, 9512106, and 9617887.We are particularly grateful to G. Mustafa Mohatarem at General Motors Corp., who made possible our access to the data

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