In this paper, we exploit new sources of cross-sectional data to estimate a detailed product-level demand system for new passenger vehicles. We use four data sources: on the characteristics of products, on the attributes of the U.S. population of households, on the match between the first and second vehicle choices of the household, and on the match between households attributes and first choice vehicles. We show that these data solve some, but not all, of the traditional problems in estimating differentiated products demand systems and indicate which data sources are important for which problem. The data is rich enough to reveal a rather complex substitution pattern, requiring a quite general modeling framework. Together the data and model make a detailed analysis of industry demand possible.
*Published:
Berry, Steven, James Levinsohn and Ariel Pakes. "Differentiated Products Demand Systems From A Combination Of Micro And Macro Data: The New Car Market," Journal of Political Economy, 2004, v112(1,Feb), 68-105.
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