Estimating the Benefits of New Products,This chapter is a preliminary draft unless otherwise noted. It may not have been subjected to the formal review process of the NBER. This page will be updated as the chapter is revised.
Chapter in forthcoming NBER book Big Data for Twenty-First Century Economic Statistics, Katharine G. Abraham, Ron S. Jarmin, Brian Moyer, and Matthew D. Shapiro, editors A major challenge facing statistical agencies is the problem of adjusting price and quantity indexes for changes in the availability of commodities. This problem arises in the scanner data context as products in a commodity stratum appear and disappear in retail outlets. Hicks suggested a reservation price methodology for dealing with this problem in the context of the economic approach to index number theory. Hausman used a linear approximation to the demand curve to compute the reservation price, while Feenstra used a reservation price of infinity for a CES demand curve, which will lead to higher gains. The present paper evaluates these approaches, comparing the CES gains to those obtained using a quadratic utility function using scanner data on frozen juice products. We find that the CES gains from new frozen juice products are about six times greater than those obtained using the quadratic utility function, and the confidence intervals of these estimates do not overlap. This paper is available as PDF (552 K) or via email
Machine-readable bibliographic record - MARC, RIS, BibTeX This chapter first appeared as NBER working paper w25991, Estimating the Benefits of New Products, W. Erwin Diewert, Robert C. Feenstra |
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