Working Paper: NBER ID: w25991
Authors: W. Erwin Diewert; Robert C. Feenstra
Abstract: 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 five times greater than those obtained using the quadratic utility function.
Keywords: consumer price index; new products; utility functions; scanner data
JEL Codes: C43; C81; D11
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| product availability (L15) | consumer surplus (D46) |
| CES utility function (D11) | consumer surplus (D46) |
| quadratic utility function (D11) | consumer surplus (D46) |
| constant elasticity demand curve (D11) | consumer surplus (D46) |