Note: We are appreciative of the financial support of the Australian Research Council (LP0667655) in undertaking this research, and the very constructive comments we received from two anonymous referees and participants at the UNSW Economic Measurement Group Workshop. Any remaining errors are our own.
Non-Linear Pricing and Price Indexes: Evidence and Implications from Scanner Data
Version of Record online: 29 NOV 2012
© 2012 The Authors. Review of Income and Wealth © International Association for Research in Income and Wealth 2012
Review of Income and Wealth
Volume 60, Issue 2, pages 261–278, June 2014
How to Cite
Fox, K. J. and Melser, D. (2014), Non-Linear Pricing and Price Indexes: Evidence and Implications from Scanner Data. Review of Income and Wealth, 60: 261–278. doi: 10.1111/roiw.12000
- Issue online: 8 MAY 2014
- Version of Record online: 29 NOV 2012
- Australian Research Council. Grant Number: LP0667655
- hedonic regression;
- local regression;
- non-linear pricing;
- quantity discount
Non-linear pricing, the fact that prices do not necessarily change in proportion to size, is a ubiquitous phenomenon. However, it has been neither particularly well understood nor well measured. Non-linear pricing is of practical importance for statistical agencies who, in constructing price indexes, are often required to compare the relative price of a product-variety of two different sizes. It is usually assumed that prices change one-for-one with package and pack size (e.g. a 1-liter cola costs half as much as a 2-liter bottle). We question the wisdom of such an assumption and outline a model to flexibly estimate the price-size function. Applying our model to a large U.S. scanner dataset for carbonated beverages, at a disaggregated level, we find very significant discounts for larger-sized products. This highlights the need to pursue methods such as those advocated in this paper.