Abstract
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.
Original language | English |
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Pages (from-to) | 261-278 |
Number of pages | 18 |
Journal | Review of Income and Wealth |
Volume | 60 |
Issue number | 2 |
DOIs | |
Publication status | Published - Jun 2014 |
Externally published | Yes |
Keywords
- Hedonic regression
- Local regression
- Non-linear pricing
- Quantity discount