Working Paper: CEPR ID: DP16666
Authors: Alessandro Iaria; Ao Wang
Abstract: We introduce a Generalized Nested Logit model of demand for bundles that can be estimated sequentially and virtually eliminates any challenge of dimensionality related to large choice sets. We use it to investigate quantity discounts for carbonated soft drinks by simulating a counterfactual with linear pricing. The prices of quantities up to 1L decrease by -31.5% while those of larger quantities increase by +14.8%. Purchased quantities decrease by -20.4%, associated added sugar by -23.8%, and industry profit by -20.5%. Consumer surplus however reduces only moderately, suggesting that linear pricing may be effective in limiting added sugar intake.
Keywords: quantity discounts; large choice sets; demand for bundles; generalized nested logit; carbonated soft drinks; purchase of multiple units
JEL Codes: C55; C63; L4; L13; L66
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| linear pricing (D41) | reduction in the average price of small quantities (up to 1L) (P22) |
| linear pricing (D41) | increase in the average price of larger quantities (over 1L) (E30) |
| linear pricing (D41) | decrease in total quantities purchased (D12) |
| linear pricing (D41) | decline in associated added sugar intake (L66) |
| linear pricing (D41) | shrink in industry profit (L16) |
| linear pricing (D41) | moderate reduction in consumer surplus (D11) |