Ershov, Daniel;
Orr, Scott;
Laliberte, Jean-William;
Marcoux, Mathieu;
(2024)
Estimating Complementarity with Large Choice Sets: An Application to Mergers.
The RAND Journal of Economics
10.1111/1756-2171.70024.
(In press).
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Abstract
Standard discrete choice demand models assume that all products are substitutes. Merger analyses based on these models may overstate consumer harm. We develop an estimator that identifies demand complementarity and remains computationally feasible with large choice sets. We apply this estimator to the chips and soda market and find a high degree of complementarity between these product groups. We show that a counterfactual merger ignoring complementarity between PepsiCo/Frito-Lay and Dr. Pepper generates price increases for soda that are 33% larger than a model with complementarity, and that post-merger chip prices decrease when accounting for complementarity.
| Type: | Article |
|---|---|
| Title: | Estimating Complementarity with Large Choice Sets: An Application to Mergers |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1111/1756-2171.70024 |
| Publisher version: | https://doi.org/10.1111/1756-2171.70024 |
| Language: | English |
| Additional information: | © 2025 The Author(s). The RAND Journal of Economics published by Wiley Periodicals LLC on behalf of The RAND Corporation. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > UCL School of Management |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10189990 |
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