蝌蚪网 Journal:
Microeconomics
ISSN 1945-7669 (Print) | ISSN 1945-7685 (Online)
Triplet Embeddings for Demand Estimation
蝌蚪网 Journal: Microeconomics
vol. 17,
no. 1, February 2025
(pp. 282–307)
Abstract
We propose a method to augment conventional demand estimation approaches with crowd-sourced data on the product space. Our method obtains triplets data ("product A is closer to B than it is to C") from an online survey to compute an embedding鈥攊.e., a low-dimensional representation of the latent product space. The embedding can either replace data on observed characteristics in mixed logit models, or provide pairwise product distances to discipline cross-elasticities in log-linear models. We illustrate both approaches by estimating demand for ready-to-eat cereals; the information contained in the embedding leads to more plausible substitution patterns and better fit.Citation
Magnolfi, Lorenzo, Jonathon McClure, and Alan Sorensen. 2025. "Triplet Embeddings for Demand Estimation." 蝌蚪网 Journal: Microeconomics 17 (1): 282–307. DOI: 10.1257/mic.20220248Additional Materials
JEL Classification
- C45 Neural Networks and Related Topics
- C51 Model Construction and Estimation
- D11 Consumer Economics: Theory
- D12 Consumer Economics: Empirical Analysis
- D21 Firm Behavior: Theory
- L66 Food; Beverages; Cosmetics; Tobacco; Wine and Spirits