Estimating Very Large Demand Systems (New Insights)
We present a discrete choice, random utility model and a new estimation technique for analyzing consumer demand for large numbers of products. We allow the consumer to purchase multiple units of any product and to purchase multiple products at once (think of a consumer selecting a bundle of goods in a supermarket). In our model each product has an associated unobservable vector of attributes from which the consumer derives utility. Our model allows for heterogeneous utility functions across consumers, complex patterns of substitution and complementarity across products, and nonlinear price effects. The dimension of the attribute space is, by assumption, much smaller than the number of products, which effectively reduces the size of the consumption space and simplifies estimation. Nonetheless, because the number of bundles available is massive, a new estimation technique, which is based on the practice of negative sampling in machine learning, is needed to sidestep an intractable likelihood function. We prove consistency of our estimator, validate the consistency result through simulation exercises, and present the latest estimates from our model using supermarket scanner data.
Date: 12 October 2023, 14:00 (Thursday, 1st week, Michaelmas 2023)
Venue: Manor Road Building, Manor Road OX1 3UQ
Venue Details: Seminar Room C & online via Zoom
Speaker: Jeremy Large (University of Oxford)
Organising department: Institute for New Economic Thinking
Organiser: Susan Mousley (INET Oxford Admin Team)
Organiser contact email address: events@inet.ox.ac.uk
Part of: INET Oxford Researcher Seminars
Booking required?: Required
Booking url: https://forms.office.com/e/jgMLYqR7r9
Booking email: events@inet.ox.ac.uk
Audience: Public
Editor: Susan Mousley