LLM Time Machines: Valuing Digital Goods Over Time

12 Pages Posted: 18 Mar 2025

See all articles by Avinash Collis

Avinash Collis

Carnegie Mellon University

Felix Eggers

Copenhagen Business School - Department of Marketing

Erik Brynjolfsson

National Bureau of Economic Research (NBER); Stanford

Date Written: December 01, 2024

Abstract

Digital goods generate a significant amount of consumer welfare, yet the magnitude of these welfare gains is hard to estimate due to the lack of prices since most of these goods are free to consumers. Moreover, to fully understand their impact and track the welfare gains over time, we must assess how their value has evolved since their introduction. This is particularly challenging as newly introduced digital goods have limited consumer awareness, and current perceptions often bias retrospective estimates of previous consumer valuations. We investigate the feasibility of using large language models (LLMs) to estimate the valuations of digital goods via incentive-compatible single binary discrete choice experiments. We benchmark LLMs against valuations obtained from these choice experiments on representative samples of US populations from 2016-24. We find that valuations generated by LLMs are similar to valuations estimated using humans and follow similar patterns over time. Moreover, LLMs can be potentially used to extrapolate, going back or forward in time. We conclude by offering some guidance on using LLMs to generate longitudinal data on the valuations of digital goods and other types of goods.

Suggested Citation

Collis, Avinash and Eggers, Felix and Brynjolfsson, Erik, LLM Time Machines: Valuing Digital Goods Over Time (December 01, 2024). Available at SSRN: https://ssrn.com/abstract=5140159 or http://dx.doi.org/10.2139/ssrn.5140159

Avinash Collis (Contact Author)

Carnegie Mellon University ( email )

Pittsburgh, PA
United States

Felix Eggers

Copenhagen Business School - Department of Marketing ( email )

Copenhagen
Denmark

Erik Brynjolfsson

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Stanford ( email )

366 Galvez St
Stanford, CA 94305
United States

HOME PAGE: http://brynjolfsson.com

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