Cover Image

Can large language models assist choice modelling? Insights into prompting strategies and current models capabilities

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Sfeir, Georges, Nova, Gabriel, Hess, Stephane, van Cranenburgh, Sander
Format:	Preprint
Published:	2025
Subjects:	Econometrics Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Understanding the decision-making process of choice modellers
by: Nova, Gabriel, et al.
Published: (2024)

Flexibility without foresight: the predictive limitations of mixture models
by: Hess, Stephane, et al.
Published: (2025)

Combine and conquer: model averaging for out-of-distribution forecasting
by: Hess, Stephane, et al.
Published: (2025)

Delphos: A reinforcement learning framework for assisting discrete choice model specification
by: Nova, Gabriel, et al.
Published: (2025)

An economically-consistent discrete choice model with flexible utility specification based on artificial neural networks
by: Hernandez, Jose Ignacio, et al.
Published: (2024)

Posterior inference of attitude-behaviour relationships using latent class choice models
by: Vij, Akshay, et al.
Published: (2025)

Statistical significance in choice modelling: computation, usage and reporting
by: Hess, Stephane, et al.
Published: (2025)

Get me out of this hole: a profile likelihood approach to identifying and avoiding inferior local optima in choice models
by: Hess, Stephane, et al.
Published: (2025)

Comparing hundreds of machine learning classifiers and discrete choice models in predicting travel behavior: an empirical benchmark
by: Wang, Shenhao, et al.
Published: (2021)

Comment on Scientific production in the era of large language models
by: Renault, Thomas, et al.
Published: (2026)

Beyond utility: incorporating eye-tracking, skin conductance and heart rate data into cognitive and econometric travel behaviour models
by: Hancock, Thomas O., et al.
Published: (2025)

Can AI Master Econometrics? Evidence from Econometrics AI Agent on Expert-Level Tasks
by: Chen, Qiang, et al.
Published: (2025)

Grouped fixed effects regularization for binary choice models
by: Pigini, Claudia, et al.
Published: (2025)

Can language models boost the power of randomized experiments without statistical bias?
by: Ruan, Xinrui, et al.
Published: (2025)

Continuous permanent unobserved heterogeneity in dynamic discrete choice models
by: Bunting, Jackson
Published: (2022)

Faster estimation of dynamic discrete choice models using index invertibility
by: Bunting, Jackson, et al.
Published: (2023)

Binary choice logit models with general fixed effects for panel and network data
by: Dano, Kevin, et al.
Published: (2025)

Forecasting Labor Demand: Predicting JOLT Job Openings using Deep Learning Model
by: Kim, Kyungsu
Published: (2025)

From Model Choice to Model Belief: Establishing a New Measure for LLM-Based Research
by: Sun, Hongshen, et al.
Published: (2025)

A Deep Learning Representation of Spatial Interaction Model for Resilient Spatial Planning of Community Business Clusters
by: Hao, Haiyan, et al.
Published: (2024)

Neural Network Modeling for Forecasting Tourism Demand in Stopića Cave: A Serbian Cave Tourism Study
by: Bajić, Buda, et al.
Published: (2024)

AI Assisted Economics Measurement From Survey: Evidence from Public Employee Pension Choice
by: Wang, Tiancheng, et al.
Published: (2026)

Sufficient conditions for a Heuristic Rating Estimation Method application
by: Szybowski, Jacek, et al.
Published: (2026)

Large Language Models: An Applied Econometric Framework
by: Ludwig, Jens, et al.
Published: (2024)

Estimating Visual Attribute Effects in Advertising from Observational Data: A Deepfake-Informed Double Machine Learning Approach
by: Liu, Yizhi, et al.
Published: (2026)

Certificates without Electrons? Theory and Evidence on Impacts from AI-Driven Power Demand
by: Golden, Dana, et al.
Published: (2026)

Evaluating the Accuracy of Chatbots in Financial Literature
by: Erdem, Orhan, et al.
Published: (2024)

Analyzing the Reporting Error of Public Transport Trips in the Danish National Travel Survey Using Smart Card Data
by: Sfeir, Georges, et al.
Published: (2023)

A break from the norm? Parametric representations of preference heterogeneity for discrete choice models in health
by: Buckell, John, et al.
Published: (2025)

Microtransit revenue management informed by citywide travel demand and joint subscription-mode choice modeling
by: Ren, Xiyuan, et al.
Published: (2024)

From What Ifs to Insights: Counterfactuals in Causal Inference vs. Explainable AI
by: Shmueli, Galit, et al.
Published: (2025)

New possibilities in identification of binary choice models with fixed effects
by: Zhu, Yinchu
Published: (2022)

Scaling Causal Mediation for Complex Systems: A Framework for Root Cause Analysis
by: Casadei, Alessandro, et al.
Published: (2025)

A primer on optimal transport for causal inference with observational data
by: Gunsilius, Florian F
Published: (2025)

Sentiment trading with large language models
by: Kirtac, Kemal, et al.
Published: (2024)

A sequential test procedure for the choice of the number of regimes in multivariate nonlinear models
by: Bucci, Andrea
Published: (2024)

Some models are useful, but for how long?: A decision theoretic approach to choosing when to refit large-scale prediction models
by: Hoffman, Kentaro, et al.
Published: (2024)

Unleashing the potential of prompt engineering for large language models
by: Chen, Banghao, et al.
Published: (2023)

LLM Personas as a Substitute for Field Experiments in Method Benchmarking
by: Kang, Enoch Hyunwook
Published: (2025)

Foundation Priors
by: Misra, Sanjog
Published: (2025)