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Targeting, Personalization, Heterogeneity, Choice Models, Machine Learning
targeting, personalization, heterogeneity, choice models, machine learning
multi-category demand, nonparametric demand estimation, Bernstein polynomials, model misspecification, omitted variable bias
Hierarchical Priors, Global-Local Priors, Non-Sparse Shrinkage, Horseshoe, Seemingly Unrelated Regression, Price Elasticities
price elasticities, category demand, price promotions, random partition models, Bayesian inference
Outside good, satiation, multiple discreteness, price elasticity, category pricing
Bayesian inference, location-scale family, Polya urn, Markov chain Monte Carlo, price elasticity
Constrained Hierarchical Prior, Discrete Choice, Bayesian Inference, Counterfactual Simulation
learning-by-doing, demand for bundles, preference heterogeneity
differentiated products, price elasticities, shape constraints, Bernstein polynomials, nonparametric instrumental variables, Sequential Monte Carlo, counterfactual analysis
Satiation, Multiple discreteness, Price elasticity
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Choice Models, Heterogeneity, Machine Learning, Personalization, targeting