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AI Revolution on Chat Bot: Evidence from a Randomized Controlled Experiment
In recent years, generative AI has undergone major advancements, demonstrating significant promise in augmenting human productivity.
Design-based Estimation Theory for Complex Experiments
This paper considers the estimation of treatment effects in randomized experiments with complex experimental designs, including cases with interference between units.
Approximating Choice Data by Discrete Choice Models
We obtain a necessary and sufficient condition under which random-coefficient discrete choice models, such as mixed-logit models, are rich enough to approximate any nonparametric random utility models arbitrarily well across choice sets.
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