Welcome to home of NNE#
This website provides the code and some documentation for the neural net estimator (NNE), a general approach that uses neural nets to estimate structural econometric models.
Please select the type of NNE below.
Original NNE (limited-information)
Based on "Estimating Parameters of Structural Models Using Neural Nets," Wei and Jiang (2025), Marketing Science, 44(1). This NNE uses researcher-specified moments as input to the neural net. It is most useful when the researcher has clear intuition about what data moments identify the structural model.
Open →Pretrained NNE
Based on "Pre-Training Estimators for Structural Models: Application to Consumer Search," Wei and Jiang (2025). This NNE pretrains a neural net for a given structural model, so users ca estimate the structural model at negligible cost — as easy as running a reduced-form regression.
Open →Full-information NNE
Based on "Estimating and Assessing Identification of Structural Models via Deep Learning," Wei and Jiang (2026). This NNE uses an entire dataset as input, and automatically exploits variation in data. It is useful for not only estimating but also assessing the identification of a structural model.
Open →Contact#
Marshall School of Business, University of Southern California. |
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The Wharton School, University of Pennsylvania. |