Structural economic models, while parsimonious and interpretable, often exhibit poor data fit and limited forecasting performance. Machine learning models, by contrast, offer substantial flexibility but are prone to overfitting and weak out-of-distribution generalization. We propose a...

Synthetic microdata - data retaining the structure of original microdata while replacing original values with modeled values for the sake of privacy - presents an opportunity to increase access to useful microdata for data users while meeting the privacy and confidentiality requirements for data...