Exploring Effects of Consumer Finance Regulation with Deep Learning
Sebastian Benthall (NYU), Alan Lujan, Ngozi Nwanta (NYU), Zixuan Pan (UC Berkeley), Katherine J. Strandburg (NYU)
Applies deep learning methods to analyze and predict the effects of consumer finance regulation. Supported by National Science Foundation through Award No. 2131532.
Identification by Simulation Pretraining: Learned Identifying Statistics for Structural Economic Models
Karan Bhasin (SUNY Albany), Alan Lujan
Monotonicity Is All You Need
Alan Lujan
Proves that monotonicity makes the upper envelope sufficient for finding globally optimal solutions in discrete choice models, providing theoretical foundations for applying the Endogenous Grid Method to these problems.
Can News of AI Growth Lower Spending?
Alan Lujan
Households with perfect foresight in the AI scenarios of Korinek, Jones, Sacher, Cotter, and McCrory (2026). A foreseen transition that raises average income lowers consumption in the month it is announced.
Who Funds the Capital behind AI Wage Gains?
Alan Lujan
The AI scenarios supply capital from a schedule with no saving behind it. A domestic owner of capital with perfect foresight saves far less than that schedule supplies, so the wage gain in the extreme scenario rests on foreign lending.