We study identification and estimation of the average treatment effect in a correlated random coefficients model that allows for first stage heterogeneity and binary instruments. The model also allows for multiple endogenous variables and interactions between endogenous variables and covariates....

This paper derives conditions under which preferences and technology are nonparametrically identified in hedonic equilibrium models, where products are differentiated along more than one dimension and agents are characterized by several dimensions of unobserved heterogeneity. With products...

We use hedonic prices and purchase quantities to consider what can be learned about household willingness to pay for baskets of organic products and how this varies across households. We use rich scanner data on food purchases by a large number of households to compute household specific lower...

The recent literature has brought together the characteristics model of utility and classic revealed preference arguments to learn about consumers' willingness to pay. We incorporate market pricing equilibrium conditions into this setting. This allows us to use observed purchase prices and...

We develop empirical models of hedonic prices and derive hedonic indices for measuring changes in customer welfare based upon deep learning. We first generate abstract product attributes, or "features," from text descriptions and images using deep neural networks, and then use these attributes...

Accurate, real-time measurements of price index changes using electronic records are essential for tracking inflation and productivity in today's economic environment. We develop empirical hedonic models that can process large amounts of unstructured product data (text, images, prices,...