This paper uses new data to reexamine trends in concentration in U.S. markets from 1994 to 2019. The paper's main contribution is to construct concentration measures that reflect narrowly defined consumption-based product markets, as would be defined in an antitrust setting, while accounting for...

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,...

This paper proposes a method to estimate price sensitivity of economic agents exploiting discontinuity in nonlinear contracts. As an application, we study contracts between a managed care organization and hospitals for organ transplants. Exploiting donut holes in the reimbursement contracts, we...

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...

When procurement contracts are incomplete, they are frequently changed after the contract is awarded to the lowest bidder. This results in a final cost that differs from the initial price, and may involve significant transaction costs due to renegotiation. We propose a stylized model of bidding...