Working Papers

Screening Property Rights for Innovation (SSRN), with Mark Schankerman (Online Appendices)
Revise and Resubmit, Econometrica

Coverage: C-IP2
Recording of intro: Spotify Acast Apple

We develop a dynamic structural model of patent screening incorporating incentives, intrinsic motivation, and multi-round negotiation. We estimate the model using detailed data on examiner decisions and employ natural language processing to create a new measure of patent distance that enables us to study strategic decisions by applicants and examiners. The estimated parameters and counterfactual analysis imply three main findings. First, patent screening is moderately effective, given the existing standards for patentability. Second, examiners exhibit substantial intrinsic motivation that significantly improves the effectiveness, and reduces the net social costs, of screening. Third, limiting the number of negotiation rounds strongly increases the speed and quality of screening. We quantify the net social costs of patent screening and find that the annual social cost of the existing system is $25.5bn, equivalent to 6.5% of U.S. R&D performed by the private sector.

Risk-Based Borrowing Limits in Credit Card Markets
Coverage: FCA

Credit card lenders individualize contracts primarily through risk-based credit limits rather than interest rates. To understand lenders’ credit limit choices, I use novel statement-level data on the near-universe of UK credit cards active between 2010–2015 to estimate a structural model of the credit card market. The model explains differences in the shape of lenders’ credit limit distributions through a screening technology that provides lenders with a noisy signal of customers’ risk. I identify model parameters using a novel cost shock that results from the April 2011 case in the England and Wales High Court concerning the mis-selling of payment protection insurance. I use the estimated model to evaluate a counterfactual scenario in which lenders can freely individualize interest rates and credit limits, which the existing environment precludes. As a result, individualized interest rates and credit limits emerge, profits increase, and borrowing becomes more dispersed as a result.

Multivariate Ordered Discrete Response Models (SSRN), with Tatiana Komarova

We introduce multivariate ordered discrete response models with general rectangular structures. From the perspective of behavioral economics, these non-lattice models correspond to broad bracketing in decision making, whereas lattice models, which researchers typically estimate in practice, correspond to narrow bracketing. In these models, we specify latent processes as a sum of an index of covariates and an unobserved error, with unobservables for different latent processes potentially correlated. We provide conditions that are sufficient for identification under the independence of errors and covariates and outline an estimation approach. We present simulations and empirical examples, with a particular focus on probit specifications.

Other Work in Progress

Simultaneous Sample Selection models