Working Papers
Screening Property Rights for Innovation (SSRN), with Mark Schankerman (Online Appendices)
Revise and Resubmit (2nd round), Econometrica
Coverage: C-IP2
Recording of intro: Spotify Acast Apple Amazon Music
Presentations: Zvi Conference 2024
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 (SSRN) (Online Appendices) [Extra Note]
Revise and Resubmit (1st round), Journal of Financial Economics
Coverage: FCA
Recording of intro: Spotify Acast Apple Amazon Music
I use novel statement-level data on the 2010—2015 UK credit card market to show that lenders individualize contracts through risk-based credit limits. Though shared with other European credit markets, this feature contrasts with the US counterpart, where interest rates are also individualized. To quantify the implications of this distinction, I estimate a structural model relating individualized interest rates and credit limits to lender-specific credit scores. I evaluate a counterfactual where lenders can freely tailor prices and credit limits, which the UK environment precludes. Lenders control default risk with credit limits and use prices to extract surplus from inelastic borrowers.
Multivariate Ordered Discrete Response Models with Two Layers of Dependence (SSRN), with Tatiana Komarova
Submitted
We develop a class of multivariate ordered discrete response models featuring general rectangular structures, which allow for functionally interdependent thresholds across dimensions, extending beyond traditional (lattice) models that assume threshold independence. The new models incorporate two layers of dependence: one arising from the interdependence of decision rules (capturing broad bracketing behaviors) and another from the correlation of latent utilities conditional on observables. We provide microfoundations, explore semiparametric and parametric specifications, and establish identification conditions under {logical} consistency in decision-making. An empirical application to health insurance markets demonstrates the advantages of this new framework, showing how it disentangles moral hazard (captured via threshold dependence) from adverse selection (isolated in unobservable correlations), offering insights into behavioral responses obscured by lattice models.
Multivariate Ordered Discrete Response Models with Lattice Structures (SSRN) (with Tatiana Komarova)
We analyze multivariate ordered discrete response models with a lattice structure, modeling decision makers who narrowly bracket choices across multiple dimensions. These models map latent continuous processes into discrete responses using functionally independent decision thresholds. In a semiparametric framework, we model latent processes as sums of covariate indices and unobserved errors, deriving conditions for identifying parameters, thresholds, and the joint cumulative distribution function of errors. For the parametric bivariate probit case, we separately derive identification of regression parameters and thresholds, and the correlation parameter, with the latter requiring additional covariate conditions. We outline estimation approaches for semiparametric and parametric models and present simulations illustrating the performance of estimators for lattice models.
Policy Reports
Patent Quality Policy Brief, with Ani Harutyunyan
Patent Quality Fact Sheet, with Ani Harutyunyan
Patent Quality in the United States: Findings and Suggestions for Policymakers, with Matthew Chervenak, Ani Harutyunyan, Mark Schankerman, and Nishant Shrestha
Coverage: IP Watchdog Law360 MarketWatch ClaimWise TheWellNews
Council For Innovation Promotion (C4IP) Panel Discussion (2nd October 2024):
Work in Progress
On Finance:
The Effects of Income Shocks on Asset Allocation and Wealth Inequality (with Akash Raja)
The Design of Misconduct Redress: Evidence from the UK Financial Ombudsman
On Innovation (with Mark Schankerman):
Patent Trial and Appeal Board: Killing Property Rights?
Evaluating Screening in the European Patent Office
Micro-Dynamics of Creative Destruction: Causal Evidence from Patent Renewals
Assessing the Patentability Standard
Patent Screening in Diverse Technology Fields
On Econometrics:
Linear Simultaneous Sample Selection models