Evidence on Firm-to-Firm R&D Collaboration Intensity

Presented at: IIOC - Rising Stars (scheduled), Econometric Society NASM (scheduled), Federal Reserve Bank of Philadelphia

Abstract: Firm-to-firm R&D collaborations have become increasingly common, and firms have been assigning more inventors to these collaborative projects. Despite this trend, existing research on collaboration subsidies has mainly focused on the existence of collaborations rather than their intensity. In this paper, I develop a model in which firms jointly choose their R&D collaborators, the intensity of each collaboration, and their R&D investment. Accounting for heterogeneity in intensity is central to the optimal subsidy design. Using U.S. patent and accounting data, I find that increasing collaboration intensity from below-median to above-median raises collaboration costs by 23% but increases benefits from technological complementarities more than twelvefold. Counterfactual analysis shows that, under a constrained government budget of less than $26 billion, targeting high-intensity collaborations is more cost-effective than subsidizing all collaborations uniformly. Although targeting high-intensity collaborations increases network congestion and attracts less R&D-efficient firms, it accelerates technological complementarities. 

The Hidden Inflation in Homeowners' Insurance (with Mallick Hossain, Natee Amornsiripanitch, Siddhartha Biswas)

Presented at: ASSA 2026 (by coauthor), Urban Economics Association European Meeting (scheduled)

Abstract: Rising homeowners’ insurance prices increase housing and debt service costs, while household coverage adjustments may increase exposure to expense shocks. Using novel data linking mortgages to insurance policies, we develop a quality-adjusted price index showing that the menu of insurance costs increased 18 percent more than premium expenditure growth from 2013-2022. During this period, households responded by increasing deductibles and reducing coverage relative to structure values, leaving them more exposed to financial shocks. Our estimates reveal low household demand elasticities for insurance features, though these elasticities increase significantly during home purchases, refinancing, or when households receive updated property valuations. These findings suggest inattention and information frictions substantially influence insurance decisions. Policy implications favor behavioral nudges and regular property assessments over price-based interventions to reduce household financial vulnerability in insurance markets. Credit utilization results suggest that households self-insure when faced with higher insurance costs. 

Identifying the Causal Effects of Information Interventions under Network Interference (with Ju Hyun Oh)

Abstract: Information spreads easily among individuals. This paper studies how to identify the causal effects of information interventions under network interference, where treated individuals can spread information to their peers. We focus on key causal parameters, including the average treatment effect (ATE) and the persuasion rate--the probability that individuals change their behaviors after exposure to new information. We develop partial identification strategies in various intervention contexts, with particular focus on two empirically relevant scenarios: 1) individuals strategically choose which treatment to receive and with whom to interact, and 2) policymakers strategically target central individuals within the network, anticipating greater information diffusion. To illustrate the practical relevance of our framework, we apply it to study pharmaceutical advertising and information spillovers in physicians’ prescription behavior. We find that information interventions generate weakly positive direct and peer effects on prescribing, but these effects exhibit saturation as peer exposure increases.