Every empirical approach to causal inference relies on untestable identifying assumptions. Yet, just 5% of recent empirical studies in top management journals test for sensitivity to the violation of these assumptions. To address this gap, we highlight recent methods that examine how sensitive...

We examine deadlines-induced behavior using large-scale, high frequency data on about 5 million U.S. patents and published applications. We motivate the study with a model of rational agents facing discontinuous incentives around deadline thresholds, without using time-inconsistent preferences...

We build a new concordance between the NBER Patent Data and US Census micro-data, and use it to examine what happens when firms patent. We find strong evidence that increases in patent stock are associated with increases in firm size and scope as well as with changes in factor intensity. We find...

This note provides details about the construction of the NBER Patent Data-BR concordance, and is intended for researchers planning to use this concordance. In addition to describing the matching process used to construct the concordance, this note provides a discussion of the benefits and...