Truncation Bias in Patent Data: Does It Explain Why Stock-Liquidity Seemingly Reduces Innovation?

Abstract

Patent application data is subject to a truncation-bias since application information is released only after the patent is granted. To address this bias, patent application numbers are typically adjusted using historical patterns. The NBER patents database, which is widely used in extant research, was recently updated, extending the sample end-date of 2006 to 2010. The updated sample, with four more years of data, is largely free of truncation-bias over the period covered by the NBER-2006 sample, allowing us to evaluate the bias-adjustment method and its implications for existing studies. We find that adjustments perform poorly towards the end of NBER-2006 sample. Furthermore, the bias is correlated with firm attributes, such as stock-liquidity. We revisit the findings of Fang et al. (2014) and show that their result that stock-market-liquidity has a negative causal impact on innovation is not supported in the updated, relatively bias-free sample. Our findings suggest that studies using patent-application data should drop observations over 3-5 years from the end-date.