Using machine learning and 10-K filings to measure innovation

Abstract

The purpose of this paper is to develop and validate a text-based measure of innovation using latent Dirichlet allocation on a sample of 45,409 10-K filings from US listed companies. We expect that the text-based innovation measure is associated with innovation and can be used to measure innovation for companies without patents or significant research and development expenditures. The empirical results are consistent with these assumptions, but reveal that thorough initial testing is required to ensure robustness. This study extends the research on innovation measurement and company disclosures, and provides a new method for assessing innovation using company disclosures.