Technology and Innovation Commons^™

Machine Learning Using Instruments For Text Selection: Predicting Innovation Performance, Kian Guan Lim, Michelle S. J. Lim

Research Collection Lee Kong Chian School Of Business

In machine learning we utilize the idea of employing instrumental variable such as patent records to train the texts. Patent records are highly correlated with R&D expenditures, but are not necessarily correlated with performance residuals not linked to R&D. Thus, using instrumental patent records to train word counts of selected texts to serve as a proxy for firm R&D expenditure, we show that the texts and associated word counts provide effective prediction of firm innovation performances such as firm market value and total sales growth.