Intangible capital indicators based on web scraping of social media - Patrick Breithaupt; Reinhold Kesler; Thomas Niebel; Christian Rammer (ZEW - Leibniz-Zentrum für Europäische Wirtschaftsforschung, 2020)
Knowledge-based capital is a key factor for productivity growth. Over the past 15 years, it has been increasingly recognised that knowledge-based capital comprises much more than technological knowledge and that these other components are essential for understanding productivity developments and competitiveness of both firms and economies. We develop selected indicators for knowledge-based capital, often denoted as intangible capital, on the basis of publicly available data from online platforms. These indicators based on data from Facebook and the employer branding and review platform Kununu are compared by OLS regressions with firm-level survey data from the Mannheim Innovation Panel (MIP). All regressions show a positive and significant relationship between survey-based firm-level expenditures for marketing and on-the-job training and the respective information stemming from the online platforms. We therefore explore the possibility of predicting brand equity and firm-specific human capital with machine learning methods.
Keywords: C81; E22; O30; 330; Web Scraping; Knowledge-Based Capital; Intangibles