MAN Seminar: “Technological Obsolescence”, Song Ma, Yale University, 5:00PM November 12 (EN)

Date: 12 November 2021, Friday
Time: 17:00-18:00

by Song Ma, Yale University

***This is an online seminar. To obtain the event link and password, please send a mail to the department.

Abstract: This paper proposes a new measure of technological obsolescence at the firm-year level using detailed annual patent ownership and citation data. Armed with this measure, we present two sets of results. First, for firms, technological obsolescence foreshadows substantially lower growth, productivity, and reallocation of capital. This finding applies mainly for obsolescence of core innovation and embodied innovation, and it is stronger when product markets are competitive. In stock markets, prices do not fully incorporate technological obsolescence—analysts are too optimistic about obsolete firms’ future profits, leading to an under-performance of 7 percent. Importantly, the measure contains incremental information relative to existing measures that focus on the arrival of new innovation. (JEL: O3, O4).

Song Ma is with Yale University and the NBER. This paper was started during my PhD study at Duke University. Working on this paper constantly reminds me of the joy and pain of working on a solo paper. For continuous support, I want to thank my coauthors and numerous colleagues whose comments and discussions helped shape my thinking around this topic over the years. For detailed comments and discussions, I thank Nick Barberis, Wesley Cohen, Michael Ewens, Laurent Fresard, Stefano Giglio, Paul Goldsmith-Pinkham, Po-Hsuan Hsu, Allen Hu, Bryan Kelly, Lenoid Kogan, Ernest Liu, Yueran Ma, Stavros Panageas, Dimitris Papanikolaou, Bruno Pellegrino, Peter Schott, Kelly Shue, Janis Skrastins, Kaushik Vasudevan, Ting Xu, and Alex Zentefis. I also want to thank workshop participants at BlackRock, Bocconi, FOM Annual Conference (Dartmouth), Harvard, Illinois, LSE, Lugano, Michigan State, NBER Summer Institute (Macroeconomics and Productivity), PKU, Queen Mary, RUC, Toulouse School of Economics, Tulane, UT Dallas, Warwick, Yale (Economics). Xugan Chen provided excellent research assistance. All errors are certainly my own.