A multi-populated mean-field model applied on financial data from U.S. pharmaceutical and biotechnological companies is used to measure if a company investing in Research and Development (R&D) is influenced by the interaction with other firms (peer-to-peer effect). This model allows us to estimate the mutual influence among firms as well as their own inner propensity to invest in R&D. Our database covers the period 1989 – 2012. We validate our results out of sample by comparing them with the data of the period 2013 – 2019. The model is descriptive of the status quo of this investment behavior and it allows predictions to be made at industry and firm level.
A statistical mechanics approach to measure peer-to-peer effects in Pharma research and development investments / Ferrari, Mascia; Fedele, Micaela; Luzi, Rachele; Vernia, Cecilia. - In: PHYSICA. A. - ISSN 0378-4371. - (2025), pp. 1-30. [10.1016/j.physa.2024.130297]
A statistical mechanics approach to measure peer-to-peer effects in Pharma research and development investments
Ferrari, Mascia;Vernia, Cecilia
2025
Abstract
A multi-populated mean-field model applied on financial data from U.S. pharmaceutical and biotechnological companies is used to measure if a company investing in Research and Development (R&D) is influenced by the interaction with other firms (peer-to-peer effect). This model allows us to estimate the mutual influence among firms as well as their own inner propensity to invest in R&D. Our database covers the period 1989 – 2012. We validate our results out of sample by comparing them with the data of the period 2013 – 2019. The model is descriptive of the status quo of this investment behavior and it allows predictions to be made at industry and firm level.
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