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Abstract

The purpose of this paper is to empirically re-explore the effects of current and lagged R&D expenditures on Tobin’s Q for selected ten US IT companies (Apple, Alphabet, Microsoft, Facebook/ Meta, Dell Technologies, Intel Corp, IBM, HP Inc, Cisco Systems, Oracle). These companies have been selected for their visible and enduring dominance in term of market-capitalization in the US IT sector. They belong to the magnificent 7 as well that approximately constitute 30% of the S&P 500 index value. The empirical methodology involves the implementation of the Ordinary Least Squares (OLS) upon satisfying the statistical requirements for its suitability. Annual data are used with differing sample periods across these companies due to complete availability of data. Unduly wide variabilities are observed in their year-to-year R&D expenditures. The current and lagged explanatory variables negatively correlate with current Tobin’s Q with some minor exceptions. Their net effects range from zero to negative in most cases, amid a few exceptions. To conclude, the findings are conditioned on how the spendings for R&D are expensed and the length of the gestation period between R&D spending and the unpredictable outcomes. The findings of this paper are supported by de Andres et al (2017, 2021), Oriani and Sabrero (2008), Coad and Rao (2010), Arad and Weill (2007), and Li and Tallman (2011).
Keywords:  Tobin’s Q, R&D, Correlation, Regression, Causality, Net Effect
JEL Classifications: G10, G30, G39.