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R&D intensity and the effective tax rate : a meta-regression analysis
Belz, Thomas
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Hagen, Dominik von
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Steffens, Christian
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DOI:
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https://doi.org/10.1111/joes.12181
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URL:
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http://onlinelibrary.wiley.com/doi/10.1111/joes.12...
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Weitere URL:
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https://www.researchgate.net/publication/315407518...
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Dokumenttyp:
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Zeitschriftenartikel
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Erscheinungsjahr:
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2017
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Titel einer Zeitschrift oder einer Reihe:
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Journal of Economic Surveys
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Band/Volume:
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31
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Heft/Issue:
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4
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Seitenbereich:
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988-1010
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Ort der Veröffentlichung:
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Oxford [u.a.]
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Verlag:
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Wiley-Blackwell
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ISSN:
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0950-0804 , 1467-6419
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Sprache der Veröffentlichung:
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Englisch
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Einrichtung:
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Fakultät für Betriebswirtschaftslehre > ABWL u. Betriebswirtschaftliche Steuerlehre (Schreiber 1999-2019)
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Fachgebiet:
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330 Wirtschaft
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Fachklassifikation:
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JEL:
F23 , H25 , H26 , M41,
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Freie Schlagwörter (Englisch):
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Effective tax rate , R&D intensity , Intangible assets , Profit shifting , Tax accounting , Meta-regression analysis
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Abstract:
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We apply meta-regression techniques to provide a quantitative review of the empirical literature on how research and development (R&D) expenses affect the effective tax rate (ETR). R&D expenses relate to a well-accepted profit shifting channel, strategic placement of intellectual property within a multinational entity. Using a unique hand-collected data set, we add a new perspective to the current base erosion and profit shifting (BEPS) state of research and debate, in three ways: First, observing that primary studies report mixed evidence on how R&D expenses affect ETR, we provide a consensus estimate for this effect. Second, we consider this effect in more detail by separating a tax accounting effect and a profit shifting effect, which to our knowledge has not yet been investigated. We detect that one-third of the R&D effect on the ETR is due to the tax accounting effect and could be mitigated via book-tax conformity. We further find that 10% of the profit shifting effect can be traced back to R&D tax credits. Third, our meta-regression reveals factors that are possible sources of variation and bias in previous empirical studies.
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