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11 Am. U. Bus. L. Rev. 1 (2022)
Empirical Evidence on Robot Taxation: Literature Review and Technical Analysis

handle is hein.journals/aubulrw11 and id is 10 raw text is: 








     EMPIRICAL EVIDENCE ON ROBOT

     TAXATION: LITERATURE REVIEW

          AND TECHNICAL ANALYSIS


                      BRET  N. BOGENSCHNEIDER*


     The literature on robot taxation has continued to expand since 2018 with
     numerous articles now referring to empirical evidence. The evidence
     presented in prior studies comprises abstract modeling and statistical
     pattern reviews with no statistically significant findings reported to date.
     Notably, one article is an advocacy piece by a tech lobbyist who at one
     point purchased priority Google results for the search robot taxation.
     In some cases, technical errors are sufficient to reverse the stated results.
     Examples of error in empirical analyses include (i) motivated reasoning,
     such as the failure to model simpler or best explanations; (ii) lack of
     causal analysis; (iii) tax technical errors; (iv) omission of citations to
     conflicting theory or results; (v) errors in accounting methods; (vi)
     enhanced degrees offreedom in modeling parameters; and (vii) reliance
     on economic  theories not reflecting robots as a fourth factor of
     production. The empirical evidence indicates that capital investment,
     such as in robots, occurs largely in higher tax nations, and that robot
     density is positively associated with high corporate tax rates, such as in
     Germany, Japan, South Korea, and the Nordic states, with little or no
     automation occurring in tax havens where the value of tax deductions for
     capital investment is zero.



I. Introdu ction ................................................................................ . .  2
II. Technical Errors in the Empirical Evidence on
       R obot T axation ..................................................................... 7
III. Literature Review: Empirical Evidence on
       Robot Taxation ........................................................................18
       A. Technequality (Statistical Trends in EU Public
           Finances Related to Robots).............................................18


* PhD; J.D.; LL.M. Associate Professor of Accounting, State University of New York,
Plattsburgh. Thanks to participants in the Southeastern Institute for Operations Research
and the Management Sciences 2021 conference.


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