Learning (Not) to Evade Taxes
Department of Business and Economics, Institute of Public Economics, University of Muenster, 48143 Muenster, Germany
Games 2019, 10(4), 38; https://doi.org/10.3390/g10040038
Received: 24 July 2019 / Revised: 23 September 2019 / Accepted: 27 September 2019 / Published: 29 September 2019
(This article belongs to the Special Issue Empirical Tax Research and Application)
In this paper, lab experiments on tax compliance were theoretically investigated with dynamic and stochastic methods. It is well known from experimental games that learning allows a better understanding of participants’ behavior. However, it has not been explicitly applied so far in the theoretical analysis of tax compliance experiments. In this paper, it was shown that two decision-making processes may be distinguished: a discrete process in which all options are regarded and an all-or-nothing process in which either the respective tax is paid fully or not at all. The corresponding variant of the learning model was either a stochastic or a deterministic one, with the stochastic version as the more general model. In the additional empirical part of the paper, it was shown that tax payments decline in trend over the rounds of the considered experiment. This negative trend was interpreted as a learning effect, in accordance with the stochastic version of the theoretical model. However, the alternative interpretation that the observed behavior was driven by a tiring effect cannot be completely excluded.
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Keywords:
tax compliance; experiments; deterministic and stochastic learning; discrete decision making; all-or-nothing decision making
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MDPI and ACS Style
Prinz, A. Learning (Not) to Evade Taxes. Games 2019, 10, 38. https://doi.org/10.3390/g10040038
AMA Style
Prinz A. Learning (Not) to Evade Taxes. Games. 2019; 10(4):38. https://doi.org/10.3390/g10040038
Chicago/Turabian StylePrinz, Aloys. 2019. "Learning (Not) to Evade Taxes" Games 10, no. 4: 38. https://doi.org/10.3390/g10040038
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