A search model with subjective judgments: Auditing of incorrect tax declarations

This paper proposes a new search model to deal with public sector decisions in which intangible factors need to be considered along with tangible ones. Such problems are often found in a wide range of administrative investigations and criminal inspections in Japan. In an effort to manage such problems, this article first constructs an Analytic Hierarchy Process (AHP) model to deal with the intangible factors. Then, we reinforce the AHP model by incorporating tangible factors which are not included in the model. The probit and/or logit models are applied to test the statistical significance of this combination, based on a past data set. This model can be considered as a two-stage procedure in the sense that the AHP results (the first stage) are utilized to construct a statistical model in the second stage, which aims at obtaining a better probability of detection. Although this study can foresee the probability of detection for individual objects based on this probability model, there is another important practical issue, i.e. the scheduling of associated officials. Therefore, we propose a scheduling model using mathematical programming methodology. Finally, the proposed model was applied to the investigation work of the Post-Clearance Audit Department of Japanese Customs. It was found that the probability of finding incorrect declarations would be improved from the current 60% to 75–80%. While our problem is not related to criminal activities directly, this study predicts that our approach might be applicable for other governmental investigations and inspections in the scope of this empirical study.