scholarly journals Dynamics of tax evasion through an epidemic-like model

2017 ◽  
Vol 28 (02) ◽  
pp. 1750023 ◽  
Author(s):  
Rafael M. Brum ◽  
Nuno Crokidakis

In this work, we study a model of tax evasion. We considered a fixed population divided in three compartments, namely honest tax payers, tax evaders and a third class between the mentioned two, which we call susceptibles to become evaders. The transitions among those compartments are ruled by probabilities, similarly to a model of epidemic spreading. These probabilities model social interactions among the individuals, as well as the government’s fiscalization. We simulate the model on fully-connected graphs, as well as on scale-free and random complex networks. For the fully-connected and random graph cases, we observe that the emergence of tax evaders in the population is associated with an active-absorbing nonequilibrium phase transition, that is absent in scale-free networks.

2007 ◽  
Vol 377 (1) ◽  
pp. 125-130 ◽  
Author(s):  
Xin-Jian Xu ◽  
Zhi-Xi Wu ◽  
Guanrong Chen

2006 ◽  
Vol 17 (12) ◽  
pp. 1815-1822 ◽  
Author(s):  
XIN-JIAN XU ◽  
WEN-XU WANG ◽  
TAO ZHOU ◽  
GUANRONG CHEN

Many real networks are embedded in a metric space: the interactions among individuals depend on their spatial distances and usually take place among their nearest neighbors. In this paper, we introduce a modified susceptible-infected-susceptible (SIS) model to study geographical effects on the spread of diseases by assuming that the probability of a healthy individual infected by an infectious one is inversely proportional to the Euclidean distance between them. It is found that geography plays a more important role than hubs in disease spreading: the more geographically constrained the network is, the more highly the epidemic prevails.


2009 ◽  
Vol 26 (6) ◽  
pp. 068901 ◽  
Author(s):  
Zhang Hai-Feng ◽  
Li Ke-Zan ◽  
Fu Xin-Chu ◽  
Wang Bing-Hong

2002 ◽  
Vol 66 (4) ◽  
Author(s):  
D. Volchenkov ◽  
L. Volchenkova ◽  
Ph. Blanchard

2008 ◽  
Vol 77 (2) ◽  
Author(s):  
Carlo Piccardi ◽  
Renato Casagrandi

2011 ◽  
Vol 390 (3) ◽  
pp. 471-481 ◽  
Author(s):  
Xiangwei Chu ◽  
Zhongzhi Zhang ◽  
Jihong Guan ◽  
Shuigeng Zhou

2014 ◽  
Vol 989-994 ◽  
pp. 4524-4527
Author(s):  
Tao Li ◽  
Yuan Mei Wang ◽  
You Ping Yang

A modified spreading dynamic model with feedback-mechanism based on scale-free networks is presented in this study. Using the mean field theory, the spreading dynamics of the model is analyzed. The spreading threshold and equilibriums are derived. The relationship between the spreading threshold, the epidemic steady-state and the feedback-mechanism is analyzed in detail. Theoretical results indicate the feedback-mechanism can increase the spreading threshold, resulting in effectively controlling the epidemic spreading.


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