Παρακαλώ χρησιμοποιήστε αυτό το αναγνωριστικό για να παραπέμψετε ή να δημιουργήσετε σύνδεσμο προς αυτό το τεκμήριο: https://ruomo.lib.uom.gr/handle/7000/208
Πλήρης εγγραφή μεταδεδομένων
Πεδίο DCΤιμήΓλώσσα
dc.contributor.authorPapadopoulou, Paraskevi-
dc.contributor.authorHristu-Varsakelis, Dimitrios-
dc.contributor.editorDemetriou, Ioannis C.-
dc.contributor.editorPardalos, Panos M.-
dc.date.accessioned2019-10-29T06:30:17Z-
dc.date.available2019-10-29T06:30:17Z-
dc.date.issued2019-01-
dc.identifier.isbn978-3-030-12767-1en_US
dc.identifier.urihttps://ruomo.lib.uom.gr/handle/7000/208-
dc.description.abstractMotivated by the persistent phenomenon of tax evasion and the challenge of tax collection during economic crises, we explore the behavior of a risk-neutral self-interested firm that may engage in tax evasion to maximize its profits. The firm evolves in a tax system which includes many of ``standard'' features such as audits, penalties, and occasional tax amnesties, and may be uncertain as to its tax status (not knowing, for example, whether a tax amnesty may be imminent). We show that the firm's dynamics can be expressed via a partially observable Markov decision process and use that model to compute the firm's optimal behavior and expected long-term discounted rewards in a variety of scenarios of practical interest. Going beyond previous work, we are able to investigate the effect of ``leaks'' or ``pre-announcements'' of any tax amnesties on the firm's behavior (and thus on tax revenues). We also compute the effect on firm behavior of any extensions of the statute of limitations within which the firm's tax filings can be audited, and show that such extensions can be a significant deterrent against tax evasion.en_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofseriesSpringer Optimization and Its Applicationsen_US
dc.subjectFRASCATI::Engineering and technology::Electrical engineering, Electronic engineering, Information engineeringen_US
dc.titleTax evasion as an optimal solution to a partially observable Markov decision processen_US
dc.typeBook chapteren_US
dc.contributor.departmentΤμήμα Εφαρμοσμένης Πληροφορικήςen_US
local.identifier.volume145en_US
local.identifier.firstpage219en_US
local.identifier.lastpage237en_US
local.identifier.volumetitleApproximation and Optimization : Algorithms, Complexity and Applicationsen_US
Εμφανίζεται στις Συλλογές: Τμήμα Εφαρμοσμένης Πληροφορικής

Αρχεία σε αυτό το Τεκμήριο:
Αρχείο Περιγραφή ΜέγεθοςΜορφότυπος 
Papadopoulou_Hristu_COACA2017.pdf491,25 kBAdobe PDFΠροβολή/Ανοιγμα


Τα τεκμήρια στο Αποθετήριο προστατεύονται από πνευματικά δικαιώματα, εκτός αν αναφέρεται κάτι διαφορετικό.