2017
DOI: 10.1080/00343404.2017.1299934
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Regional tax evasion and audit enforcement

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Cited by 16 publications
(10 citation statements)
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References 35 publications
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“…In this model, the coefficient of the dynamic component or persistence (γ) is significant, which means that the average taxpayer learns over time. His or her tax behavior today depends positively on what he or she did in the past, as found by Alm and Yunus (2009) and Carfora, Vega, and Pisani (2018), although in the latter, separately from spatial dependence. As mentioned above, the spatial correlation coefficient (ρ) is also significant, indicating that there is a regional interaction in the tax compliance decision and that this interaction is positive, the same result found by Alm and Yunus (2009) for the United States and Carfora, Vega, and Pisani (2018) for Italy.…”
Section: Estimates Of the Factors Explaining Irpf Compliance In Regionsmentioning
confidence: 82%
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“…In this model, the coefficient of the dynamic component or persistence (γ) is significant, which means that the average taxpayer learns over time. His or her tax behavior today depends positively on what he or she did in the past, as found by Alm and Yunus (2009) and Carfora, Vega, and Pisani (2018), although in the latter, separately from spatial dependence. As mentioned above, the spatial correlation coefficient (ρ) is also significant, indicating that there is a regional interaction in the tax compliance decision and that this interaction is positive, the same result found by Alm and Yunus (2009) for the United States and Carfora, Vega, and Pisani (2018) for Italy.…”
Section: Estimates Of the Factors Explaining Irpf Compliance In Regionsmentioning
confidence: 82%
“…Later, Di Caro and Nicotra (2014) for the period 2007–2011, and Carfora, Vega, and Pisani (2018) for the period 2001–2011, analyze tax compliance for the Italian regions, also using spatial econometric models, although the paper of Carfora, Vega, and Pisani (2018) is not limited to income tax but analyzes total tax gap.…”
Section: Introductionmentioning
confidence: 99%
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“…We argue that spatial measurement models can more accurately characterize the relationship between local government debt and regional economic growth. In the spatial econometrics literature, scholars often use the spatial lag model (SLM), spatial error model (SEM), and SDM to investigate spatial correlation [57][58][59]. Spatial effects may occur simultaneously in the spatial lag of the dependent variable and the variation of the error term caused by the random impact.…”
Section: Basic Regression Modelmentioning
confidence: 99%
“…Andreoni et al 1998, Cerqueti and Coppier, 2011, Orsi et al 2014, Bovi and Cerqueti, 2014, Argentiero and Bollino, 2015 and empirically (see e.g. Carfora et al 2017); on the other hand, an increase in the tax rates may reduce tax compliance (see e.g. Gutmann 1977, Clotfelter 1983, Myles and Naylor 1996.…”
Section: Introductionmentioning
confidence: 99%