Data Modeling and Visualization of Tax Strategies Employed by Overseas American Individuals and Firms

Miller, Alfred H.

doi:10.1007/978-3-030-12839-5_28

Cited by 2 publications

(3 citation statements)

References 13 publications

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“…Mwanza and Phiri used intelligent mining algorithm in the research of tax data to realize the outlier algorithm of fraud detection, continuous monitoring based on distance and outlier query based on distance, which improved the accuracy of abnormal data analysis [10]. Miller used KH coder's data mining technology to model individual tax behavior and used unsupervised machine learning text mining and modeling technology to help conduct large-scale analysis of tax behavior methods and find the problems of avoidance and tax evasion in time [11]. Battiston et al used machine learning algorithm for tax analysis in their research and proposed a loss function to analyze the difference between ideal tax and display [12].…”

Section: State Of the Artmentioning

confidence: 99%

Application of Optimized Support Vector Machine Model in Tax Forecasting System

Xin

2022

Journal of Function Spaces

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Tax forecast has an important impact on financial budget and tax plan. The amount of tax data is greatly increased, the difficulty of tax forecast is improved, and the accuracy is always difficult to keep up with the development demand. Analyze the application of optimized support vector machine model in tax prediction system. Based on the simple analysis of the research situation of tax prediction and the research status of data mining algorithm in tax data classification and prediction, this paper constructs a tax prediction model. Aiming at the problem of too many influencing factors of tax prediction, this paper puts forward the use of principal component analysis to extract the main factors, reduce the dimension of tax data, and reduce the difficulty of analysis. Support vector machine is used to realize tax prediction, aiming at the problem of parameter optimization proposed to optimize the parameters. Finally, the prediction accuracy is evaluated by comparing the error between tax prediction value and real value. The results show that the algorithm used in this paper can optimize the parameters of support vector machine. The tax prediction results show that the predicted value is similar to the real value curve. After grid search optimization, the introduction of principal component analysis reduces the redundancy and improves the prediction accuracy.

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Section: State Of the Artmentioning

confidence: 99%

Application of Optimized Support Vector Machine Model in Tax Forecasting System

Xin

2022

Journal of Function Spaces

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“…Tax evasion may also be classified based on individual, organizational, or corporate levels but is found worldwide. The finding of tax evasion at the individual level is supported by vast and recent literature (Alstadsaeter, Johannesen, & Zucman, 2019;Austin et al, 2019;Besley, Jensen, & Persson, 2019;Clotfelter, 1983;Miller, 2019;Richardson, 2006). Alstadsaeter et al (2019) measured tax evasion in Scandinavia by comparing the leaked customer list obtained from offshore financial institutions and administrative wealth records and found that rich people evade more tax.…”

Section: Literature Review and Hypothesis Developmentmentioning

confidence: 83%

“…Individuals try to be in gain states rather than loss states during change. Miller (2019) explored small firms and American individuals for tax evasion. The author used text analysis based on multiple reports obtained from numerous sources.…”

Section: Literature Review and Hypothesis Developmentmentioning

confidence: 99%

Cryptocurrencies-tax evasion nexus: Does economic performance matter? The case of G-7 countries

Nawaz,

Bhutto,

Khan

2023

Preprint

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The global challenge of tax evasion presents a profound impact, leading to diminished tax revenues that are the lifeblood of a nation's seamless operations. This issue is exacerbated by the ingenious strategies employed by tax evaders, which distort economic performance benchmarks and create financial imbalances. Amidst these concerns, cryptocurrencies have emerged as a contentious subject, accused of abetting tax evasion. The covert nature of cryptocurrency transactions poses a significant hurdle for regulatory oversight and transaction recording. In response to this burgeoning concern, our comprehensive study delves into the intricate interplay between cryptocurrencies and tax evasion, utilizing annual data spanning from 2013 to 2020. With an extensive scope testing thirty two hypotheses and twelve interaction terms, our research unfurls the multifaceted dynamics at play. This study embarks by constructing a latest tax evasion index for the esteemed G-7 nations. Employing asymmetric/symmetric panel techniques, our investigation unveils a compelling revelation: cryptocurrencies exert a counteractive influence on instances of tax evasion. Furthermore, the nexus between economic performance and cryptocurrencies bears considerable sway over their correlation with tax evasion. Innovatively, our research charts the intricate relationship between tax evasion and cryptocurrencies across varying levels of economic performance. Notably, our findings underscore that Economic Freedom, Government Integrity, Government Spending, Business Freedom, Labor Freedom, Monetary Freedom, Investment Freedom, and Bureaucracy function as moderators, influencing the association between tax evasion and cryptocurrencies. These insights transcend academia, delivering significant implications to policymakers with informed guidance to devise nuanced strategies and policies.

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Data Modeling and Visualization of Tax Strategies Employed by Overseas American Individuals and Firms

Cited by 2 publications

References 13 publications

Application of Optimized Support Vector Machine Model in Tax Forecasting System

Application of Optimized Support Vector Machine Model in Tax Forecasting System

Cryptocurrencies-tax evasion nexus: Does economic performance matter? The case of G-7 countries

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