Mathematical models forecasting the transformation of the tax path of large russian companies

About the authors:

Bannova Kristina A., Cand. Sci. (Econ.), Head of the Department of Economics and Finance, University of Tyumen; k.a.bannova@utmn.ru; ORCID: 0000-0002-3603-2659

Nurken E. Aktaev , Cand. Sci. (Phys.-Math.), Research Associate, University of Tyumen n.e.aktaev@utmn.ru

Tyurina Yulia G., Dr. Sci. (Econ.), Associate Professor, Professor, Department of Social Finance, Financial University under the Government of the Russian Federation (Moscow); u_turina@mail.ru; ORCID: 0000-0002-5279-4901

Abstract:

Digital technologies have changed the relationship between the society and business entities, taxpayers and the state. Ceteris paribus, the ability to effectively manage financial flows and make administrative decisions depends on the correct and established interaction between the state and taxpayers.
This study aims to form and develop a taxpayer’s understanding of the digital age with all its features and opportunities for information and communication technologies, including mathematical modeling methods that form the basis of the digital economy for building and sustaining business development, improving the systemic vision of business processes. The research hypothesis is that the further development of economic entities management in the digital context, as well as the coordination of these entities’ interests, is possible only in the partnership of the key economic participants, with the taxpayer at the forefront. That will allow identifying the areas for improving tax trajectories.
Using polynomial approximation, the authors have obtained the models of tax trajectories of companies that allow predicting tax burden. The data for approximations are obtained using the previously constructed mathematical model of the optimal tax path. The main input data of the model are fixed assets and human resources, the totality of which form the production function.
The analysis of the transformation of tax paths shows ways for achieving a balance of interests between both the state and the taxpayers. Finding this balance will help to overcome the crisis of confidence in the authorities, the development of adaptability and creativity of Russian society to new tax changes. A number of parameters determines the scale of this task. They include the complexity of the object of study, the long-term and multi-aspect nature of the impact which modeling the digital economy has on adaptation to the new digital realities of the state and taxpayers, as well as the absence of significant analogues of the solution to this problem in global and Russian economics.

References:

1. Bannova K. A., Aktaev N. E. 2018. “Optimal tax management model for standard types of production functions”. The bulletin of the Far Eastern Federal University. Economics and Management, no 2 (86), pp. 38-44. [In Russian]

2. Bannova K. A., Aktaev N. E. 2017. “Mathematical modeling of maximization of output in the formation of the optimal tax burden”. The bulletin of the Far Eastern Federal University. Economics and Management, no 2 (82), pp. 33-38. [In Russian]

3. Bach S., Corneo G., Steiner V. 2012. “Optimal top marginal tax rates under income splitting for couples”. European Economic Review, no 56, pp. 1055-1069.

4. Bannova K. A., Aktaev N. E. 2019. “Mathematical modelling of optimal tax trajectory within the framework of Cobb-Douglas model”. Applied Economics Letters, pр. 1-7. DOI: 10.1080/13504851.2019.1688240 (accepted).

5. Barhoumi K., Cherif R., Rebei N. 2018. “Stochastic trends and fiscal policy”. Economic Modelling, no 75, pp. 256-267.

6. Belan P., Gauthier S. 2006. “Optimal indirect taxation with a restricted number of tax rates”. Economic Modelling, no 90, pp. 1201-1213.

7. Bhattarai K., Bachman P., Conte F., Haughton J., Head M., Tuerc D. 2017. “Tax plan debates in the US presidential election: a dynamic CGE analysis of growth and redistribution trade-offs”. Economic Modelling, no 68, pp. 529-542.

8. Biddle J. 2012. “The introduction of the Cobb-Douglas regression”. Journal of Economic Perspectives, vol. 26, no 2, pp. 223-236.

9. Bohácek R., Kejak M. 2018. “Optimal government policies in models with heterogeneous agents”. Journal of Economic Theory, no 176, pp. 834-858.

10. Castelletti-Font B., Clerc P., Lemoine M. 2018. “Should euro area countries cut taxes on labour or capital in order to boost their growth?”. Economic Modelling, no 71, pp. 279-288.

11. Celimene F., Dufrenot G., Mophou G., N’Gurekata G. 2014. “Tax evasion, tax corruption and stochastic growth”. Economic Modelling, no 52, pp. 251-258.

12. Cheng M. L., Han Y. 2014. “A modified Cobb-Douglas production function model and its application”. IMA journal of management mathematics, no 25, pp. 353-365.

13. Choi Y., Kim S. 2016. “Dynamic scoring of tax reforms in a small open economy model”. Economy Modelling, no 58, pp. 182-193.

14. Dahan M., Strawczynski M. 2012. “The optimal asymptotic income tax rate”. Journal of Public Economic Theory, no 14, pp. 737-755.

15. Dahan M., Strawczynski M. 2000. “Optimal income taxation: an example with a U-Shaped pattern of optimal marginal tax rates: comment”. The American Economic Review, no 90, pp. 681-686.

16. Diamond P., Helms L. 1980. “Optimal taxation in a stochastic economy. A Cobb-Douglas example”. Journal of Public Economics, no 14, pp. 1-29.

17. Eichert W. 2014. “Long-period positions in multi-sectorial Cobb-Douglas economies”. Metroeconomica, no 65, pp. 136-153.

18. Gaffeo E., Molinari M. 2017. “Taxing financial transactions in fundamentally heterogeneous markets”. Economic Modelling, no 64, pp. 322-333.

19. Guo J., Krause A. 2015. “Dynamic income taxation without commitment: comparing alternative tax systems”. Economic Modelling, no 47, pp. 319-326.

20. Kaneko M. 1982. “The optimal progressive income tax. The existence and the limit tax rate”. Mathematical Social Sciences, no 3, pp. 193-222.

21. Minabe N. 1980. “The possible shapes of the production possibility curve under Cobb-Douglas production function”. European Economic Review, no 14, pp. 1-8.

22. Mitra S. 2017. “To tax or not to tax? When does it matter for informality?”. Economic Modelling, no 64, pp. 117-127.

23. Morimoto H., Zhou X. 2008. “Optimal consumption in a growth model with the Cobb-Douglas production function”. SIAM Journal on Control and Optimization, no 47, pp. 2991-3006.

24. Muro K. 2013. “A note on the three-sector Cobb-Douglas GDP function”. Economic Modeling, no 31, pp. 18-21.

25. Myles G. 2000. “On the optimal marginal rate of income tax”. Economics Letters, no 66, pp. 113-119.

26. Newbery D. 1997. “Optimal tax rates and tax design during systemic reform”. Journal of Public Economics, no 63, pp. 177-206.

27. Richardson G., Taylor G., Lanis R. 2015. “The impact of financial distress on corporate tax avoidance spanning the global financial crisis: evidence from Australia”. Economic Modeling, no 44, pp. 44-53.

28. Saez E. 2001. “Using elastic to derive optimal income tax rate”. Review of Economic Studies, no 68, pp. 205-229.

29. Sanz-Sanz J. F. 2016. “The Laffer curve in scheduler multi-rate income taxes with non-genuine allowances: an application to Spain”. Economic Modelling, no 55, pp. 42-56.

30. Shen Z., Hassani A., Shi Q. 2016. “Multi-objective time-cost optimization using Cobb-Douglas production function and hybrid genetic algorithm”. Journal of Civil Engineering and Management. 22, 187-198.

31. Yang Z. 2016. “Tax reform, fiscal decentralization, and regional economic growth: new evidence from China”. Economic modelling. 59, 520-528.

32. Zhang L., Ru Y., Li J. 2016. “Optimal tax structure and public expenditure composition in a simple model of endogenous growth”. Economic modelling. 59, 352-360.