Optimal tax trajectories of the Kazakhstan largest 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

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:

The agro-industrial complex of any country forms its food and economic security; it also acts as a guarantor of sustainable development of the socio-economic system. Today, one of the components of the agro-industrial complex, agriculture, contributes to the implementation of a number of life-supporting functions of the state. Thus, due to its geographical location and vast territories, agriculture is one of the most important types of economic activity in Kazakhstan. The current stage of the country’s economic activity is closely related to the development of the fuel and energy industry. The key factor in the development of the industry is a company’s tax strategy.

This article features an analysis of the main large companies of Kazakhstan (Svetland-Oil, Kazgermunai, Potentsial Oil, South Oil, Karatau, Mangistaumunaigas, Katko, Kazburgas, Adzhip Karachaganak), which was performed in order to determine an effective tax policy and increase the capacity of enterprises. The authors have implemented a numerical study of the company’s tax trajectory. Using the Cobb-Douglas model, they describe the production function of companies. The choice of the model coefficients is due to the agreement of the calculation results with the official data.

As a result of taking into account the optimization of the tax trajectory, an increase in fixed assets in the time range of 2008-2017 has been revealed. The authors assume that taking into account the effect of optimization of the tax trajectory will allow increasing the efficiency of distribution of financial and production resources of companies.

References:

1. Bannova K. A., Aktaev N. E., Tyurina Yu. G. 2019. “Mathematical models forecasting the transformation of the tax path of large Russian companies”. Tyumen State University Herald. Social, Economic, and Law Research, vol. 5, no. 3 (19), pp. 193-203. DOI: 10.21684/2411-7897-2019-5-3-193-203 [In Russian]

2. Kazakhstan Taxes: the official website. https://nalogikz.kz [In Russian]

3. Baik B., Kim K., Morton R., Roh Y. 2016. “Analysts’ pre-tax income forecasts and the tax expense anomaly”. Review of Accounting Studies, vol. 21, no. 2, pp. 559-595. DOI: 10.1007/s11142-016-9349-z 

4. Bannova K. A., Aktaev N. E. 2020. “Mathematical modelling of optimal tax trajectory within the framework of Cobb-Douglas model”. Applied Economics Letters, vol. 27, no. 17, pp. 1451-1457. DOI: 10.1080/13504851.2019.1688240

5. Berezka K. M. Masliy V. V. 2011. “Еthodological aspects of applying model of fuzzy time series in forecasting tax revenues”. Actual Problems of Economics, vol. 115, pp. 227-235.

6. Bretschneider S., Gorr W. 1992. “Economic, organizational, and political influences on biases in forecasting state sales tax receipts”. International Journal of Forecasting, no. 7 (4), pp. 457-466. DOI: 10.1016/0169-2070(92)90029-9

7. Breuer C. 2015. “On the rationality of medium-term tax revenue forecasts: evidence from Germany”. Jahrbucher fur Nationalokonomie und Statistik, vol. 235, no. 1, pp. 22-40.

8. Buettner T., Kauder B. 2015. “Political biases despite external expert participation? An empirical analysis of tax revenue forecasts in Germany”. Public Choice, vol. 164, nos. 3-4, pp. 287-307. DOI: 10.1007/s11127-015-0279-2 

9. Christensen R. C., Hearson M. 2019. “The new politics of global tax governance: taking stock a decade after the financial crisis”. Review of International Political Economy, vol. 26, no. 5, pp. 1-21. DOI: 10.1080/09692290.2019.1625802

10. Dhaliwal D. S., Gleason C. A., Mills L. F. 2004. “Last-Chance earnings management: using the tax expense to meet analysts’ forecasts”. Contemporary Accounting Research, vol. 21, no. 2, pp. 431-460. DOI: 10.1506/tfvv-uyt1-nnyt-1yfh

11. Fendek M., Hatrak M., Mlynarovic V. 2001. “The model structure for forecasting, optimization and analysis of tax revenues in the Slovak economy”. Ekonomicky Casopis, vol. 49, no. 5, pp. 941-959.

12. Fisher L. A., Kingston G. 2017. “Improved forecasts of tax revenue via the permanent income hypothesis”. Australian Economic Review, vol. 50, no. 1, pp. 21-31. DOI: 10.1111/1467-8462.12198 

13. Francis J. R., Neuman S. S., Newton N. J. 2019. “Does tax planning affect analysts’ forecast accuracy?”. Contemporary Accounting Research, vol. 36, no. 4, pp. 2663-2694. DOI: 10.1111/1911-3846.12515 

14. Gupta S., Laux R. C., Lynch D. P. 2015. “Do firms use tax reserves to meet analysts’ forecasts? Evidence from the pre- and post-FIN 48 Periods”. Contemporary Accounting Research, vol. 33, no. 3, pp. 1044-1074. DOI: 10.1111/1911-3846.12180

15. Jochimsen B., Lehmann R. 2016. “On the political economy of national tax revenue forecasts: evidence from OECD countries”. Public Choice, vol. 170, nos. 3-4, pp. 211-230. DOI: 10.1007/s11127-016-0391-y 

16. Ju J., Li L., Nie G., Shi K., Wei S. 2019. “Nonlinear capital flow tax: capital flow management and financial crisis prevention in China”. China & World Economy, vol. 27, no. 4, pp. 1-28. DOI: 10.1111/cwe.12284

17. Kanseitkyzy K. A. 2012. “Improvement of the individual income tax as a priority social and economic modernization in Kazakhstan”. International Scientific Forum of the 6^th Ryskulov’s Readings — Socio-Economic Modernization of Kazakhstan Under Conditions of Global Financial Instability, pp. 313-334.

18. Kapenova A., Zhanakova N. 2015. “Some aspects of perfection of tax administration in the republic of Kazakhstan”. Bulletin of the National Academy of Sciences of the Republic of Kazakhstan, no. 6, pp. 163-169.

19. Kaplanoglou G., Rapanos V. T., Daskalakis N. 2016. “Tax compliance behaviour during the crisis: the case of Greek SMEs”. European Journal of Law and Economics, vol. 42, no. 3, pp. 405-444. DOI: 10.1007/s10657-016-9547-y 

20. Kuo Y.-Y., Liang K.-Y. 2004. “Human judgments in New York state sales and use tax forecasting”. Journal of Forecasting, vol. 23, no. 4, pp. 297-314. DOI: 10.1002/for.914 

21. Li-xia Liu, Yi-qi Z., Liu X. 2011. “Tax forecasting theory and model based on SVM optimized by PSO”. Expert Systems with Applications, vol. 38, no. 1, pp. 116-120. DOI: 10.1016/j.eswa.2010.06.022 

22. Lygina O. 2012. “Theoretical & methodological approaches to tax load estimation for various sectors of Kazakhstan’s economy”. Actual Problems of Economics, vol. 137, pp. 388-396.

23. Maekawa S., Fukushige M. 2012. “Tax projections and economic forecasts by government bureaucrats: hidden manoeuverings behind fiscal reconstruction in Japan”. Japanese Economic Review, vol. 63, no. 4, pp. 528-545. DOI: 10.1111/j.1468-5876.2011.00558.x

24. Okafor L. E., Bhattacharya M., Apergis N. 2019. “Bank credit, public financial incentives, tax financial incentives and export performance during the global financial crisis”. The World Economy, vol. 43, no. 1, pp. 114-145. DOI: 10.1111/twec.12848

25. Rich R., Bram J., Haughwout A., Orr J., Rosen R., Sela R. 2005. “Using regional economic indexes to forecast tax bases: evidence from New York”. Review of Economics and Statistics, vol. 87, no. 4, pp. 627-634. DOI: 10.1162/003465305775098215

26. Shnaider E., Kandel A. 1992. “A system for forecasting corporate-tax revenue based on fuzzy logic and fuzzy set theory”. Information Sciences, vol. 63, nos. 1-2, pp. 11-31. DOI: 10.1016/0020-0255(92)90060-l

27. Šimurina N., Barbić D. 2017. “Porezne promjene i dohodovne nejednakosti u Europskoj uniji tijekom financijske krize”. Revija za socijalnu politiku, Svezak 24, Br. 2. DOI: 10.3935/rsp.v24i2.1405

28. Spalek J., Moravansky D. 2005. “Evaluation of tax-revenue forecasts in the CR”. Finance a Uver-Czech Journal of Economics and Finance, vol. 55, nos. 3-4, pp. 162-187.

29. Streimikiene D., Raheem A. R., Vveinhardt J., Ghauri S. P., Zahid S. 2018. “Forecasting tax revenues using time series techniques — a case of Pakistan”. Economic Research-Ekonomska Istraživanja, vol. 31, no. 1, pp. 722-754. DOI: 10.1080/1331677x.2018.1442236

30. Yang C., Zhang Z., Jiao J. 2015. “Error correction method based on data transformational GM (1,1) and application on tax forecasting”. Applied Soft Computing, vol. 37, pp. 554-560. DOI: 10.1016/j.asoc.2015.09.001

31. Yusupov U. B. 2012. “Improving the organization of tax accounting in the republic of Kazakhstan”. Actual Problems of Economics, vol. 131, pp. 495-502.