Preview

Finance: Theory and Practice

Advanced search

Government Policy Impact on the Development of the VAT Rates

https://doi.org/10.26794/2587-5671-2026-30-4-113-125

Abstract

The relevance of the research topic is due to the Indonesian government’s policy plan which will increase the VAT rate from 11% to 12% in early 2025, and has become a hot topic. The aim of this research is to provide the best alternative policy options by providing comprehensive solutions. The research method uses a system dynamics simulation model, employing qualitative and quantitative approaches facilitated by Powersim constructor software by considering three scenarios: pessimistic, moderate, and optimistic. This study uses six main variables and three additional variables. The research results reveal that, in a pessimistic simulation scenario, an increase in the VAT rate will reduce people’s purchasing power and increase tax avoidance. In a moderate scenario simulation, there will be a balance in economic conditions, but in the future, this will reduce the potential for taxes and increase tax avoidance. In an optimistic scenario, reducing the VAT rate will reduce the tax burden, increase potential tax purchasing power, increase exports, and reduce imports, while decreasing tax avoidance and increase tax potential. This research concludes that, of the three scenarios, the best choice is to use the optimistic scenario because it will benefit overall economic conditions. It recommends that the government should reduce the tax avoidance ratio and simplify the supply chain, as supply chain complexity contributes to increased costs.

About the Author

A. A. Samudra
Universitas Muhammadiyah Jakarta
Indonesia

Azhari Aziz Samudra — PhD, Prof., Doctoral Program in Public Policy

Jakarta


Competing Interests:

The author has no conflicts of interest to declare



References

1. Poplawski-Ribeiro M., Yoo J., Haver V., et al. 2023 Global debt monitor. Washington, DC: International Monetary Fund; 2023. 9 p. URL: https://www.imf.org/-/media/files/conferences/2023/2023-09-2023‑global-debt-monitor.pdf (accessed on 09.05.2024).

2. Liu Y., Wang W., Liu C. The effect of a VAT rate reduction on enterprise costs: Empirical research based on China’s VAT reform practice. Frontiers in Environmental Science. 2022;10:912574. DOI: 10.3389/fenvs.2022.912574

3. Waseem M. The role of withholding in the self-enforcement of a value-added tax: Evidence from Pakistan. The Review of Economics and Statistics. 2022;104(2):336-354. DOI: 10.1162/rest_a_00959

4. Đorđević M., Đurović Todorović J., Ristić M. Improving performance of VAT system in developing EU countries: Estimating the determinants of the ratio C-efficiency in the period 1997–2017. Facta Universitatis. Series: Economics and Organization. 2019;16(3):239-254. DOI: 10.22190/FUEO1903239D

5. Erero J. L. Contribution of VAT to economic growth: A dynamic CGE analysis. Journal of Economics and Management. 2021;43(1):22-51. DOI: 10.22367/jem.2021.43.02

6. What is the VAT Gap? European Commission. Taxation and Customs Union. 2019. URL: https://taxation-customs. ec.europa.eu/taxation/vat/fight-against-vat-fraud/vat-gap_en (accessed on 09.05.2024).

7. Samudra A. A. Perpajakan di Indonesia: Keuangan, Pajak dan Retribusi Daerah. 5th ed. Jakarta: PT Rajagrafindo Persada Rajawali Pers; 2023. 336 p. URL: https://www.rajagrafindo.co.id/ (accessed on 09.05.2024).

8. Usman A., Usman A., Abubakar Z. Assessing the impact of value added tax (VAT) gaps on VAT revenue generation in Nigeria. IOSR Journal of Humanities and Social Science. 2019;24(10):68-83. DOI: 10.9790/0837-2410086883

9. Rachman Y., Wulansari D., Amelia Y., et al. Value added tax: Development and issues in Indonesia. Review of International Geographical Education Online. 2021;11(5):923-931. DOI: 10.48047/rigeo.11.05.89

10. Korauš A., Gombár M., Vagaská A., Šišulák S., Černák F. Secondary energy sources and their optimization in the context of the tax gap on petrol and diesel. Energies. 2021;14(14):4121. DOI: 10.3390/en14144121

11. Asri S. A.C., Suseno D. A. The effect of value-added tax policy on per capita income and inequality in Indonesia. Journal of Economics, Business, and Accountancy Ventura. 2023;26(2):220-235. DOI: 10.14414/jebav.v26i2.3526

12. Sonbay E. F., Djamhuri A., Baridwan Z. Tax planning value added tax and Article 4(2) Tax on Income in Indonesia. International Research Journal of Business Studies. 2022;15(1):53-62. DOI: 10.21632/irjbs.15.1.53-62

13. Li F., Yang Z., Hu X. Cross-border dual-channel supply chain decision-making under random demand and tariff conditions. PLoS One. 2024;19(2): e0297923. DOI: 10.1371/journal.pone.0297923

14. Bukina I. S., Smirnov A. I. Tax policy directions in Russia and the possibility of reducing the tax burden on domestic producers operating in the home market. Finance: Theory and Practice. 2020;24(4):104-119. DOI: 10.26794/2587-5671-2020-24-4-104-119

15. Barnert E. S., Scannell C., Ashtari N., Albertson E. Policy solutions to end gaps in medicaid coverage during reentry after incarceration in the United States: Experts’ recommendations. Journal of Public Health. 2022;30(9):2201-2209. DOI: 10.1007/s10389-021-01483-4

16. Al-Rahamneh N. M., Al Zobi M. K., Bidin Z. The influence of tax transparency on sales tax evasion among Jordanian SMEs: The moderating role of moral obligation. Cogent Business & Management. 2023;10(2):2220478. DOI: 10.1080/23311975.2023.2220478

17. Hasan A., Sheikh N., Farooq M. B. Exploring stakeholder perceptions of tax reform failures and their proposed solutions: A developing country perspective. Meditari Accountancy Research. 2023;32(3):721-755. DOI: 10.1108/MEDAR-03-2023-1961

18. Tadesse T. Explaining customs tax evasion in Ethiopia: The effect of trade tax, law enforcement, and product characteristics. Global Journal of Emerging Market Economies. 2023;15(3):330-353. DOI: 10.1177/09749101221100637

19. Lyssiotou P., Savva E. Who pays taxes on basic foodstuffs? Evidence from broadening the VAT base. International Tax and Public Finance. 2021;28(1):212-247. DOI: 10.1007/s10797-020-09605-6

20. Fedoseeva S., Van Droogenbroeck E. Temporary VAT rate cuts and food prices in e-commerce. Journal of Retailing and Consumer Services. 2024;77:103693. DOI: 10.1016/j.jretconser.2023.103693

21. Belyaev V. A. Analysis of the dynamics of IPO transactions in the banking sector. Finance: Theory and Practice. 2021;25(6):16-28. DOI: 10.26794/2587-5671-2021-25-6-16-28

22. Shin H. S., Jeong A. Modeling the relationship between students’ prior knowledge, causal reasoning processes, and quality of causal maps. Computers & Education. 2021;163:104113. DOI: 10.1016/j.compedu.2020.104113

23. Samudra A. A., Hertasning B., Amiro L. Policy for handling air pollution in Jakarta: Study using system dynamics simulation models. Journal of Infrastructure, Policy and Development. 2024;8(2):2969. DOI: 10.24294/jipd.v8i2.2969

24. Esteso A., Alemany M. M.E., Ottati F., Ortiz A. System dynamics model for improving the robustness of a fresh agri-food supply chain to disruptions. Operational Research. 2023;23(2):28. DOI: 10.1007/s12351-023-00769-7

25. Zheng M., Marsh J. K., Nickerson J. V., Kleinberg S. How causal information affects decisions. Cognitive Research: Principles and Implications. 2020;5(1):6. DOI: 10.1186/s41235-020-0206-z

26. Araya A., Dahalan J., Muhammad B. The relationship between financial patterns and exogenous variables: Empirical evidence from symmetric and asymmetric ARDL. International Journal of Business Society. 2022;6(6):638-661. DOI: 10.30566/ijo-bs/2022.06.90

27. Ludji D. G., Sianturi P., Nugrahani E. H. Dynamical system of the mathematical model for tuberculosis with vaccination. ComTech: Computer, Mathematics and Engineering Applications. 2019;10(2):59-66. DOI: 10.21512/comtech.v10i2.5686

28. Zídková H., Arltová M., Josková K. Does the level of e-government affect value-added tax collection? A study conducted among the European Union member states. Policy & Internet. 2024;16(3):567-587. DOI: 10.1002/poi3.389

29. Schoenenberger L., Schmid A., Tanase R., Beck M., Schwaninger M. Structural analysis of system dynamics models. Simulation Modelling Practice and Theory. 2021;110:102333. DOI: 10.1016/j.simpat.2021.102333

30. Samara E., Kilintzis P., Katsoras E., Martnidis G., Kosti P. A system dynamics approach for the development of a regional innovation system. Journal of Innovation and Entrepreneurship. 2024;13(1):26. DOI: 10.1186/s13731-024-00385-5

31. Samudra A. A. Property tax in Indonesia: A proposal for increasing land and building tax revenue using the system dynamics simulation method. Journal of Tax Reform. 2024;10(1):100-121. DOI: 10.15826/jtr.2024.10.1.159

32. Paudel A. C., Doranga S., Li Y., Khanal M. System identification and dynamic analysis of the propulsion shaft systems using response surface optimization technique. Applied Mechanics. 2024;5(2):305-321. DOI: 10.3390/applmech5020018

33. Hakim L., Widyawati, Monalisa, Safrida. Behavior and performance of the integrated farming system model for cassava agribusiness development in Aceh Besar regency. IOP Conference Series: Earth and Environmental Science. 2024;1297:012025. DOI: 10.1088/1755-1315/1297/1/012025

34. Naumov I. V., Nikulina N. L. Scenario modelling of the impact of the dynamics of public debt on the gross regional product of Russian regions. Finance: Theory and Practice. 2021;25(6):68-84. DOI: 10.26794/2587-5671-2021-25-6-68-84

35. Wellek S. Testing for goodness rather than lack of fit of continuous probability distributions. PLoS One. 2021;16(9): e0256499. DOI: 10.1371/journal.pone.0256499

36. Mohizin A., Imran J. H., Lee K. S., Kim J. K. Dynamic interaction of injected liquid jet with skin layer interfaces revealed by microsecond imaging of optically cleared ex vivo skin tissue model. Journal of Biological Engineering. 2023;17(1):15. DOI: 10.1186/s13036-023-00335-x

37. Kim Y., Choi S., Yi M. Y. Applying comparable sales method to the automated estimation of real estate prices. Sustainability. 2020;12(14):5679. DOI: 10.3390/su12145679

38. Song Y., Sebe N., Wang W. Fast differentiable matrix square root and inverse square root. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2023;45(6):7367-7380. DOI: 10.1109/TPAMI.2022.3216339

39. Zhu S., Zhan H., Yan Z., et al. Prediction of spherical equivalent refraction and axial length in children based on machine learning. Indian Journal of Ophthalmology. 2023;71(5):2115-2131. DOI: 10.4103/IJO.IJO_2989_22

40. Joshi B., Craciun G. Foundations of Static and Dynamic Absolute Concentration Robustness. Journal of Mathematical Biology. 2022;85(5):53. DOI: 10.1007/s00285-022-01823-2

41. Jara Aguirre J. C., Norgan A. P., Cook W. J., Karon B. S. Error simulation modeling to assess the effects of bias and precision on bilirubin measurements used to screen for neonatal hyperbilirubinemia. Clinical Chemistry and Laboratory Medicine. 2021;59(6):1069-1075. DOI: 10.1515/cclm-2020-1640


Review

For citations:


Samudra A.A. Government Policy Impact on the Development of the VAT Rates. Finance: Theory and Practice. 2026;30(4):113-125. https://doi.org/10.26794/2587-5671-2026-30-4-113-125

Views: 78

JATS XML


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 2587-5671 (Print)
ISSN 2587-7089 (Online)