Tax Administration Transformation and Tax Revenue Collection in Kenya: An ARDL Bounds-Testing Approach

This paper evaluates the joint effect of the Kenya Revenue Authority’s (KRA) three-pronged tax administration transformation signaled by iTax system usage, tax base expansion and data-driven compliance, on domestic tax revenue collection. No prior study has jointly evaluated these three reforms using national-level time-series data, a gap this paper addresses. Quarterly secondary data covering January 2014 to March 2023 (N = 37) were obtained from KRA and analyzed using a correlational design. Based on Augmented Dickey-Fuller and Phillips-Perron unit-root tests confirmation of mixed order integration among the series, an autoregressive distributed lag (ARDL) bounds-testing approach to cointegration was applied. This was complemented by an error-correction model (ECM) and pairwise Granger causality tests. iTax usage correlated weakly with revenue (r = 0.29), tax base expansion (r = 0.84) and compliance (r = 0.95) correlated strongly. The bounds F-statistic (11.91) confirmed long-run cointegration. In the long run, compliance raised revenue by 114 per cent (p = 0.000), while tax base expansion (–12 per cent, p = 0.033) and iTax usage (–8 per cent, p = 0.152) were associated with revenue declines. The error-correction term adjusted at 209 per cent per quarter, and the model explained 88 per cent of revenue variance, passing all residual diagnostics. Causality ran bidirectionally between iTax usage and revenue, and unidirectionally from base expansion and from compliance to revenue. The findings suggested that Kenya’s revenue reforms should be sequenced. Investment in data-driven compliance and enforcement be prioritized, followed by deeper iTax system integration. Base-expansion drives should be paired always with monitoring of the existing taxpayer base.
Keywords: iTax, tax base expansion, data-driven compliance, ARDL bounds testing, tax revenue collection

Public Finance-Economics

1. Ameyaw, B., Oppong, A., Abruquah, L. A., & Ashalley, E. (2016). Informal sector tax compliance issues and the causality nexus between taxation and economic growth: Empirical evidence from Ghana. Modern Economy, 7(12), 1478–1497. [Google Scholar] [Crossref]

2. Annrita, W. N. (2019). Effect of iTax platform on Kenya Revenue Authority’s revenue collection target among large taxpayers [Unpublished master’s thesis]. United States International University – Africa. [Google Scholar] [Crossref]

3. Bagozzi, R. P., Davis, F. D., & Warshaw, P. R. (1992). Development and test of a theory of technological learning and usage. Human Relations, 45(7), 659–686. [Google Scholar] [Crossref]

4. Benaihia, K., & Omondi, A. (2017). Contribution of iTax system as a strategy for revenue collection at Kenya Revenue Authority, Rift Valley region, Kenya [Unpublished thesis]. University of Kabianga. [Google Scholar] [Crossref]

5. Benbasat, I., & Barki, H. (2007). Quo vadis, TAM? Journal of the Association for Information Systems, 8(4), 211–218. [Google Scholar] [Crossref]

6. Besley, T., & Persson, T. (2009). The origins of state capacity: Property rights, taxation, and politics. American Economic Review, 99(4), 1218–1244. [Google Scholar] [Crossref]

7. Besley, T., & Persson, T. (2010). State capacity, conflict, and development. Econometrica, 78(1), 1–34. [Google Scholar] [Crossref]

8. Brun, J.-F., Chambas, G., Tapsoba, J., & Wandaogo, A. A. (2020). Are ICTs boosting tax revenues? Evidence from developing countries [Working paper]. CERDI. [Google Scholar] [Crossref]

9. Chuttur, M. (2009). Overview of the technology acceptance model: Origins, developments and future directions. Sprouts: Working Papers on Information Systems, 9(37). [Google Scholar] [Crossref]

10. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008 [Google Scholar] [Crossref]

11. Eissa, N., Zeitlin, A., Karpe, S., & Murray, S. (2014). Incidence and impact of electronic billing machines for VAT in Rwanda [Working paper]. International Growth Centre. [Google Scholar] [Crossref]

12. Ekeocha, P. C., Ekeocha, C. S., Malaolu, V., & Oduh, M. O. (2012). Revenue implications of Nigeria’s tax system. Journal of Economics and Sustainable Development, 3(8), 206–215. [Google Scholar] [Crossref]

13. Fan, H., Liu, Y., Qian, N., & Wen, J. (2024). Technological adoption and taxation: The case of China’s golden tax reform. Tax Policy and the Economy, 38(1), 101–122. [Google Scholar] [Crossref]

14. Gaspar, V., Jaramillo, L., & Wingender, P. (2016). Tax capacity and growth: Is there a tipping point? (Working Paper No. WP/16/234). International Monetary Fund. [Google Scholar] [Crossref]

15. Gujarati, D. N. (2004). Basic econometrics (4th ed.). McGraw-Hill. [Google Scholar] [Crossref]

16. Kagina, A. C. (2015). The transformation of Uganda Revenue Authority: What lessons can we learn from the URA case study? [Unpublished MA thesis]. Uganda Christian University. [Google Scholar] [Crossref]

17. Kandil, M. (2002). Macroeconomic shocks and dynamics in the Arab world. IMF/University of Wisconsin. [Google Scholar] [Crossref]

18. Livoi, G. M. (2017). The effect of tax reforms on corporate tax compliance to Kenya Revenue Authority [Doctoral dissertation, KCA University]. [Google Scholar] [Crossref]

19. Maganya, M. H. (2020). Tax revenue and economic growth in developing country: An autoregressive distribution lags approach. Central European Economic Journal, 7(54), 205–217. [Google Scholar] [Crossref]

20. Magumba, M. (2019). Tax administration reforms: Lessons from Georgia and Uganda [Details to be confirmed by author against original source]. [Google Scholar] [Crossref]

21. Mascagni, G., Mengistu, A. T., & Woldeyes, F. B. (2021). Can ICTs increase tax compliance? Evidence on taxpayer responses to technological innovation in Ethiopia. Journal of Economic Behavior & Organization, 189, 172–193. [Google Scholar] [Crossref]

22. Murunga, J., Muriithi, M., & Wawire, N. W. (2021). The size of the informal sector and tax revenue in Kenya. Journal of Economics and Public Finance, 7(5), 15–28. https://doi.org/10.22158/jepf.v7n5p15 [Google Scholar] [Crossref]

23. Musgrave, R. A., & Musgrave, P. B. (1959). The theory of public finance: A study in public economy. McGraw-Hill. [Google Scholar] [Crossref]

24. Nwaorgu, I. A., Herbert, W. E., & Onyilo, F. (2016). A longitudinal assessment of tax reforms and national income in Nigeria: 1971–2014. International Journal of Economics and Finance, 8(8), 43–52. [Google Scholar] [Crossref]

25. OECD. (2022). Tax administration 2022: Comparative information on OECD and other advanced and emerging economies. OECD Publishing. [Google Scholar] [Crossref]

26. Oeta, A. N. (2017). iTax and revenue collection by Kenya Revenue Authority in Western Region, Kenya [Unpublished thesis]. University of Nairobi. [Google Scholar] [Crossref]

27. Okunogbe, O., & Pouliquen, V. (2022). Technology, taxation, and corruption: Evidence from the introduction of electronic tax filing. American Economic Journal: Economic Policy, 14(1), 341–372. [Google Scholar] [Crossref]

28. Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289–326. [Google Scholar] [Crossref]

29. Schneider, F. (2005). Shadow economies around the world: What do we really know? European Journal of Political Economy, 21(3), 598–642. [Google Scholar] [Crossref]

30. Senoga, E. B., Matovu, J. M., & Twimukye, E. P. (2009). Tax evasion and widening the tax base in Uganda (Working Paper No. 677-2016-46660). [Google Scholar] [Crossref]

31. World Bank. (2012). Fighting corruption in public services: Chronicling Georgia’s reforms. World Bank. [Google Scholar] [Crossref]

32. Masibayi, P. S., & Kuso, Y. (2026). Powering industrial growth in Kenya: The role of renewable energy generation in manufacturing. International Journal of Research and Innovation in Social Science. [Google Scholar] [Crossref]

33. Owino, B. O., & Kuso, Y. (2026). The influence of ethnicity on public policy: Through the lens of political party formulation in Kenya. International Journal of Advanced Research. [Google Scholar] [Crossref]

34. Christine, J., & Kuso, Y. (2026). Guns vs. butter: Trade-offs analysis of Kenya's national budget 2020-2025. International Research Journal of Advanced Engineering and Technology. [Google Scholar] [Crossref]

35. Onyimbi, N., & Kuso, Y. (2026). The effect of corruption in the declining health service provision: A case study of Kenya. International Journal of Advanced Research in Social Sciences and Humanities. [Google Scholar] [Crossref]

36. Onong’no, O. G., & Kuso, Y. (2026). Evaluating public policy communication strategies in Kenya’s health sector reforms: An analysis of the NHIF–SHA transition in Kisumu County. International Journal of Innovative Science and Research Technology. [Google Scholar] [Crossref]

37. Onyango, O. B., & Kuso, Y. (2026). Understanding unemployment in Kenya: A dual-sided analysis of demand-side and supply-side constraints. International Journal of Advanced Research and Multidisciplinary Trends (IJARMT). [Google Scholar] [Crossref]

38. Matende Richard, K., & Kuso, Y. (2026). Examining the state of security for security providers: A case study of national government administrative officers in Vihiga County, Kenya. International Journal of Transdisciplinary Research and Perspectives. [Google Scholar] [Crossref]

39. Atieno, S. G., & Kuso, Y. (2026). Healthcare financing in Kenya: Challenges, equity, and policy options. International Journal of Advanced Research and Multidisciplinary Trends (IJARMT). [Google Scholar] [Crossref]

40. Wandigu, L. A., & Kuso, Y. (2026). Evaluating resettlement action plan implementation in Kenya’s Sondu-Homabay-Awendo transmission project. International Journal of Innovative Science and Research Technology. [Google Scholar] [Crossref]

41. Ngeywo, M. J., & Kuso, Y. (2026). Evaluating the impact of e-government platforms on public service delivery in Kenya. International Journal of Research and Scientific Innovation. [Google Scholar] [Crossref]

42. Ochieng, A. C., & Kuso, Y. (2026). Impact of inflation on household consumption patterns in urban households in Kisumu, Kenya. International Journal on Research and Development - A Management Review. [Google Scholar] [Crossref]

43. Kibet, W., & Kuso, Y. (2026). Effect of external remittance on health outcomes in Kenya. Advanced International Journal for Research. [Google Scholar] [Crossref]

44. Otieno, E. O., & Kuso, Y. (2026). Behavioral biases and consumer choice: Implications for welfare in competitive markets with evidence from developing economies. International Journal of Advanced Research. [Google Scholar] [Crossref]

45. Ochieng, G. J., & Kuso, Y. (2026). Role of government subsidies on agricultural productivity in Migori County, Kenya. International Journal on Research and Development - A Management Review. [Google Scholar] [Crossref]

46. Cheruiyot, K. K., & Kuso, Y. (2026). Assessing the policy implications of external funding on the sustainability of healthcare service delivery in Kenya. International Journal of Advanced Research. [Google Scholar] [Crossref]

47. Kuso, Y. (2026). What Wajir County needs to actualize development comparable to Central Province counties in Kenya. Conference Paper. [Google Scholar] [Crossref]

48. Chacha, V. R., & Kuso, Y. (2026). The education transformation: A comparative study of Kenya's 8-4-4 system and the competency-based curriculum. International Research Journal of Scientific Studies. [Google Scholar] [Crossref]

49. Ombewa, M., & Kuso, Y. (2026). An economic analysis journal on asymmetric information on credit markets in Kenya. International Journal of Leading Research Publication. [Google Scholar] [Crossref]

50. Ochieng, R. J., & Kuso, Y. (2026). Microeconomic stability in Kenya: Implications for the informal sector and rural economies. International Journal of Advanced Research. [Google Scholar] [Crossref]

51. Madara, G., & Kuso, Y. (2025). Influence of market competition on lending rates of microfinance institutions in Kenya. International Journal of Advanced Research. [Google Scholar] [Crossref]

52. Purity, O., & Kuso, Y. (2025). General equilibrium and market incompleteness: A conceptual re-evaluation for frontier economies. International Journal of Research and Innovation in Social Science. [Google Scholar] [Crossref]

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