International Journal of Statistics and Applied Mathematics
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International Journal of Statistics and Applied Mathematics

2020, Vol. 5, Issue 6, Part A

Time series analysis of Nandi county government revenue using seasonal autoregressive integrated moving average (SARIMA) model


Author(s): Cornelius Kipkeny Koech, Joel Cheruiyot Chelule, Ayubu Anapapa and Herbert Imboga

Abstract: In Kenya, there are two levels of government namely the National Government (NG) and County Governments (CGs). NG’s revenue is mainly from taxation, borrowing, and grants among other sources while CGs rely on allocation from NG as well as Own Source Revenue (OSR). CG of Nandi has been using basic descriptive statistics to analyze OSR data such as line and bar graphs with minimal forecasting capabilities. This study focuses on the Nandi county revenue analysis from 2013/14 financial year (FY) to the 2018/19 FY. The analysis showed that the Nandi county revenue department collected an average monthly revenue amounting to Ksh. 19.29 million (Ksh. 231.5 million annually). This study performed a time series analysis on the revenues using Seasonal Auto-Regressive Integrated Moving Average (SARIMA). The best SARIMA model SARIMA(0,0,0)(1,0,0)[12] chosen proved to fit well in the data. The study also projected the revenue of the CG of Nandi going into the future. The average amount of monthly revenues forecasted is Ksh. 34.97 million. This means that the county government of Nandi has a potential of raising an average of Ksh. 34.97 million monthly, Ksh. 104.91 million quarterly and Ksh. 419.64 million annually.

DOI: 10.22271/maths.2020.v5.i6a.599

Pages: 01-06 | Views: 214 | Downloads: 40

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How to cite this article:
Cornelius Kipkeny Koech, Joel Cheruiyot Chelule, Ayubu Anapapa, Herbert Imboga. Time series analysis of Nandi county government revenue using seasonal autoregressive integrated moving average (SARIMA) model. Int J Stat Appl Math 2020;5(6):01-06. DOI: 10.22271/maths.2020.v5.i6a.599
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