Seasonal Naïve Model Incorporating Trend Component for Tax Revenue Forecast in Kenya
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Date
2023
Authors
Samuel, Fredrick Kyalo
Journal Title
Journal ISSN
Volume Title
Publisher
kenyatta university
Abstract
Tax revenue is largest source of government revenue in Kenya. Nevertheless, the tax revenue
collection has overtime fell below the planned targets. Besides, Kenya has witnessed continuous
increase in public debt since public expenditures have maintained consistent growth pattern and
continually surpassed revenues. The structure of tax revenue data in Kenya exhibit seasonality
fluctuations with progressive increase (trend) in monthly tax revenue collections of the year. In
order to facilitate government in proper fiscal planning and long-term projections, modelling and
forecasting tax revenue is desirable. The objectives of this study were to develop a seasonal
naïve model incorporating the trend component for forecasting tax revenue in Kenya and use the
model to forecasting tax revenue collections in Kenya for the next two years. This research used
time series approach to build the model. The monthly tax revenue data comprising of 192 months
spanning July 2000 to June 2016 was used in this study. The study found that seasonal naïve
model with trend was appropriate model for forecasting tax revenue data since it recognized both
seasonal and trend components in the data and recommended application of the developed model
in forecasting tax revenue collections in Kenya. Modelling the causal relationship of tax revenue
with other variables that account for seasonality such as inflation, exchange rates, public
expenditure and public debt was identified for future area of study.
Description
A Research Project Submitted in Partial Fulfilment of the
Requirements for the Award of the Degree of Master of
Science (Statistics) in the School of Pure and Applied Sciences
of Kenyatta University
Keywords
Seasonal Naïve Model, Tax Revenue, Kenya