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    Forecasting Inflation in Kenya Using ARIMA Model

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    Forecasting+Inflation+in+Kenya+Using+ARIMA+Model+-+ASAREV+-+7.pdf (288.9Kb)
    Date
    2024-04-19
    Author
    Cheruiyot, Braden Kipkirui
    Onyango, Rodgers Otieno
    Mogesi, Maurine Boke
    Kisina, Maureen Mumbua
    Arani, Michelle Mokeira
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    Abstract
    This study was to investigates the dynamics of inflation in Kenya through the application of advanced time series modeling techniques, specifically Autoregressive Integrated Moving Average (ARIMA) analysis. Inflation is a critical economic indicator that directly influences monetary policy, investment decisions, and overall economic stability. Given the dynamic of inflation in emerging economies such as Kenya, a fine understanding of its patterns and the ability to make accurate forecasts are imperative for policymakers, businesses, and investors. The ARIMA (2,2,2) model was employed to capture the underlying trend and seasonality in the inflation data, providing insights into the historical behavior of inflation in Kenya. In this study, we used R programming software and STATA to analyze and generate meaningful information from the data. The data was obtained from World Bank for a period from 1960 to 2022.
    URI
    https://doi.org/10.51867/Asarev.Maths.1.1.7
    https://asarev.net/ojs/index.php/asarev/article/view/8
    http://ir-library.mmust.ac.ke:8080/xmlui/handle/123456789/2934
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