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*Maurice Wanyonyi orcid  -  Department of Mathematics and Statistics, University of Embu, Kenya, Kenya
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The manufacturing sector is considered a pivotal contributor to the growth of the economy around the globe. Kenya relies on the manufacturing sector to generate revenue and ultimately enhance the growth of the economy. Despite the key purpose played by these sectors in the economy, inflation rate has diversely affected their performance. The purpose of the study was to develop the Autoregressive Integrated Moving Average time series model to forecast the inflation rate in Kenya. The analysis utilized secondary data from the Kenya National Bureau of Statistics and the model was fitted to the data using R. The ARIMA  with the information criterion of 576.24 was identified as the best model. Based on the forecasting, it was established that there will be a slight shift in the inflation in the coming years. Therefore, the government should use wage and price control to fight inflation but put in place policies to prevent recession and job loss in the country. The government should also employ contractionary monetary policy to fight inflation by reducing the money supply in the economy through decreases bond prices and increased interest rates.  Implementation of these recommendations might assist in reducing the rate of inflation in the country.
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Keywords: Gross Domestic Product; Autoregressive Integrated Moving Average model; inflation rate; manufacturing sector.

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